Your Power Platform Trainer: J. H. Irwin
Author | Content Creator | Technology Strategist

At some point in the last few weeks, someone probably asked you how the requests were going.

If you have been following along, you built the Team Requests tracker in Module 2 and gave it flows in Module 3, so you almost certainly said “fine” or “busy” and meant it. But I would bet you did not actually know. Not how many came in last week compared to the week before, not which category quietly doubled, not whether the person you think is overloaded actually is. The data to answer every one of those questions has been accumulating in your Dataverse table since the day you built the app. It has just been sitting there in rows, and rows are a terrible way to see anything.

That is the whole of this module. Your system has hands and a heartbeat. Now we give it sight. By the end you will have a one-page Power BI report, built on the same Team Requests table, that answers the questions you have been guessing at, and you will have published it where your team can see it. Along the way I will show you the two or three ideas that separate people who make charts from people who understand their data, because the tool is the easy part.

What Power BI Actually Is

People tend to arrive at Power BI thinking it is Excel with nicer charts, and it is worth spending a paragraph dismantling that, because the misunderstanding causes most early frustration.

Excel is a grid where data and calculations live together on the same sheet, and you can type anything anywhere. Power BI separates three things that Excel blurs. First there is a model, a clean, structured copy of your data with defined columns, relationships between tables, and calculations that live in one place. Second there are reports, the visual pages built on top of that model. Third there is the service, the cloud home where reports are published, refreshed, and shared. The discipline of keeping those separate is exactly why a Power BI report can be handed to three hundred people and still be right, while a shared spreadsheet becomes a rumor after its third recipient.

There are two pieces of software. Power BI Desktop is a free Windows application where you connect to data, shape it, and build reports. This is where authors work. The Power BI service at app.powerbi.com is where finished reports go to be seen, and it is where the licensing lives, which we will get to plainly at the end. For today, the pattern is simple: build in Desktop, publish to the service, share from there.

One more piece of vocabulary. A report is one or more pages of visuals that all sit on a single model and filter each other. A dashboard in Power BI is a specific thing, a single pinned-together summary page that can combine tiles from several reports, and it is not what you build first. When people say “build me a dashboard,” nine times out of ten they mean a report page, and that is what we are making.

Getting Your Data Into Desktop

Install Power BI Desktop from the Microsoft Store or from Microsoft’s site; it is free and there is no trial clock on it. Open it, sign in with the same account you used for your developer environment, and you are ready.

Choose Get data and look for Dataverse in the list. Sign in if prompted, and you will see your environments. Pick the developer environment where your Team Requests app lives, then expand it and tick your Team Requests table. Before you click Load, glance at the two connection options Desktop offers. Import copies the data into your report file, which makes everything fast and lets you shape it freely, at the cost of the data being a snapshot until it is refreshed. DirectQuery leaves the data in Dataverse and asks for it live, which sounds better and almost never is for a table this size, because every click becomes a round trip. Choose Import. I will show you how to keep it fresh later.

Now, instead of loading straight away, click Transform data. This opens Power Query, the shaping room, and it is the most underrated part of the whole product. The Team Requests table will arrive with far more columns than you created, because Dataverse quietly adds system columns for ownership, versioning, and audit. Remove everything you do not recognize; you can always add a column back. Rename anything awkward so that the labels a colleague sees on a chart are the words your team actually uses. Check that your date columns show a calendar icon and your priority and status columns show text, because a date that Power BI thinks is text will refuse to make a timeline.

While you are here, add the one column that will make this report worth building. Select the Completed On date column and the Created On date column, or whatever you named them in Module 2, and use Add Column to subtract one from the other. Name the result Days to Complete. Every step you take in Power Query is recorded in a list on the right, and it will be replayed automatically on every refresh from now on. You are not editing data. You are writing a recipe, and this is the moment most people realize Power BI is nothing like a spreadsheet.

Click Close & Apply and your model is ready.

One Measure, Then We Build

Power BI has its own formula language called DAX. It is powerful, it is deep, and you do not need almost any of it today, so I am going to give you exactly one measure, both because you will use it and because writing one demystifies the rest.

In the Data or Model view, right-click your table and choose New measure, and type:

Open Requests = CALCULATE(COUNTROWS('Team Requests'), 'Team Requests'[Status] = "Open")

Read it aloud and it says what it does: count the rows, but only where Status is Open. The word CALCULATE is doing the filtering, and that one pattern, count something under a condition, is the foundation of most reporting DAX you will ever meet. If your status values differ, change the word in quotes and nothing else. A measure is a calculation that responds to whatever is on the page. Put it beside a chart of categories and it becomes open requests per category without you writing anything more. That responsiveness is the thing to fall in love with.

Building the Page

Switch to the Report view. You have a blank canvas, a Visualizations pane of chart types, and a Data pane listing your columns and your new measure. Building a visual is a matter of choosing a chart type and dragging fields into its wells. Here is the page I would build, in the order I would build it, with the question each visual exists to answer. Notice that every visual starts with a question. A chart without a question is decoration.

How much is open right now? Add a Card visual and drop your Open Requests measure onto it. One big number. Resize it and put it top left, because it is the first thing anyone will look for.

Are requests speeding up or slowing down? Add a Clustered column chart, put Created On on the x-axis, and drag any column, the request title will do, into the y-axis well, then change its aggregation to Count. Power BI will offer you a date hierarchy of year, quarter, month, and day; use the chart’s drill controls to settle on Month or, if your table is young, Day. This single chart answers the question your boss actually asked.

Where is the work coming from? Add a Bar chart with Category on the y-axis and a count on the x-axis. Sort it descending so the biggest bar is on top. Now do the same again with Assigned To, and lay the two side by side. You have just made visible the two things everyone argues about in meetings: what kind of work dominates, and who is carrying it.

How long does it take? Add another Card with Days to Complete and set its aggregation to Average. Then, because averages lie, add a Table visual with Title, Assigned To, Due Date, and Status, and use the visual’s Filters pane to show only rows where Status is Open and Due Date is before today. Title it Overdue. This is the visual that will get the report opened every morning.

Let people ask their own question. Add a Slicer with Priority in it. A slicer is a filter the reader controls, and it turns your page from a statement into a conversation.

Now do the thing that makes Power BI feel like magic the first time. Click a bar in the Category chart. Every other visual on the page instantly filters to that category: the open count changes, the trend re-draws, the overdue table shrinks to that category’s stragglers. Click it again to release. This is cross-filtering, and it is on by default between every visual on a page that shares a model. You did not configure it. You built one model, and the model does the work.

Give the page a title, tidy the alignment, and save the file. That is a report. It took perhaps forty minutes, and it answers more about your requests than you have ever known.

Your Finished Report Page

Publishing, Sharing, and Keeping It Fresh

Click Publish in Desktop, choose a workspace in the service, and Desktop uploads two things: your model and your report. Open the service in a browser and you will find both. Your team does not need Desktop to see the report; they need a browser, or the Power BI app on their phone, or, best of all, Teams.

Sharing from the service takes several forms, and the right one for a small team is the simplest. Open the report and add it as a tab in the Teams channel your Module 3 flows already post into, so the notification, the nudge, and the picture of the whole queue live in one place. If you want it inside the app itself, the Power BI tile in Power Apps embeds a report page directly onto a screen, which for the Team Requests app means a manager can see the overview and open a request from the same place. Both feel like a small thing. Both are the reason people keep using what you built.

Because you chose Import, the report is a snapshot of the moment you last refreshed it. In the service, open the model’s settings and turn on Scheduled refresh. Dataverse is a cloud source, so there is no gateway to install and no server to fuss over; you set the times, and the recipe you wrote in Power Query is replayed against live data. Once a day is plenty for a request queue. If your team wants to see the morning’s arrivals, schedule it for just before the nudge flow runs, so the two tell the same story.

Three Things That Will Make You Better Than Most

The tool is learned. Now the craft, which is where I would rather spend the last of your attention.

Decide the question before you touch the chart. The most common failure in reporting is not a wrong chart; it is a page of twelve visuals nobody asked for, each accurate and none useful. Every visual you added today began as a plain-English question, and I would hold yourself to that forever. If you cannot say what question a visual answers, remove it. A page with four honest visuals beats a page with fourteen every time, and it loads faster besides.

Distrust your own averages. The average days-to-complete card on your page is probably wrong in an interesting way. One request that sat for ninety days will drag the average of a hundred three-day requests to nearly four, and your team will feel accused of something they did not do. Averages are a starting point. The overdue table beside it is the truth. When a number surprises you, the right instinct is not to report it, it is to click on it and find the rows underneath. Power BI makes that one click. Use it.

Model once, report many. You will be tempted, next month, to build a second report by starting from scratch. Do not. Publish the model once, and build new reports on it from the service or from Desktop using the existing model as the source. When you later fix the way Days to Complete is calculated, every report on that model is fixed at once. This is the discipline that separates reporting people trust from reporting people argue with, and it is far easier to adopt now, with one table, than later, with thirty.

The Licensing Conversation, Straight

As with every module, here are the numbers as of early September 2026, and, as with every module, Microsoft changes them, so confirm on their pricing page before anyone budgets from an article.

Everything you did in Desktop was free and will stay free. You can learn an enormous amount, build real reports, and never spend a cent. The cost begins the moment a report leaves your machine to be seen by someone else.

Power BI Pro is $14 per user per month, and it is included in Microsoft 365 E5. Here is the rule that trips up every organization once: Pro is required for the person who publishes and for every person who views a shared report. Viewers are not free at this tier. Your free account can publish to a personal workspace, which is fine for practice, but sharing with your team means Pro for the team.

Premium Per User is $24 per user per month and adds larger models, more frequent refreshes, and advanced features. As with Pro, everyone who views a report that uses those features needs the same license.

Microsoft Fabric capacity is the enterprise path: the organization buys a pool of compute rather than licensing seats, starting around $263 per month for the smallest F2 tier. The number that matters in that ladder is F64, at several thousand dollars a month, because that is the level at which report viewers no longer need a paid license at all. For a small team, per-user Pro is far cheaper. For an organization with a few hundred viewers, capacity wins. Somewhere in between, somebody does the arithmetic, and it is worth knowing that the arithmetic exists so you are not surprised by which side of it you land on. Microsoft offers a Fabric trial if you want to see the capacity experience without a purchase.

One tie back to earlier modules. The report you built reads from Dataverse, and Dataverse is a premium connector in Power Apps and Power Automate terms. Power BI licensing is its own world and does not care about that, but the app your report reads from still does. Nothing about today changes the licensing conversation you had in Module 3. It just adds a second, separate one.

Your Homework, and What Comes Next

You know the shape by now. Go back to your own app, the one you built in Module 2 to fix a small, real irritation in your work and then gave a flow to in Module 3, and build it one report page. Four visuals, each with a question you can say out loud, one slicer, and an overdue table or its equivalent. Publish it, pin it in Teams next to your flow’s notifications, and then, this is the part that matters, look at it every morning for a week. Not to admire it. To notice what it tells you that you did not already know. Somewhere in that week a number will surprise you, and you will click on it, and that is the moment you become someone who understands their data rather than someone who has a chart.

Your system now has hands, a heartbeat, and sight. It collects work, moves it, and shows you the truth about it. What it does not yet have is judgment. In the next module we bring in Copilot Studio and build something that can read a new request, decide what it is, check whether it is a duplicate, and suggest where it should go, before anyone on your team has opened it. That is the piece the whole industry is shouting about this year, and I want to show you what is real underneath the noise. Bring the app, the flows, and this report. The agent is going to use all three.

Technology is changing the world. Read about it → The Augmented Life

Your Power Platform Trainer: J. H. Irwin
Author | Content Creator | Technology Strategist

When I began this training series, I had one reader in mind: the person keeping their team afloat with a spreadsheet that was never meant to carry the load, who suspects there is a better way but has never been handed a map. Everything about the series was built for that person, the plain English, the honest licensing talk, the hands-on builds. And the more of you I have heard from, the clearer one thing has become: these modules do the most good when nothing stands between them and the person who needs them. So I am making a change. Effective today, the entire Learn Power Platform section of The Augmented Life is free for everyone, every module, past and future.

Paid subscriptions will remain available, but they will be entirely optional. Those who choose to become paid subscribers will be supporting the time, research, writing, and care required to keep this publication growing. A paid subscription will become an act of support, not a price of admission. To those who have already chosen to support this work, thank you. You are, quite literally, the reason I can open these doors.

If you are just arriving, Modules 1 through 3 are waiting for you: the map of the platform, your first app, and the automations that set it in motion, with more on the way. And if you know someone wrestling with one of those overworked spreadsheets, this would be a fine moment to send them here. That has always been the point of this series, and now there is nothing in the way.

"I've spent my career building with technology and my life writing about what matters. These free courses are my attempt to do both at once, and I hope they open a door for you."

Technology is changing the world. Read about it → The Augmented Life

By J. H. Irwin
Author | Content Creator | Technology Strategist

For more than thirty years, I have done two things most people treat as separate careers

I build enterprise technology, and I write about what technology does to people. It took me a long time to realize these are not separate pursuits. In many ways, they are the same job.

Organizations often describe digital transformation as a technology initiative. They select a platform, approve a budget, assemble a project team, and begin building. Success is measured by whether the system launches on time, stays within budget, and meets its technical requirements.

Those things matter, but they do not mean transformation has occurred. A system can launch successfully while employees continue maintaining private spreadsheets, forwarding information through email, and relying on personal workarounds because the new technology never earned their confidence.

I have spent more than twenty years working inside large financial institutions and other complex organizations. My home has largely been the Microsoft ecosystem, including Power BI, Power Apps, Power Automate, SharePoint, Dataverse, and Microsoft Fabric. Across different platforms and business problems, the pattern remains remarkably consistent. Critical processes are often living in spreadsheets, email chains, disconnected documents, and one person’s memory.

Turning those processes into governed systems can be technically demanding, especially when they must withstand security requirements, audits, and regulatory scrutiny. Yet building the technology is only part of the challenge. The system must also make sense to the people whose daily routines it will change.

People Are Not the Problem

When employees hesitate to adopt new technology, they are often described as resistant to change. That description is convenient, but frequently unfair. People do not resist simply because they are stubborn or unwilling to learn.

They resist when they do not understand why the change is necessary, when decisions affecting their work are made without their participation, or when training arrives after the important choices have already been made. They may also remember previous technology projects that promised greater efficiency but created more work and frustration.

A familiar process can also become part of someone’s professional identity. The employee who maintains the spreadsheet, understands every exception, and knows how to correct every error may have spent years becoming indispensable. When a new system appears, that person may not see efficiency. They may see their expertise being transferred into software and wonder whether the organization will still value them.

That is not irrational resistance. It is a human response to uncertainty.

Communication Is Part of the Technology

Successful adoption begins before the system is built. The people closest to the work understand where the current process breaks, which exceptions matter, and which workarounds exist because the existing tools failed them. Their knowledge should help shape the solution from the beginning.

Training must also involve more than demonstrating buttons, menus, and screens. Employees need to understand what problem the technology solves, how it will improve their work, what will change, and where they can find help when something goes wrong.

This is where my years as a writer have influenced my work in technology. Writing taught me how to explain complicated ideas to intelligent people who do not share my vocabulary. People should not need to become technologists to understand how technology will affect their lives.

Instead of explaining that a new solution uses Dataverse, automated workflows, or an advanced reporting model, tell people what those capabilities mean. Information will no longer need to be entered three times. Approvals will not disappear inside an inbox. Leaders and employees will finally be working from the same numbers.

Those are outcomes people can understand and evaluate.

Trust Cannot Be Installed

Organizations can install software, configure permissions, migrate data, and automate processes. They cannot install trust. Trust develops when the technology works consistently, the information is accurate, employees feel heard, and leadership treats adoption as a shared responsibility.

If the system is unreliable or promised support never arrives, people will return to the tools they know. The old spreadsheet may be inefficient, but it feels safe because they understand it. Familiarity often wins when confidence in the replacement has not been earned.

The most successful systems I have built were not necessarily the ones with the most features. They were the ones that gave underwriters, risk teams, project managers, and executives information they could finally trust. They replaced fragile processes with something that could withstand both an audit and an ordinary difficult day.

As artificial intelligence and automation become more deeply embedded in the workplace, the human factor will become even more important. These technologies will reshape roles, redistribute knowledge, and cause many employees to question what they contribute and where they belong.

Organizations that dismiss those concerns as resistance will struggle. Those that recognize them as legitimate human questions will be better prepared to create technology that augments people instead of alienating them.

The future of work will not be determined solely by what technology can do. It will also be determined by whether people understand it, trust it, and believe there is still a meaningful place for them in the future it is creating.

Technology is changing the world. Read about it → The Augmented Life

Your SharePoint Trainer: J. H. Irwin
Author | Content Creator | Technology Strategist

The Augmented Life | Learn SharePoint Online | Module 1 | Updated August 2026

Somewhere in your organization there is a folder called Final. Inside it is a file called Budget_FINAL_v3_revised.xlsx, and next to that is Budget_FINAL_v3_revised_USE_THIS_ONE.xlsx. Nobody is entirely sure which one is current. The person who would know is in a meeting. Three people have copies on their desktops, each slightly different, and next Tuesday someone will paste the wrong numbers into a presentation and spend an afternoon figuring out why they do not add up.

If any of that sounds familiar, this section of the series is for you. I have spent a good part of my career watching capable, intelligent people build elaborate systems out of spreadsheets, email threads, and shared folders because those were the only tools anyone ever handed them. The systems work, mostly, right up until they don’t. And when they fail, it is never because the people were careless. It is because the tools were never designed to carry that much weight.

SharePoint Online was designed for it. That is the whole point of this section: to show you that the tool most people think of as “the place where files go” is actually the foundation of a connected workplace, one where documents, structured data, conversations, apps, automation, and reporting all live in the same house and know about each other. And, as with everything in this series, you will not need a development background to make use of it. If you can build a spreadsheet, you already have most of the instincts you need.

The Tool Everyone Uses and Nobody Notices

Here is something that surprises a lot of people: if your organization uses Microsoft Teams, you are already using SharePoint every day. Every file you upload to a Teams channel is stored in a SharePoint document library. Files uploaded to one-to-one or group chats are stored in the sender’s OneDrive, and sharing a link does not move the original file. Every team you belong to has a SharePoint site quietly standing behind it. Teams is the front door; SharePoint is the house. Most people only ever see the door.

That is by design, and it is also why SharePoint has such a strange reputation. It is simultaneously one of the most widely used business tools on the planet and one of the least understood. People form their opinion of it from a clunky intranet they were forced to use a decade ago, or from a colleague’s folder structure that went seven levels deep for no discernible reason. Neither of those is SharePoint’s fault, exactly, but SharePoint took the blame.

So let me offer a cleaner mental model. SharePoint Online is a service, included in many Microsoft 365 business and enterprise plans, that gives you sites. A site is a workspace for a group of people with a shared purpose: a department, a project, a committee, an entire company. Inside a site, you can keep three kinds of things. You can keep documents, organized in libraries that are considerably smarter than folders. You can keep structured data, organized in lists that look like spreadsheets but behave like databases. And you can keep pages, which are simply web pages you build without writing code, used for news, announcements, and pulling everything else together into something people actually want to look at.

That is the basic model: sites containing documents, data, and pages. Everything else in this section is about what happens when you connect those things to the rest of Microsoft 365.

Documents, Done Properly

Let me start with the part everyone expects, because even here SharePoint is doing more than most people realize. A document library looks like a folder, and you can use it like one. But underneath, it keeps a version history of every file automatically. When someone overwrites the budget with the wrong numbers, you open the version history, see who changed what and when, and restore the previous version with one click. The FINAL_v3_revised_USE_THIS_ONE problem simply stops existing, because there is only ever one file, and the file itself remembers its own past.

Libraries also support co-authoring, which means several people can have the same Word document, Excel workbook, or PowerPoint deck open at once, each seeing the others’ cursors and edits in real time. No more emailing attachments back and forth and merging changes by hand. If you have used this in Teams, you have used SharePoint’s co-authoring; it is the same engine.

The feature that most changes how people find and manage documents, though, is metadata. In a folder, the only thing you know about a file is its name and where it sits. In a library, you can add columns, exactly the way you would add columns to a spreadsheet, and those columns describe the file. A contracts library might have columns for Client, Contract Type, Expiration Date, and Status. Now you are no longer digging through folders named by whoever set them up. You are filtering: show me every active contract expiring in the next ninety days. You can save that filter as a public view and, with the necessary permissions, make it the library’s default view so the whole team sees it first. Folders make you remember where things are. Metadata lets you ask for them.

Permissions round it out. You can control who sees a site, a library, a folder, or a single document, and, when external sharing is enabled by your organization, you can share a file with someone outside the organization without giving them access to anything else. It is the difference between a shared drive where everyone can see everything and a workspace where people see what they need.

Lists: Where the Spreadsheet Goes to Retire

This is the part of SharePoint I most want you to understand, because it is where the “spreadsheet doing a job it was never meant to do” finally gets to rest. A SharePoint list is a table of rows and columns, and if you squint, it looks like a spreadsheet. The difference is in what the columns know. In a spreadsheet, every cell will accept anything. Someone types “next Tuesday” into a date column, someone else types “Done” where everyone else typed “Complete,” and six months later the data is unreliable and nobody trusts the totals. In a list, each column has a type.

A Date column only accepts dates and gives you a calendar picker. A Choice column can offer a fixed set of options with fill-in choices disabled, so “Done” and “Complete” cannot both exist. A Person column looks up real people from your organization’s directory, which means you can assign a request to a colleague and use that identity in notifications and workflows. There are columns for numbers with validation, currency, yes/no toggles, hyperlinks, images, and lookups into other lists.

Because the data is clean, everything built on top of it works. You can create multiple views of the same list: a calendar view of due dates, a board view grouped by status that looks and behaves like a Kanban board, a filtered view showing only what is assigned to you. Every row gets its own form for adding and editing, generated automatically. Version history is enabled automatically on newly created Microsoft 365 lists, so you can see who updated an item and restore an earlier version. Existing lists may differ if they predate that change or an administrator has disabled versioning. Several people can work in the list simultaneously without passing separate copies back and forth, which is the exact thing spreadsheets are worst at.

Microsoft also surfaces lists through an app called Microsoft Lists, available on the web, in Teams, and through a mobile web browser, with ready-made templates for things like issue tracking, asset management, onboarding checklists, and event itineraries. Under the hood, those are SharePoint lists. The app is simply a friendlier front door to the same thing. Microsoft retired the dedicated iOS and Android Lists apps in November 2025, but the mobile web experience remains supported.

Now the honest part, because this series does not do hype. A SharePoint list is not a full relational database. A list can contain up to 30 million items, and the 5,000-item List View Threshold is not a limit on the list itself. It limits resource-intensive queries that try to process more than 5,000 items at once, which is why indexed columns and filtered views become essential as a list grows. SharePoint is excellent at the kind of data most teams actually have: requests, assets, projects, contacts, checklists, inventories. It is the wrong tool for something with millions of transactions or dozens of deeply interrelated tables. When you get there, a tool such as Dataverse or a proper relational database is usually the better fit. Most teams never get there, and for most of the spreadsheets in your organization, a list is exactly the right size.

Workspaces People Actually Use

Sites are generally created from one of two main templates, and knowing which is which saves a lot of confusion. A team site is a workspace for a group that works together. It is usually restricted to members, and everyone in the group can contribute. This is where the documents and lists for that team live. When you create a team in Microsoft Teams, you get a team site automatically. When you create a Microsoft 365 group-connected team site directly in SharePoint, you can add Microsoft Teams to it later. They are two views of the same workspace.

A communication site is for broadcasting to many people. Think of a company intranet, an HR portal, or a project showcase. A small number of people publish; everyone else reads. These sites are built from pages, which you assemble from web parts: blocks for text, images, news, embedded documents, lists, calendars, videos, and much more. You drag them into place, and the result is a proper website that works on phones and laptops alike, without a line of code. News posts are pages with a special flag that makes them roll up across sites and appear in people’s SharePoint feeds. Depending on how the organization is configured, that news can also surface in Microsoft Teams and Viva Connections, so an announcement published on the HR site shows up where employees actually spend their day.

Hub sites connect related sites together with shared navigation, branding, and search, so a department with six project sites can present them as one coherent place instead of six islands. Search, incidentally, is one of SharePoint’s quietest strengths. It indexes the contents of documents, not just their names, and it respects permissions, so you find what you are allowed to find.

All of this is the “collaborative workspace” part of the promise. But the reason SharePoint deserves a whole section of this series, rather than one article, is what happens when you connect it to the four tools sitting right next to it.

SharePoint and Microsoft Teams

I have already given away the central fact: Teams and SharePoint are two faces of the same workspace. It is worth spelling out why that matters in practice. Files available in a Teams channel’s Shared tab are stored in SharePoint. For a standard channel, files are stored in a folder in the team’s default document library. Private and shared channels use separate SharePoint sites so their membership and permissions remain isolated.

Everything I described above about version history, co-authoring, metadata, and views is available to those files; you simply select “Open in SharePoint” to get the full experience. Many teams work in Teams for years without realizing that the library behind their channel can have columns, views, and approval workflows attached to it.

The connection runs in the other direction, too. A Team Requests tracker can be built as a SharePoint list and added as a tab within a Teams channel, so people can log a request, discuss it, and update its status without ever leaving Teams. SharePoint libraries, pages, and news can also be brought into Teams, depending on how the organization has configured the experience. The practical upshot is that you rarely have to convince anyone to “go to SharePoint.” You bring SharePoint to where they already are.

SharePoint and Power Apps

Power Apps can use a SharePoint list as its data source, making SharePoint an accessible place to begin in many organizations. You can start with the form already attached to the list and build outward from there.

The simplest integration takes about thirty seconds. A standard SharePoint list has an automatically generated form for adding and editing items, and it is perfectly serviceable. But you can open that form in Power Apps and customize it: rearrange fields, hide the ones a particular audience does not need, add conditional logic so that choosing “Hardware” as a request type reveals a field for the asset tag, and add validation that explains itself in plain language. The customized form replaces the default one, right there in the list, and nobody using it needs to know Power Apps was involved.

The fuller integration is a standalone canvas app connected to one or more SharePoint lists. This is how you turn a list into a mobile app for people who work away from a desk: field technicians logging inspections, event staff checking in attendees, a warehouse team recording stock counts with photos attached. The app reads from and writes to the same list your office colleagues see in a browser, so there is one source of truth no matter which screen someone is holding.

There are two cautions to remember as these apps grow. Formulas working with larger lists must use operations that Power Apps can delegate to SharePoint, or an app can return incomplete results. Sharing the app also does not automatically give someone access to its SharePoint data, so both the app and the underlying list must be shared with the right people.

Here is the part that matters for anyone watching costs. The SharePoint connector is a standard connector. Qualifying Microsoft 365 plans include limited Power Apps rights, so solutions that use only SharePoint and other standard connectors may not require a separate Power Apps Premium license. Premium or custom connectors, an on-premises data gateway, and other premium capabilities require additional licensing. Dataverse-based production apps generally require Power Apps Premium, pay-as-you-go, or qualifying Dynamics 365 rights, with Dynamics 365 use rights limited to apps operating within the context of the licensed Dynamics application. There is also an important exception for Managed Environments, where every active Power Apps user needs a qualifying standalone license, pay-as-you-go plan, or capacity-based entitlement even when the app uses only standard connectors. For a great many everyday business solutions outside that exception, SharePoint is not just adequate; it can be the lower-cost path.

SharePoint and Power Automate

Every Power Automate flow follows the same basic shape: when this happens, do these things. SharePoint is one of the richest sources of “this happens” anywhere in Microsoft 365.

A flow can trigger when an item is added to a list, when one is modified, when a file is uploaded to a library, when a file’s properties change, or on a schedule that checks a list for anything meeting a condition. From there, the actions are whatever you need. When a new request is logged, notify the right person in Teams and set a due date. When a request has sat in “Pending” for three business days, send a gentle reminder. When a status changes to “Complete,” email the requester and archive the item. When a contract in the library reaches sixty days before expiration, alert the account owner.

Approvals deserve their own mention, because this is the workflow every organization has and almost none have automated well. A document is uploaded to a library. A flow sends an approval request to a manager, who receives it in Teams or Outlook, reads the summary, and taps Approve or Reject without opening anything else. The flow records the decision, updates a Status column on the document, and notifies the author. That whole process, which used to live in a chain of forwarded emails and a spreadsheet someone maintained by hand, becomes something that runs itself and leaves a recorded history of the decision behind.

You do not even need to start in Power Automate. Lists and libraries offer built-in rules and an “Automate” menu with options such as reminders based on a date column, which you can configure in a few clicks. As with Power Apps, SharePoint is a standard connector. Qualifying Microsoft 365 plans include limited Power Automate rights for cloud flows that use standard connectors, while premium or custom connectors, an on-premises data gateway, and other premium capabilities require additional licensing. In a Managed Environment, every user who runs a cloud flow also needs a qualifying standalone license, pay-as-you-go plan, or capacity-based entitlement.

SharePoint and Power BI

The last connection closes the loop. Once your requests, assets, or projects live in a clean list instead of a messy spreadsheet, that list becomes reliable data, and reliable data is what Power BI wants.

Power BI connects directly to SharePoint as a data source. The SharePoint Online List connector brings in list data, while the SharePoint Folder connector works with files stored in document libraries. From a list, you can build the reports that spreadsheets never quite managed: requests by category over time, average days to completion by assignee, open items by priority, and a trend line that shows whether the team is keeping up or falling behind. You can also choose Export > Export to Power BI from a SharePoint list to create a semantic model in the Power BI service, or connect through Power BI Desktop when you need more control over transformation and modeling.

The reports go back into SharePoint, too. A Power BI web part lets you embed an interactive report or individual visual on a modern SharePoint page. Put it at the top of the team site, and the report becomes the first thing people see when they open the workspace, with data drawn from the same list at the semantic model’s latest refresh. Viewers still need permission to both the SharePoint page and the Power BI report. Data goes in through a list or an app, gets processed by a flow, and comes back out as a picture on a page. Nobody manually exported a spreadsheet or passed a file around.

One caveat, in keeping with the rest of this series: Power BI Desktop is free for authoring. To create content in a workspace other than My Workspace, securely share it, or embed it in SharePoint Online, the creator needs Power BI Pro or Premium Per User. Pro viewers can consume content in a shared Pro workspace, but a Premium Per User workspace requires Premium Per User for every viewer. Users with a Fabric Free license can view content on qualifying capacity, such as Microsoft Fabric F64 or larger, when they have Viewer access. Capacities below F64 do not remove the Pro or Premium Per User requirement. The building can begin for free; secure sharing has a cost, and it is worth knowing before you promise a report to your leadership team.

What It Looks Like When It All Connects

Let me put the pieces together with the scenario we will develop throughout this series: the Team Requests tracker. It will begin as a SharePoint list with columns for Title, Requester, Category, Priority, Assigned To, Status, and Due Date. The list will live on the team’s SharePoint site and appear as a tab in the corresponding Teams channel. We will customize the default form in Power Apps so that it asks only the questions that matter for each category. Field staff will be able to use a small canvas app on their phones to log requests from wherever they are, with those requests landing in the same list.

A Power Automate flow will watch the list. When a new request arrives, it will post a message in the channel and notify whoever is assigned. If a request is marked Urgent, it will start an approval with the team lead. If anything sits untouched for three days, it will send a reminder. When a request is completed, it will thank the requester and file the item away.

On the site’s home page, we will place a Power BI report showing the month’s volume, the backlog by priority, and how long requests are taking. The manager will be able to review it during the Monday meeting instead of asking someone to “pull the numbers.”

Every part of that can be built by people who do not write code, using tools many organizations already have available, on a foundation that keeps the history, enforces the rules, and scales as the team grows. That is what “a connected, scalable digital workplace” actually means, once you strip away the language that usually surrounds it. It is a list, a site, an app, a flow, and a report, all pointing at the same truth.

What It Honestly Costs

SharePoint Online is included in many Microsoft 365 business and enterprise plans, including Business Basic, Business Standard, Business Premium, and E3 and E5 suites, which means many organizations reading this already have access to it. As of August 2026, Microsoft no longer sells standalone SharePoint Online Plan 1 or Plan 2 to new customers. Those plans entered a phased retirement after May 31, 2026, and Microsoft 365 suites are now the primary path for new customers. Existing standalone contracts follow Microsoft’s published transition schedule.

SharePoint tenant storage is generally pooled at 1 TB plus 10 GB for each eligible license purchased, and additional storage can be purchased when needed. The integrations covered in this article use the standard SharePoint connector for Power Apps and Power Automate, but the exact rights depend on your Microsoft 365 plan, whether the solution introduces premium capabilities or connectors, and whether it runs in a Managed Environment. Power BI Desktop is free, while publishing, securely sharing, and embedding reports generally require paid licenses or qualifying capacity.

These licensing details are current as of August 2026, and I will update this module when Microsoft changes them, which Microsoft does. Before making a purchasing decision, confirm the terms on Microsoft’s current SharePoint plan, Power Platform licensing, and Power BI licensing pages.

Where SharePoint Is Not the Answer

I would be doing you a disservice if I left you thinking SharePoint is the right home for everything. It is the wrong choice for very large or highly relational datasets, where Dataverse or a proper database will serve you better. It is not designed as a customer-facing product; the audience for a SharePoint site is your organization and the guests you invite, not the general public. And it rewards a little planning. A site with no structure, no metadata, and folders nested nine deep is just a shared drive with a nicer logo. The next modules in this section will show you how to avoid that, because the difference between a SharePoint site people love and one they avoid is almost always decided in the first hour of setting it up.

Where We Go From Here

The reason I keep returning to that spreadsheet is not that spreadsheets are bad. It is that they were asked to do something they were never built for, and the people asking had no other option. That is no longer true. SharePoint Online gives ordinary teams a way to keep their documents honest, their data clean, their conversations connected, and their routines automated, using core SharePoint, Power Apps, and Power Automate capabilities that many organizations already license through Microsoft 365. Power BI sharing, Dataverse, premium connectors, and Managed Environments may add licensing costs, depending on how the solution is built and governed.

In the next module, we will create a site from scratch, build the Team Requests list properly, and set up the views and forms that make it feel less like a database and more like a place your team wants to work. Bring the spreadsheet. We are going to retire it kindly.

Technology is changing the world. Read about it → The Augmented Life

Your AI Trainer: J. H. Irwin
Author | Content Creator | Technology Strategist

For the past few years, learning artificial intelligence has largely meant learning how to write better prompts.

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By J. H. Irwin
Author | Content Creator | Technology Strategist

If you blinked this past month, you probably missed the moment humanoid robots stopped being a spectacle and started being an industry.

There was no single viral video, no robot doing a backflip on your feed. What happened instead was quieter and, I would argue, far more important. The paperwork got filed. The safety standards got written. The production lines got scheduled. That is what maturity looks like, and it rarely trends.

Let me walk you through what actually happened, in plain English, because the details tell a story the headlines keep missing.

The money stopped pretending

Agility Robotics, the Oregon company behind the warehouse robot Digit, announced plans to go public. The deal values the company at roughly $2.5 billion and is expected to raise more than $620 million, the largest capital raise in the history of humanoid robotics. If it closes, Agility becomes the first pure-play humanoid company traded on public markets, which means ordinary investors will finally get a look at the actual finances of this business rather than the carefully curated demo reels.

That transparency matters more than the dollar figure. For years, this industry has run on promises and private money. A Shenzhen startup raised over $700 million just last week. Figure AI was valued at $39 billion last fall. Those numbers are dizzying, but they tell us what investors hope. A public company has to tell us what is true.

One detail from Agility charmed me. Their CEO described a test where engineers scattered trash across a floor and told Digit, simply, to clean up the mess. The robot sorted everything correctly, right down to recognizing that bubble wrap does not belong in the recycling bin. My neighbors have not mastered that one yet.

The factories are real now

Tesla is converting part of its Fremont plant to build the third generation of its Optimus robot, with production targeted for late this summer. Elon Musk has admitted, to his credit, that the Optimus units working inside Tesla facilities have been more research project than workforce. The honest version of this story is that Tesla is still catching up to its own announcements. But a production line is a production line, and this one is designed to eventually build a million robots a year.

Meanwhile, Figure AI is quietly doing what Tesla keeps promising. Its factory is turning out more than 55 robots a week, with over 350 delivered, and its machines are doing paid work sequencing parts at BMW’s plant in South Carolina. Boston Dynamics is shipping its first electric Atlas units to Hyundai and to Google DeepMind. These are not pilots dressed up for the cameras. These are invoices.

A robot for your living room, sort of

The strangest story of the month came from China, where UBTech launched a full-size humanoid called the U1, marketed not for factories but for companionship. It has a biomimetic spine, remarkably lifelike movement, and an AI the company claims can recognize more than twenty distinct emotional states. The price is about $17,600, roughly what you would pay for a decent used car. More than 13,000 people have already ordered one.

I will admit this one sits differently with me. I am genuinely optimistic about machines that carry boxes and load sheet metal, because that work wears human bodies down. A machine built to keep you company raises questions that have nothing to do with engineering. Whether a robot can ease loneliness, and whether it should, is a conversation we are going to need to have as neighbors and families, not just as consumers. Thirteen thousand orders suggest we should have it soon.

The most important story is the most boring one

NVIDIA announced something called Halos for Robotics, a safety architecture for humanoid and industrial robots, built on nearly two decades of work certifying self-driving cars. Agility’s Digit is the first commercial humanoid to adopt it.

I know. Your eyes glazed over. Stay with me, because this is the one that determines everything else. Robots do not get to work alongside people because a demo looked impressive. They get to work alongside people when insurers, regulators, and factory managers can point to a certification and say this machine meets a standard. Every technology you trust today, from your car to your toaster, went through this unglamorous phase. Humanoid robots just entered theirs.

What it all adds up to

Add one more scene to the picture. At RoboCup, the international robot soccer competition, humanoid teams played full matches this year with an agility that would have seemed impossible five years ago. A middle school team from Macau competed by training their algorithms in simulation before loading them onto real robots. Children are now programming humanoids as a school project.

Here is the realization I keep arriving at. The era of asking whether humanoid robots will work is ending. The era of deciding how we want to live with them is beginning, and that second question belongs to all of us, not just the engineers. The companies made real progress this month. The rest of us should start doing the same.

Technology is changing the world. Read about it → The Augmented Life

Your Power Platform Trainer: J. H. Irwin
Author | Content Creator | Technology Strategist

At the end of Module 2, you held something you built in your own hand: a working app on your phone, collecting your team's requests into a proper cloud database

I promised that this time we would make that work move, and I intend to keep that promise. By the end of this module, your app will have a colleague. It will not take lunch breaks, it will not forget, and it will notice a new request the instant one arrives, at two in the afternoon or two in the morning, and quietly do something useful about it.

That colleague is Power Automate, and I want to be honest about why I find it the most quietly life-changing tool in the entire platform. Apps are visible; people admire apps. But the hours that disappear from most working lives do not vanish into a lack of apps. They vanish into forwarding, reminding, copying, checking, and nudging, the connective tissue of work that nobody is paid to do and everybody does anyway. Automation gives those hours back, and it does it without fanfare. Nobody ever sees the reminder you did not have to send.

If you are joining the series here, welcome. Module 1 maps the whole Power Platform in plain English, and Module 2 walks you through creating a free developer environment and building a Team Request tracker app. This module builds directly on that app, so if you skipped the homework, twenty minutes with Module 2 will set you up.

What a Flow Actually Is

Everything in Power Automate is a flow, and every flow has the same skeleton: when this happens, do these things. The “when” is called a trigger, and there is exactly one per flow. The “do these things” are actions, and there can be as many as you need, including branches, conditions, and loops. That is the entire mental model. Everything else is detail.

Flows come in three flavors, distinguished only by their trigger. Automated flows start when something happens in a system: a row is added to a table, an email arrives, a file lands in a folder. Scheduled flows start when a clock says so: every morning at eight, every Friday, on the first of the month. Instant flows start when a person pushes a button, often from inside a Power App or from the Power Automate mobile app. We will build the first two today. (There is a fourth family, desktop flows, which teach software to operate other software by mimicking a human at the keyboard. That is robotic process automation, it is wonderful for wrangling stubborn legacy systems, and it deserves its own module later in this series.)

The vocabulary from Module 1 pays off here, because flows speak to the outside world through connectors, the same thousand-plus bridges that Power Apps uses. And one more term will complete your kit: dynamic content. When a flow triggers because a new request was created, everything about that request, its title, its due date, who created it, becomes available for the actions that follow, like ingredients laid out on the counter. Building flows is mostly the art of arranging those ingredients.

A Short Tour, Then We Build

Open make.powerautomate.com and confirm the environment picker in the top-right corner shows your developer environment, the personal workshop you created in Module 2. Habit two from that module applies for life: real building happens in a deliberate environment, never the shared junk drawer.

The left navigation is simple: Create for new flows, My flows for everything you have built, and Templates, a gallery of thousands of prebuilt flows shared by Microsoft and the community. The templates gallery is worth ten minutes of browsing sometime, not because you will use them as-is, but because reading what other people automate is the fastest way to notice what you could. And like Power Apps, the modern designer includes Copilot: describe a flow in a sentence and it will draft one. Same advice as Module 2, and I will not belabor it: build by hand first. The autopilot serves the pilot, not the other way around.

Build One: The Instant Notification

Our first flow answers the most common automation wish in existence: tell me the moment something needs my attention. When a new Team Request is created, we will post a message to Microsoft Teams.

Step one. Choose Create, then Automated cloud flow. Name it something honest, like Notify on new Team Request, and search the trigger list for Dataverse’s “When a row is added, modified or deleted.” Select it and create the flow.

Step two. Configure the trigger. Set Change type to Added, choose your Team Requests table, and set Scope to Organization. That last setting simply means “fire no matter who created the row,” which is what you want for a team tool.

Step three. Add an action. Click the plus below the trigger and search for Teams, then choose “Post message in a chat or channel.” Point it at a team and channel you can see (your own test team is fine while learning). Now click into the message box and watch the dynamic content panel appear, listing every column from your table. Compose something like: New request: [Name] — due [Due Date]. Details: [Details]. You are not typing values; you are placing the ingredients, and the flow will fill in the real ones at runtime.

Step four. Save, then test it the satisfying way: open your Module 2 app on your phone and submit a request. Within a few seconds, Teams chimes with a message describing exactly what you just entered. Take a moment with that. Your app and your flow just cooperated without you, and that little chime is the sound of an entire category of “hey, did anyone see my request?” follow-up messages becoming unnecessary.

Build Two: The Morning Nudge

The second flow demonstrates scheduled automation, and it addresses the second most common wish: remind me before things are late, not after. Every morning at eight, this flow will look for requests due within a day that are not finished, and it will nudge you about each one.

Step one. Create a Scheduled cloud flow named Daily due-date nudge, running every 1 day at 8:00 AM.

Step two. Add the Dataverse action “List rows” and choose your Team Requests table. This action fetches rows for the steps that follow. Seasoned builders filter right here using a query language called OData, and one day you will too, because it is more efficient. But it is also a wall of syntax you do not need on day one, so we will filter the friendly way instead.

Step three. Add a Condition. Power Automate will offer to wrap it in an “Apply to each” loop the moment you use dynamic content from List rows; accept that, because it means “check every row.” In the condition, test two things: Due Date is less than or equal to the expression addDays(utcNow(), 1), and Status is not equal to Done. (That addDays expression is your first taste of flow expressions, which are cousins of the Power Fx formulas you met in Module 2. It simply means “now plus one day.”)

Step four. In the If yes branch, add Teams’ “Post message in a chat or channel” again, or the Outlook “Send an email” action if you prefer, and compose your nudge with dynamic content: Heads up: “[Name]” is due [Due Date] and is still [Status]. Save, then use the Test button and run it manually rather than waiting for tomorrow morning. If you seeded a request due soon, your nudge arrives.

Two flows, maybe forty minutes of work, and your little request tracker now behaves like a system some vendor would happily charge your company five figures a year for.

The Approval Pattern

I promised routing approvals without anyone forwarding an email, so let me hand you the pattern, because it is nearly identical to what you have already built. Power Automate includes a first-class Approvals connector, and its key action is “Start and wait for an approval.” Drop it into a flow, name an approver, and the flow genuinely pauses, for hours or days if necessary, while that person receives an approval card in Teams, Outlook, and the Power Automate mobile app. They tap Approve or Reject, optionally with comments, and the flow resumes with their answer as dynamic content, ready for a condition: if approved, update the request’s status and notify the requester; if rejected, notify them of that instead, with the comments attached.

Try it as an extension of Build One: instead of merely announcing a new request, route it for approval first. Every piece, the trigger, the condition, the Teams message, the Dataverse “Update a row” action, is something you have now touched. That is not an accident. Power Automate has a small vocabulary and enormous grammar; a dozen building blocks combine into almost anything.

When Flows Misbehave, and They Will

Here is a truth every builder learns: flows fail, and that is fine, because Power Automate keeps receipts. Open any flow and its run history shows every execution, when it ran, whether it succeeded, and, most usefully, exactly what data moved through every single step. Click a failed run and you can see the precise action that broke and the inputs it received when it did. I have watched this panel turn a mystifying failure into a thirty-second fix more times than I can count, usually revealing something humble, like a renamed channel or an empty due date. Make run history your first stop when something misfires, not your last. Debugging a flow is not detective work; it is reading.

Two related habits are worth adopting now. First, rename your steps. “Post message in a chat or channel 3” tells future-you nothing; “Notify requester of rejection” tells the whole story, and run history becomes self-documenting. Second, keep each flow to one job. A flow that notifies and nudges and escalates and archives is a flow nobody, including its author, will confidently modify a year from now. Small flows with honest names age gracefully.

The Licensing Footnote That Will Save You a Headache

One piece of straight talk before homework, tying back to the line I drew in Module 1 between standard and premium connectors. The flows you built today use the Dataverse connector, which is premium. Inside your free developer environment, that costs nothing, because the Developer Plan includes premium capabilities for learning. But the day you rebuild these flows at work for real, the people using them will need premium licensing, whether that is Power Automate Premium per user or your app’s Power Apps licensing carrying the rights. Knowing this before you demo something wonderful to your team spares you a deflating conversation with IT afterward. Nothing about today’s skills is wasted either way; the same patterns work with standard connectors like SharePoint, just with a different table under them.

Your Homework, and What Comes Next

In Module 2, your homework was to build an app around a small, real annoyance of your own. This module’s homework is its natural sequel: give that app one flow. Just one, and make it the one that saves the most nagging. A notification when something new arrives, a morning nudge before deadlines, an approval that currently lives in email, whichever would genuinely change next Tuesday. Building automation for a problem you personally feel is worth ten tutorials, because you will know immediately whether it actually helped.

Your system now has hands and a heartbeat: an app that collects work and flows that move it. What it lacks is sight. In Module 4 we bring in Power BI and turn the data quietly accumulating in your Team Requests table into something you can see: how many requests arrive each week, how long they take, where they pile up. That is when the tool you built stops just handling the work and starts telling you the truth about it. Bring your data. There should be a decent little pile of it by then.

Technology is changing the world. Read about it → The Augmented Life

Your Power Platform Trainer: J. H. Irwin
Author | Content Creator | Technology Strategist

At the end of Module 1, I asked you to bring your curiosity and that spreadsheet quietly holding your department together

I hope you brought both, because this is the module where we stop touring the workshop and start building in it. By the time you finish, you will have a free development environment of your own, a working understanding of how Power Apps thinks, and a real application running on your phone that you built yourself. Not a demo you watched. Yours.

If you missed Module 1, it maps the whole Power Platform in plain English, and it is worth ten minutes before you continue. The short version: Power Apps is Microsoft’s tool for building business applications without traditional code, and it sits on a shared foundation called Dataverse alongside its siblings for automation, analytics, websites, and AI agents. Today we go deep on this one tool, because everything else in this series builds on it.

First, Get Yourself a Workshop (It’s Free)

Before you can build anything, you need a place to build it, and Microsoft gives you one at no cost. The Power Apps Developer Plan provides your own personal environment with the full premium feature set: Dataverse, premium connectors, the works. It is meant for learning and building, not for running production apps for other people, which is exactly what we want right now. Nothing you break in your developer environment can hurt anyone.

Sign up at Microsoft’s Power Apps developer plan page (search “Power Apps Developer Plan” and it will be the first result). One honest caveat: you need a work or school Microsoft account to enroll. Personal accounts like outlook.com or gmail.com will not work. If you have a job with Microsoft 365, you almost certainly have a qualifying account already. If your employer has locked down self-service signups, or you do not have a work account at all, Microsoft offers a path to create a free developer tenant through the Microsoft 365 Developer Program, though availability of that program has tightened over the years. Most readers will be fine with the account they use at work.

Once you are enrolled, open make.powerapps.com in your browser. Check the environment picker in the top-right corner and make sure it says your name followed by “dev” or similar. That is your workshop. Everything in this series happens there, deliberately away from your organization’s shared spaces.

A Quick Tour Before We Touch Anything

The maker portal home page will greet you with a large text box inviting you to describe an app in plain language. That is Copilot, and yes, it can genuinely generate working applications from a sentence, including a newer capability called plans that can design entire multi-part solutions, tables and apps and automations together, from a description of your business problem. We will talk about when to lean on that shortly. For now, resist it. There is a reason flight schools still teach students to fly before handing them the autopilot.

Down the left side you will find the navigation that matters: Create (where new apps begin), Apps (everything you have built), Tables (your Dataverse data), and Solutions (containers for packaging work, which becomes important later in your journey but not today). Spend two minutes clicking around. Nothing here bites.

The Two Kinds of Apps, and How to Choose

Module 1 introduced canvas and model-driven apps from a distance. Up close, the difference is philosophical, and understanding it will save you from building the wrong kind of app, which is the most common early mistake I see.

A canvas app starts with a blank screen and gives you total control. You place every button, every label, every gallery exactly where you want it, the way you would arrange objects on a PowerPoint slide. The app’s behavior comes from formulas you attach to those objects. Canvas apps shine when the task is the star: a warehouse check-in screen, a field inspection form, a conference room booking tool. Anything where you can picture the ideal screen for one focused job, that is canvas territory.

A model-driven app flips the relationship. You do not design screens at all, at least not at first. You design data: tables, columns, relationships, business rules. Power Apps then generates a complete, consistent, professional interface around that data, with forms, views, dashboards, and search, all following the same design language as Dynamics 365. Model-driven apps shine when the data is the star: case management, asset tracking, anything with many related record types and people whose whole job is working those records. Recent updates have made these apps genuinely pleasant, with modern theming and Copilot built into the experience, so users can ask questions about their data in plain language.

Here is the rule of thumb I give everyone. If you find yourself sketching a screen, build canvas. If you find yourself sketching a spreadsheet with multiple related tabs, build model-driven. And if you are torn, start with your data in Dataverse either way, because a well-built table can feed both kinds of app later. Data outlives interfaces. It always has.

Power Fx: If You Can Excel, You Can App

The logic inside canvas apps is written in Power Fx, and if the word “programming” makes your shoulders tense, I have good news: you already know most of what you need. Power Fx was deliberately modeled on Excel formulas, right down to the philosophy. In Excel, when cell A1 changes, every formula referencing A1 updates instantly, without you telling it to. Power Fx works the same way. When your data changes, everything built on it recalculates. You describe what should be true, and the app keeps it true.

A few formulas will carry you a long way. Filter(Requests, Status = "New") returns only the new requests from a table called Requests. SortByColumns(Requests, "DueDate") puts them in date order. User().FullName returns the name of whoever is using the app right now, which is how one app can greet a thousand different people correctly. Navigate(DetailScreen) moves the user to another screen. And Patch() writes changes back to your data, the formula equivalent of hitting save. That handful, combined with If(), which works exactly like its Excel cousin, covers a remarkable share of real-world apps.

Now We Build: Your First Working App

Enough philosophy. We are going to build a simple team request tracker, the honest replacement for a thousand overworked spreadsheets. Follow along in your developer environment; the whole exercise takes twenty to thirty minutes.

Step one: create the table. In the maker portal, choose Tables, then create a new table named Team Request. Every Dataverse table comes with a primary text column, which will hold each request’s title. Add three more columns: Details (multiple lines of text), Status (a choice column with the options New, In Progress, and Done, with New as the default), and Due Date (a date column). Save it. You have just built a proper, secure, cloud database table, the thing that used to require a database administrator and a week of meetings.

Step two: add a few rows. Use the table’s editing grid to type in three or four sample requests, the way you would fill in a spreadsheet. Real-looking data makes the next step far more satisfying.

Step three: generate the app. From your table, choose the option to create an app. Power Apps will read your table’s structure and, in under a minute, hand you a complete working canvas app: a browse screen listing your requests, a detail screen for reading one, and an edit screen for changing or creating them. Press the play button in the upper right and use your app. Add a request. Edit one. This moment, watching software you made actually work, is the hook that catches most people permanently.

Step four: make it yours. Close the preview and look at the Studio around your app. The left panel is the tree view, listing every screen and every control on them. The center is your canvas. The right panel shows properties of whatever you have selected, and along the top runs the formula bar, Power Fx’s home. Try two changes. First, select the main gallery on the browse screen (it will have a name like RecordsGallery1), find its Items property in the formula bar, and wrap it so it reads something like SortByColumns(Filter('Team Requests', Status <> 'Status (Team Requests)'.Done), "DueDate"). Your list now hides finished work and sorts by urgency, which already beats most spreadsheets. Second, add a label to the top of the screen and set its Text property to "Welcome, " & User().FullName. Press play again and watch the app greet you by name.

Step five: publish and go mobile. Save and publish the app, then install the Power Apps mobile app on your phone, sign in with the same account, and open your creation. There is something quietly profound about holding it. Two hours ago this did not exist, and no programmer was involved, and yet here it is in your hand, storing data in a secure cloud database. Show someone. You have earned it.

About That Copilot Box

Now that you have built an app by hand, you have my blessing to use the shortcut, and I mean that sequence sincerely. Go back to the home page, describe an app in a sentence or two, and watch Copilot draft tables and screens for you. It is genuinely impressive, and for a first draft it can save real time. But you will notice something now that you would have missed before: you can read what it made. You can see where its table design is naive, where a screen needs rework, where a formula should change. AI is an extraordinary accelerant for people who understand the fundamentals and a frustrating black box for people who do not. The thirty minutes you just spent building manually is what converts you from the second group to the first, and that trade only gets more valuable as these tools grow more capable.

Three Habits to Start Now

I will close with the advice I wish someone had given me at this stage, because habits are cheap to form now and expensive to form later.

Name your controls. The Studio generates names like Label3 and Gallery1, and they seem harmless until your app has forty controls and a formula that references six of them. Rename things as you create them, using a short prefix for the type: galRequests, lblWelcome, btnSave. Six months from now, the person maintaining your app, quite possibly you, will be grateful.

Build in your developer environment, always. Your organization has a “default” environment that everyone shares, and it is the junk drawer of the Power Platform world. Real solutions deserve a deliberate home, and while you are learning, that home is the personal environment you created today.

Know that delegation is coming. Some Power Fx formulas can be executed by the server, which can search a million rows instantly, while others force your phone to download data and do the work itself, which quietly stops at a few hundred rows. This is called delegation, the Studio warns you about it with a blue underline, and it is the single most common reason a beginner’s app works perfectly in testing and misbehaves with real data. You do not need to master it today. You need only respect the blue underline when you see it, and know that we will tame it properly later in this series.

Your Homework, and What Comes Next

Before Module 3, build one more app, this time without me. Pick a small, real annoyance from your own work, something currently tracked in a spreadsheet, a notebook, or someone’s memory, and give it the treatment we used today: table, columns, generated app, two custom touches. Small and real beats ambitious and imaginary every time, because real problems teach you things sample data never will.

In Module 3, we hand your app a colleague that never sleeps. Power Automate can watch your Team Requests table and act the moment something changes: notify the right person in Teams when a request arrives, send a nudge when a due date approaches, route approvals without anyone forwarding an email. Your app collects the work. Next time, we make the work move.

Technology is changing the world. Read about it → The Augmented Life

Your Power Platform Trainer: J. H. Irwin
Author | Content Creator | Technology Strategist

Somewhere in almost every workplace, there is a spreadsheet doing a job it was never meant to do

It tracks vacation requests, or equipment checkouts, or customer complaints, and it has grown so many tabs and color codes that only one person truly understands it. When that person goes on vacation, the whole department holds its breath. If you have ever been that person, or worked beside them, you already understand why the Power Platform exists.

For most of computing history, there has been a wall between the people who understand the work and the people who can build software. On one side sit the folks who know exactly why the approval process takes eleven days. On the other side sit the developers who could fix it, if only they had the time, the budget, and a translator. The Microsoft Power Platform is an attempt to take that wall down. It gives ordinary people, the ones who actually live inside the problem, the tools to build their own solutions without writing traditional code.

This is the first module in a training series I am writing for people who want to genuinely understand these tools, not just nod along in meetings when someone mentions them. In this module, we will cover what the Power Platform is, why it is worth your attention, and what each component actually does, including how Microsoft licenses them and how they fit together with the rest of the Microsoft world you probably already use. Future modules will go deep on each component individually. Today, we are building the map.

What the Power Platform Actually Is

The Microsoft Power Platform is a family of low-code tools for building business applications, automating workflows, analyzing data, creating websites, and building AI agents. “Low-code” means you assemble solutions visually, by dragging, dropping, connecting, and configuring, rather than writing thousands of lines of programming. When you do need logic, you write short formulas that look remarkably like the ones you already use in Excel.

The platform consists of five main products: Power Apps for building applications, Power Automate for automating processes, Power BI for analyzing and visualizing data, Power Pages for building external-facing websites, and Copilot Studio for creating AI agents and chatbots. Underneath all five sits a shared foundation: Dataverse (a secure cloud database), a library of more than a thousand connectors that link to other software, and AI Builder, which lets you add artificial intelligence to whatever you create.

Here is the mental model I find most useful. Think of the Power Platform as a workshop. Power Apps builds the tools people hold in their hands. Power Automate is the assembly line running quietly in the background. Power BI is the window that lets you see what is actually happening. Power Pages is the storefront facing the street. Copilot Studio is the helpful assistant who greets people at the door. And Dataverse is the workbench they all share, where everything is stored, organized, and kept safe.

Why It Matters

I want to be honest with you rather than breathless, because this platform gets more than its share of marketing enthusiasm. Here is what is genuinely true about it.

It dramatically shortens the distance between a problem and a solution. An app that would have taken a development team three months and a five-figure budget can often be built by a motivated business user in a week or two. That is not hype. It is the everyday experience of people using these tools, and it changes what kinds of problems are worth solving. All those small, unglamorous inefficiencies that never justified a real software project suddenly become fixable.

It meets you where you already are. If your organization uses Microsoft 365, you are already standing inside the ecosystem. Power Platform tools connect natively to Outlook, Teams, SharePoint, Excel, OneDrive, and Dynamics 365. Apps can live inside Teams. Flows can respond to emails. Reports can pull from the spreadsheets you already maintain. You are not adopting a foreign system; you are extending one you already know.

It gives IT a way to say yes. For decades, the choice was between IT building everything (slow) or business users building shadow systems in Excel and Access (risky). The Power Platform includes genuine governance tools, centralized administration, data loss prevention policies, and environment controls, so IT departments can let people build while still protecting the organization. That balance is the quiet achievement here, and it is the reason large, careful companies have adopted it.

It is where Microsoft is putting its AI energy. Copilot features are woven throughout the platform now. You can describe the app you want in plain English and get a working starting point. That does not eliminate the need to understand these tools. It makes understanding them more valuable, because you become the person who can direct the AI well and recognize when its output needs correcting.

The honest caveat: licensing is complicated, and the line between “included with what you already pay for” and “requires an additional license” catches almost everyone off guard at least once. I will point out where that line sits as we go, because knowing where it is will save you real money and real frustration.

The Five Components, One by One

Power Apps: Building Applications Without Code

What it is. Power Apps lets you build custom business applications that run on the web, on phones, and inside Microsoft Teams. There are two main styles. Canvas apps start with a blank screen you design freely, like arranging a PowerPoint slide that happens to be a working application. Model-driven apps start with your data instead; you define the information and relationships, and Power Apps generates a consistent, professional interface around them. Canvas apps suit focused tools like an inspection checklist or an event check-in screen. Model-driven apps suit complex, data-heavy systems like case management.

When you need logic, you use Power Fx, a formula language deliberately designed to feel like Excel. If you can write IF(A1>100, "High", "Low") in a spreadsheet, you already have a head start.

Licensing. A free Developer Plan lets you learn and build in a personal environment, and I recommend everyone in this series sign up for one. Your Microsoft 365 license includes a limited version of Power Apps that works with standard connectors like SharePoint and Excel. For full capability, including Dataverse and premium connectors, the Power Apps Premium plan runs $20 per user per month, dropping to around $12 per user for organizations buying 2,000 or more licenses. There is also a pay-as-you-go option billed through Azure at roughly $10 per active user per app each month, which suits apps used occasionally or seasonally. One recent change worth knowing: as of January 2026, the old $5 Per App plan is no longer sold to new customers.

Integration. Power Apps connects deeply with SharePoint (a very common starting point for beginners), embeds directly into Teams, extends Dynamics 365, and reaches hundreds of other systems through connectors, from Salesforce to SQL Server.

Power Automate: Workflows That Run Themselves

What it is. Power Automate handles the repetitive digital work that quietly consumes people’s days. It runs flows: sequences of steps triggered by events. When an email with an attachment arrives, save the attachment to OneDrive and post a message in Teams. When someone submits a form, route it for approval and update a tracking list. You build these visually, choosing triggers and actions from menus.

It also includes desktop flows, which is robotic process automation, or RPA. This lets software mimic a human at a keyboard, clicking through older applications that have no modern way to connect. And Process Mining analyzes how work actually moves through your organization, revealing bottlenecks you may not have known existed.

Licensing. Microsoft 365 includes basic Power Automate rights for flows using standard connectors. Power Automate Premium, at $15 per user per month, unlocks premium connectors, attended desktop flows, and process mining for an individual. For unattended automation, where bots run without a person present, the Process plan is $150 per bot per month, or $215 for the Hosted Process plan where Microsoft supplies the virtual machine.

Integration. This is the connective tissue of the entire platform. Flows trigger from Power Apps buttons, refresh Power BI data, respond to Dataverse changes, send Teams approvals, and reach into nearly any system through those thousand-plus connectors.

Power BI: Turning Data Into Understanding

What it is. Power BI is Microsoft’s business intelligence tool. It connects to your data wherever it lives, in Excel files, databases, cloud services, or Dataverse, and turns it into interactive reports and dashboards. Instead of a static monthly chart, you get living visuals you can click into, filter, and question. It is the most mature product in the family, widely considered a leader in its category, and for many organizations it was the doorway into the rest of the platform.

Licensing. Power BI Desktop, the tool where reports are authored, is completely free, and you can learn an enormous amount without spending anything. Sharing is where licenses enter the picture. Power BI Pro, at $14 per user per month, lets people publish and view shared reports, and note that viewers need licenses too, not just authors. Pro is included in Microsoft 365 E5. Premium Per User, at $24 per month, adds larger data models, more frequent refreshes, and advanced features. (Both prices rose in April 2025, from $10 and $20 respectively.) At enterprise scale, organizations buy Microsoft Fabric capacity instead, which starts around $263 per month for the smallest tier and, at the F64 level and above, allows unlimited free report viewers.

Integration. Power BI is tightly woven into Excel, embeds reports in Teams and SharePoint and Power Apps, visualizes Dataverse data directly, and now lives inside Microsoft Fabric, Microsoft’s broader data platform.

Power Pages: Websites for the Outside World

What it is. Everything above serves people inside your organization. Power Pages is for everyone else. It builds secure, data-driven websites for external audiences: a portal where customers check order status, a site where residents apply for permits, a page where partners submit documents. The distinguishing feature is that these sites connect directly to Dataverse, so information submitted on the website flows straight into the same data your internal apps and reports use, with enterprise-grade security controlling who sees what.

Licensing. Power Pages is licensed per website based on monthly users, and it is the model most likely to change, so treat these as directional: roughly $200 per site per month for each block of 100 authenticated (logged-in) users, and about $75 per site per month for each block of 500 anonymous visitors, with pay-as-you-go options available. Always confirm current numbers on Microsoft’s pricing page before budgeting.

Integration. Power Pages runs on Dataverse, handles sign-ins through Microsoft Entra ID and other identity providers, and lets professional developers extend sites using Visual Studio Code when a project needs custom polish.

Copilot Studio: Building Your Own AI Agents

What it is. Copilot Studio, formerly Power Virtual Agents, is where you build AI agents: assistants that answer questions, take actions, and handle conversations on your behalf. You can point an agent at your documentation and let generative AI answer customer questions naturally, design guided conversations for specific processes, and connect agents to Power Automate so they can actually do things, like look up an order or create a support ticket. You can also extend Microsoft 365 Copilot itself, teaching the Copilot your organization already uses new skills specific to your business.

Licensing. Copilot Studio uses capacity-based licensing measured in Copilot Credits, which are consumed as agents respond and act. Organizations can buy a message pack, around $200 per month for 25,000 credits, or pay as they go at roughly a penny per credit. Simple answers consume little; complex generative responses and actions consume more.

Integration. Agents publish to Teams, websites, and other channels, draw knowledge from SharePoint and Dataverse and public sites, act through Power Automate flows, and plug into Microsoft 365 Copilot.

The Foundation Underneath

Three shared pieces make the five products feel like one platform, and understanding them will spare you confusion later.

Dataverse is the platform’s native database, though calling it a database undersells it. It stores your data in structured tables with built-in security, business rules, auditing, and relationships, and every Power Platform product speaks to it fluently. Premium licenses include a base amount of Dataverse capacity pooled across your organization, with additional storage available as a paid add-on. When people ask why they should use Dataverse instead of a SharePoint list, the answer is usually scale, security, and sophistication: SharePoint is a fine starting point, and Dataverse is where serious solutions live.

Connectors are the bridges to other software, and here is the single most important licensing concept on the entire platform: connectors come in two tiers. Standard connectors, covering most Microsoft 365 services like SharePoint, Outlook, and Teams, are included with Microsoft 365 licenses. Premium connectors, which include Dataverse, SQL Server, Salesforce, and most third-party systems, require a standalone Power Apps or Power Automate license. The moment a solution touches one premium connector, everyone using it needs premium licensing. More budget surprises trace back to this line than to anything else, so learn where it sits early.

AI Builder adds prebuilt and custom AI models, things like reading invoices, extracting text from images, and detecting sentiment, to your apps and flows, consuming credits as it works. One heads-up for planners: Microsoft has announced that the 5,000 monthly AI Builder credits currently bundled with premium licenses will be removed on November 1, 2026, so factor that into any solution that leans on these features.

A Quick Word About All Those Prices

Every figure in this module is Microsoft’s published list pricing in US dollars as of this writing, and if there is one constant in this ecosystem, it is that licensing evolves. Nonprofit, government, and academic pricing exists, enterprise agreements negotiate discounts, and Microsoft publishes an official Power Platform Licensing Guide that is updated regularly. The prices here are for orientation, so you understand the shape of the costs. Before any real purchasing decision, check the current guide. I will keep this series updated as the landscape shifts.

Where We Go From Here

If you take one idea away from this module, let it be this: the Power Platform is not really about apps or flows or dashboards. It is about who gets to build. For a very long time, the ability to create software belonged to a small group of specialists, and everyone else had to wait in line with their spreadsheets and their workarounds. These tools hand that ability to the people closest to the work, the ones who understand not just what the process is, but why it matters and whom it serves. That is a genuinely hopeful shift, and it is why I think this series is worth both my time and yours.

In Module 2, we will roll up our sleeves and go deep on Power Apps: setting up your free developer environment, understanding canvas and model-driven apps from the inside, and building your first working application. Bring your curiosity, and maybe that spreadsheet that has been quietly holding your department together. We might just retire it.

Technology is changing the world. Read about it → The Augmented Life

AI Used For This Module: Claude Opus 4.8 | Effort: High

Your AI Trainer: J. H. Irwin
Author | Content Creator | Technology Strategist

Training Objective

Ask anyone who has lived through a home remodel and you’ll get the same faraway look. It isn’t that the work is impossible. It’s that a remodel asks you to become, almost overnight, a project manager, a budget analyst, a materials expert, and a referee between people who don’t always agree with each other. Most of us were never trained for any of that, and the stress rarely comes from the construction itself. It comes from the sheer number of decisions piling up faster than we can think them through.

This is exactly the kind of problem AI handles beautifully, and it’s a good example of what I want you to take away from this workshop. You don’t need AI to be creative or clever here. You need it to be organized, patient, and thorough in a way that frees you to focus on the choices only you can make. A well-built prompt turns a vague, overwhelming project into a clear plan with phases, a budget, a realistic timeline, and a list of the questions you didn’t even know to ask.

Below is a prompt you can copy, fill in with your own details, and use with any capable AI assistant. After it, I’ve included a full example so you can see the kind of plan it produces before you run it yourself.

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Your Power Platform Trainer: J. H. Irwin
Author | Content Creator | Technology Strategist

This educational platform is designed to help non-technical users understand and confidently use Microsoft Power Platform in practical, meaningful ways

No coding background. No complicated jargon. Just clear, approachable guidance on how Power Platform tools can improve daily life, increase productivity, support creativity, and open new opportunities for income, learning, and personal growth.

Inside, you’ll find:

• New training material released weekly

• Step-by-step tutorials for today’s most useful Power Platform capabilities

• Video walkthroughs and hands-on demonstrations designed for everyday users

• Occasional podcast discussions exploring emerging trends, tools, and real-world impact

• Practical daily Power Platform use cases for work, writing, research, organization, business, and creativity

• Simple explanations of Power Platform technologies and what they mean for ordinary people

• Tips for saving time, improving workflow, and using Power Platform more effectively in real-world situations

• Honest discussions about the opportunities for using Power Platform

Whether you are a creator, entrepreneur, employee, retiree, student, or simply curious about the future, this platform is designed to help you navigate the rapidly changing world of Microsoft Technologies with confidence instead of confusion.

Power Platform is no longer just for tech experts. It is becoming part of everyday life. This educational platform helps ensure you are ready for it.

View Learn Microsoft Power Platform

Please Note:

Some content in “Learn Power Platform” is available to “Training Workshop” subscription plan subscribers only

Upgrade today to gain full access to all training modules

New tutorials and real life use case scenario are released weekly

Technology is changing the world. Read about it → The Augmented Life

By J. H. Irwin
Author | Content Creator | Technology Strategist

The most significant advancement wasn’t a new chip or another successful patient. It was eliminating one of brain surgery’s most delicate steps.

When most people hear news about Neuralink, the headlines tend to focus on the dramatic. Someone controls a computer with their thoughts. A patient plays chess using only their brain. Another milestone is reached in human trials.

Those accomplishments deserve attention, but they can also overshadow the quieter engineering advances that make them possible.

This week, Neuralink announced what may ultimately prove to be one of its most significant achievements yet. It wasn’t a new implant, a faster processor, or an artificial intelligence breakthrough. Instead, it was something that sounds almost mundane: finding a way to implant its brain-computer interface without first cutting through the brain’s protective outer membrane.

It is the kind of accomplishment that rarely becomes a headline, yet it has the potential to change how brain-computer interfaces are implanted for years to come.

The Brain’s First Line of Defense

The human brain is protected by three layers of tissue collectively known as the meninges. The outermost of these layers, called the dura mater, is remarkably tough. Its name comes from the Latin phrase meaning “tough mother,” an appropriate description for a membrane whose primary purpose is to shield one of the body’s most fragile organs.

Until now, implanting a Neuralink device required surgeons to perform a procedure known as a durectomy, carefully opening or removing a small section of this protective layer before the robot could insert the implant’s microscopic electrode threads into the brain.

While this has been performed safely in clinical trials, it remains one of the most technically demanding portions of the surgery. Every additional surgical step introduces complexity, consumes valuable operating time, and carries its own degree of risk.

Engineers often say that the best design is not one with more parts, but one with fewer. The same principle applies to surgery.

One Less Cut

Neuralink has now demonstrated a new implantation technique that allows its surgical robot to insert the flexible electrode threads directly through the intact dura without first opening it.

At first glance, that may not sound revolutionary. In reality, it represents years of engineering and one of the most sophisticated robotic surgical achievements the company has accomplished.

The electrode threads themselves are thinner than a human hair. The dura, by comparison, is many times thicker and considerably stronger. Successfully passing those delicate threads through an intact protective membrane without damaging either the electrodes or the underlying brain tissue required solving several extraordinarily difficult problems simultaneously.

The company redesigned its insertion needle to generate enough force to penetrate the membrane while still maintaining microscopic precision. Engineers also developed advanced optical systems capable of visualizing blood vessels hidden beneath the dura so the robot can avoid them during implantation. Additional imaging technologies continuously measure the changing distance between the protective membrane and the brain itself, allowing the robotic system to adjust in real time with extraordinary accuracy.

None of these advances are particularly glamorous on their own. Together, however, they represent the difference between a highly specialized experimental procedure and one that begins moving closer to routine clinical practice.

Engineering Over Headlines

There is a tendency to judge technological progress by dramatic public demonstrations. We celebrate the moment someone controls a robotic arm with their thoughts or speaks through a synthesized voice after losing the ability to communicate.

Those moments are important because they reveal what is possible.

But lasting progress usually comes from quieter breakthroughs that receive far less attention.

The invention of the modern airplane was not defined by a single successful flight. It was improved through thousands of refinements that made flying safer, more reliable, and eventually commonplace.

The same pattern is emerging with brain-computer interfaces.

Each refinement to the implantation process reduces complexity. Each improvement makes the technology more repeatable. Each reduction in surgical risk moves it one step closer to broader clinical adoption.

Sometimes the greatest innovation is simply removing an unnecessary step.

A Glimpse of the Future

Neuralink’s long-term ambitions extend well beyond allowing someone to move a computer cursor. Researchers are pursuing technologies that could restore speech to individuals who can no longer communicate, provide control of robotic limbs, and eventually explore methods of restoring functional vision by stimulating the brain directly.

Every one of those future capabilities depends upon safely placing thousands of tiny electrodes into the brain.

Making that process simpler is not merely an engineering convenience. It is foundational to everything that comes next.

If brain-computer interfaces are ever to become widely available for treating neurological disease, spinal cord injury, paralysis, or sensory loss, implantation must become safer, faster, and more consistent than it is today.

This latest accomplishment moves the industry meaningfully in that direction.

Beyond Biology

One of the recurring themes of Beyond Biology is that transformative technologies rarely arrive all at once. Instead, they emerge through countless incremental improvements that gradually reshape what is possible.

This latest Neuralink milestone illustrates that perfectly.

The public may remember the videos of people controlling computers with their thoughts. History, however, may remember something far quieter: the moment engineers figured out how to leave the brain’s natural armor intact.

It is not the kind of breakthrough that captures imaginations overnight.

It is the kind that changes medicine forever.

As brain-computer interfaces continue to mature, the biggest advances may no longer come from what the implant allows us to do. They may come from making the technology so safe, so precise, and so reliable that one day it becomes as routine as many other neurosurgical procedures are today.

That future is still years away, but this week’s achievement suggests we may have taken a much larger step toward it than the headlines alone would have us believe.

Technology is changing the world. Read about it → The Augmented Life

AI Used For This Module: Claude Opus 4.8 | Effort: High

Your AI Trainer: J. H. Irwin
Author | Content Creator | Technology Strategist

Training Objective

Learn how to use AI to create a complete international vacation itinerary including transportation, lodging, sightseeing, dining, budgeting, driving routes, local customs, and daily planning.

Instead of asking dozens of separate questions, you’ll learn how to write one comprehensive prompt that allows AI to perform the work of an experienced travel advisor.

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By J. H. Irwin
Author | Content Creator | Technology Strategist

Every generation experiences a handful of technological moments that fundamentally alter the trajectory of civilization

The steam engine transformed industry. Electricity reshaped daily life. The internet connected billions of people across the globe and changed how information moves through society. Artificial intelligence is now accelerating that transformation at a pace few predicted.

Yet another revolution may already be forming just beyond the horizon.

For years, quantum computing has occupied a strange place in the public imagination. It has been simultaneously groundbreaking and perpetually distant. Headlines have promised world-changing breakthroughs while practical applications always seemed five or ten years away. Most people understood that quantum computers were important, but few could clearly explain why.

That may be beginning to change.

Recent government investments, national initiatives, and strategic announcements suggest that world leaders increasingly believe quantum computing is approaching a point where it can no longer be treated as an experimental curiosity. Nations are beginning to view quantum technology not simply as a scientific endeavor, but as a matter of economic competitiveness, technological leadership, and national security.

At first glance, this may appear to be just another story about faster computers. It is far more significant than that.

Quantum computing has the potential to solve certain categories of problems that would take today’s most powerful supercomputers thousands, millions, or even billions of years to process. While traditional computers operate using bits that represent either a one or a zero, quantum computers use quantum bits, or qubits, which can exist in multiple states simultaneously. The result is not merely a faster version of today’s machines but an entirely different way of approaching computation itself.

The implications become extraordinary when quantum computing is viewed not as a standalone technology but as part of a larger technological convergence.

Artificial intelligence is rapidly becoming humanity’s most powerful tool for recognizing patterns, generating insights, and assisting decision-making. Robotics is increasingly capable of performing physical tasks once reserved for human labor. Human augmentation technologies are beginning to blur the line between biology and machine through neural interfaces, wearable intelligence, advanced prosthetics, and emerging biomedical innovations.

Each of these technologies is transformative on its own.

Together, they may create something far greater than the sum of their parts.

Imagine an AI system capable of modeling the interactions of millions of molecules simultaneously using quantum computing. Such a system could accelerate drug discovery, identify treatments for diseases previously considered incurable, and compress years of medical research into weeks or days.

Imagine climate models with unprecedented accuracy, capable of predicting environmental outcomes and guiding global responses with far greater precision than current systems allow.

Imagine advanced robotics powered by AI systems capable of processing vast amounts of information and learning from complex environments in ways that mirror or even exceed human adaptability.

Imagine neural interfaces that allow humans to interact with information directly through augmented cognition, assisted by AI and supported by computational capabilities that today seem almost unimaginable.

This is where the story becomes less about machines and more about people.

Throughout history, technology has expanded human capability. The wheel amplified movement. Printing amplified knowledge. Computers amplified calculation. The internet amplified communication.

The convergence of quantum computing, artificial intelligence, robotics, and human augmentation may amplify something even more profound: human understanding itself.

For the first time, we may be approaching tools capable of helping us explore questions that have remained beyond our reach for centuries. Questions involving consciousness, genetics, disease, energy production, materials science, environmental sustainability, and even the fundamental nature of reality could become accessible in ways previous generations could scarcely imagine.

Of course, every technological leap brings legitimate concerns. The same quantum systems that could accelerate scientific discovery could also threaten current encryption methods and cybersecurity frameworks. Advanced AI systems raise difficult questions about employment, ethics, misinformation, and human agency. Human augmentation technologies force society to confront questions of access, equity, privacy, and what it means to remain authentically human.

These challenges are real and should not be minimized.

History shows that technological progress is rarely defined solely by what we can build. It is ultimately defined by how wisely we choose to use what we build.

That is why this moment matters.

The recent developments surrounding quantum computing are not important because they suggest faster computers are coming. They matter because they indicate that multiple transformative technologies are beginning to mature simultaneously. The lines connecting quantum computing, artificial intelligence, robotics, biotechnology, and human augmentation are becoming increasingly visible.

When these fields begin reinforcing one another, the pace of innovation may accelerate beyond anything we have previously experienced.

For readers of The Augmented Life, this is perhaps the most important story of the week because it offers a glimpse beyond individual technologies and into a future shaped by their convergence.

The next era will not be defined by artificial intelligence alone. It will not be defined solely by quantum computing, robotics, or human augmentation.

It will be defined by what happens when all of them begin working together.

And if recent developments are any indication, that future may be arriving sooner than many of us expected.

Technology is changing the world. Read about it → The Augmented Life

Your AI Trainer: J. H. Irwin
Author | Content Creator | Technology Strategist

In the previous installment of Learn to Prompt™, we explored one of the most overlooked capabilities in modern artificial intelligence: personalization.

Most people use AI as a tool.

The most effective users train AI as a collaborator.

The difference between those two approaches can be dramatic.

When AI knows nothing about you, every conversation starts from zero. You spend time explaining your goals, correcting tone, fixing formatting, and rewriting content until it feels right.

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Your AI Trainer: J. H. Irwin
Author | Content Creator | Technology Strategist

Artificial intelligence is often described as a tool, assistant, or productivity enhancer. While all of those descriptions are accurate, they miss one of the most important developments in modern AI: personalization.

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Your AI Trainer: J. H. Irwin
Author | Content Creator | Technology Strategist

One of the most practical ways to use artificial intelligence is by allowing it to analyze information you already have

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By J. H. Irwin
Author | Content Creator | Technology Strategist

When Apple announced the latest Vision Pro updates at WWDC, most of the headlines focused on artificial intelligence, visual intelligence, and a long list of new features coming to vision OS later this year

Those improvements are certainly important and will make the platform more capable than ever before, but they are not what captured my attention. After spending time with the current beta release, I found myself drawn to a feature that received far less attention but may ultimately have the greatest impact on how many people experience the device.

Apple has introduced the ability to transform your own panoramic photographs into immersive environments. Instead of viewing a panorama as a flat image stretched across a screen, Vision Pro can place you inside that moment, surrounding you with the landscape you captured. As both a lifelong technology enthusiast and an avid photographer, I immediately began experimenting with panoramic images from some of my favorite travels. Among them were photographs I had taken in Ireland during what remains one of the most memorable vacations of my life.

What happened next surprised me.

Within minutes, I was standing once again at the Cliffs of Moher. I revisited Doolin, looked out across familiar landscapes, and found myself surrounded by places that until now existed only in photographs and memory. While I was physically sitting in my office wearing a headset, the experience created a sense of presence that traditional photographs simply cannot replicate. The cliffs, coastline, and countryside felt remarkably familiar, almost as if I had stepped back into a chapter of my own life that had long since passed.

The emotional impact caught me completely off guard. As I explored those environments, I found myself becoming overwhelmed by memories of the trip, the people I shared it with, and the experiences that made it so meaningful. Like many travelers, I have often looked back through photographs hoping to recapture a small piece of what I felt when I was there. Photographs preserve images, but they rarely preserve atmosphere. Vision Pro’s new environment capability changes that equation by creating an experience that feels far closer to being present than simply remembering.

What struck me most was the realization that I could revisit those moments whenever I wanted. There were no airline tickets to purchase, no hotel reservations to make, and no long travel days standing between me and a place I loved. Instead, I could spend a few minutes reconnecting with a meaningful memory and experience a small part of what made it special in the first place. That may sound like a simple feature on paper, but in practice it feels transformative.

Apple has also added an entirely new immersive environment that demonstrates just how far spatial computing has evolved. One of my favorites places the user beside a river in Thorsmork Iceland, surrounded by flowing water, natural ambient sounds, dramatic landscapes, and the Aurora Borealis shimmering overhead. The environment is rendered in full 360 degrees, creating a convincing sense of being transported somewhere far removed from the room you are physically sitting in. I have found myself working there frequently, answering emails, writing articles, and researching topics while surrounded by one of the most beautiful settings imaginable.

Experiences like these highlight something many people still misunderstand about Vision Pro. It is easy to focus on the technical specifications, the displays, the processors, or the software features. Those elements matter, but they are not what people remember after using the device. What remains with you are the experiences themselves. The ability to revisit a treasured memory, escape a stressful afternoon, or place yourself in a calming environment while working can have a surprisingly powerful effect on your mood, focus, and overall sense of well-being.

The additional features arriving later this year will make those experiences even better. Apple Intelligence will bring a more capable and context-aware Siri. Visual Intelligence will help the system understand what you are looking at and provide relevant information naturally. Enhanced eye-tracking interactions, improved window management, and numerous quality-of-life improvements will make the platform feel more intuitive and responsive. While these features may generate headlines, their true value lies in how seamlessly they allow users to interact with the technology without constantly thinking about the technology itself.

The current release remains in beta, with a public rollout expected later this year, but the direction is already becoming clear. Apple is steadily transforming Vision Pro from an impressive piece of hardware into something far more meaningful. The future of spatial computing may not be defined by bigger screens, faster processors, or more advanced artificial intelligence. It may be defined by technology’s ability to help us reconnect with the places, experiences, and memories that have shaped our lives. After returning to Ireland through my own photographs, I am more convinced of that than ever.

Technology is changing the world. Read about it → The Augmented Life

Your AI Trainer: J. H. Irwin
Author | Content Creator | Technology Strategist

Create a professional business infographic for a fictitious IT consulting company named “Summit IT Advisors.”

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Your AI Trainer: J. H. Irwin
Author | Content Creator | Technology Strategist

For more than thirty years, I have built my career around technology

I have been a software developer, software engineer, data analyst, reporting specialist, architect, and technology leader. During that time, I have witnessed wave after wave of innovation arrive with predictions that entire professions would disappear. Personal computers were supposed to eliminate jobs. The internet was supposed to eliminate jobs. Cloud computing was supposed to eliminate jobs. Automation was supposed to eliminate jobs. Each technological revolution changed the nature of work, but none of them eliminated the need for capable people who were willing to learn, adapt, and evolve.

Today, artificial intelligence has become the latest source of anxiety for millions of workers, and unlike many previous technological advances, the concerns are understandable. AI can already write code, generate reports, analyze data, summarize documents, create presentations, answer questions, and automate tasks that once required significant human effort. It is easy to look at these capabilities and wonder whether the careers many of us spent decades building are slowly being replaced by machines.

I understand that concern because I work in one of the very professions frequently listed as being at risk. Every week there seems to be another article declaring that software engineers, analysts, developers, writers, accountants, and countless other professionals are about to become obsolete. The headlines are designed to generate clicks, but they often overlook an important reality. While artificial intelligence is certainly changing how work gets done, it is also creating entirely new opportunities for those willing to embrace it.

The mistake many people make is viewing AI as a replacement for human expertise. In reality, AI is proving to be far more effective as an amplifier of expertise. The technology can generate solutions, but it still requires someone who understands the problem. It can produce code, but it does not truly understand the business requirements behind that code. It can create reports, but it does not know which questions matter most to decision-makers. It can analyze data, but it cannot determine whether the conclusions it reaches make sense within the broader context of an organization, industry, or society.

That distinction matters because it reveals where the future opportunities exist.

For decades, technical professionals were valued largely for their ability to create. We wrote the code. We built the reports. We designed the databases. We constructed the workflows. Those skills remain important, but increasingly our value may come from our ability to guide intelligent systems toward the right outcomes rather than manually performing every step ourselves. In many ways, the profession is shifting from builder to conductor. The orchestra has become far more capable, but it still requires someone who understands the music.

One of the most important skills professionals can begin developing today is advanced prompting. Many people hear the phrase “prompt engineering” and immediately assume it is a highly technical discipline reserved for AI researchers. In reality, advanced prompting is simply the art of communicating clearly with artificial intelligence. It involves understanding how to define objectives, provide context, establish constraints, identify desired outcomes, and iteratively refine results until they meet expectations.

The individuals who become exceptionally skilled at guiding AI systems are likely to be among the most valuable professionals in the next decade. Organizations will need people who understand not only how AI works, but how to direct it toward solving real business problems. A well-crafted prompt can often mean the difference between a mediocre result and an exceptional one. Just as previous generations learned programming languages to communicate with computers, today’s professionals are learning how to communicate effectively with artificial intelligence.

Beyond prompting, there are several other skills that will become increasingly valuable. Critical thinking will remain essential because AI-generated content is not always correct. Someone must validate assumptions, identify errors, recognize gaps, and ensure that outputs align with reality. Business knowledge will become even more important because AI can assist with execution, but understanding organizational objectives, customer needs, and industry dynamics remains fundamentally human. Communication skills will also grow in importance because translating complex business challenges into clear instructions for both people and AI systems requires clarity, precision, and insight.

Another area of opportunity lies in AI governance, ethics, and oversight. As organizations deploy artificial intelligence at scale, they will need professionals who understand responsible use, privacy concerns, compliance requirements, security implications, and risk management. These are not areas where experience becomes less valuable. If anything, they become more important as technology becomes more powerful.

Perhaps the most encouraging aspect of this transition is that experienced professionals may be uniquely positioned to succeed. One of the great misconceptions surrounding AI is that decades of experience suddenly become irrelevant. My own observations suggest the opposite. Artificial intelligence is remarkably effective at generating possibilities, but experienced professionals possess something that cannot easily be replicated by an algorithm. They have judgment.

Judgment is what allows an experienced software engineer to recognize a design flaw before it becomes a production issue. It is what enables a seasoned analyst to identify when data appears technically correct but logically impossible. It is what allows an experienced leader to understand the human consequences of a business decision. Judgment is developed through years of successes, failures, lessons learned, and hard-earned wisdom. AI can assist with many tasks, but it does not possess lived experience.

As I look toward the future, I do not see a world where artificial intelligence eliminates the need for human talent. I see a world where human talent evolves. The professionals who thrive will not be those who refuse to learn AI, nor will they be those who blindly trust everything it produces. The greatest opportunities will belong to those who learn how to partner with these new tools while continuing to apply their uniquely human strengths.

For anyone worried about their career, my advice is simple. Do not spend your energy competing against artificial intelligence. Spend your energy learning how to work alongside it. Explore AI tools. Learn advanced prompting techniques. Understand how these systems think, where they excel, and where they fail. Develop your critical thinking, communication, and leadership abilities. Most importantly, continue learning.

Every major technological shift creates disruption, uncertainty, and fear. It also creates opportunity. The people who recognize that opportunity early are often the ones who shape the future rather than becoming victims of it.

Artificial intelligence is changing our professions. There is little doubt about that. What remains to be seen is how each of us chooses to respond. For those willing to adapt, learn, and grow, the future may hold far more opportunity than many of today’s headlines would have us believe.

Technology is changing the world. Read about it → The Augmented Life