Why GitHub Copilot Doesn’t Belong Inside Microsoft 365 Copilot

The other day I was asked a question that sounds sensible on the surface.

“If GitHub Copilot is so good, why not just build it directly into Microsoft 365 Copilot for everyone?”

At first glance it feels like the logical next step. One Copilot. One interface. One AI assistant for everything.

The more I think about it though, the more I believe that would be a mistake.

The reason comes down to something that AI vendors often overlook. Different people work in very different ways.

A software developer spends their day creating, testing and refining code. A finance manager lives in spreadsheets. A salesperson works across emails, meetings and CRM records. An executive spends much of their time making decisions based on information coming from multiple sources.

Those aren’t variations of the same job. They’re fundamentally different disciplines.

The Context Is More Important Than The AI

What makes GitHub Copilot valuable isn’t simply that it can generate code.

It’s that it understands the environment a developer works within.

It sits inside development tools. It understands repositories. It helps navigate large codebases. It assists with testing, debugging and software creation workflows. The value comes from the context surrounding the AI.

Microsoft 365 Copilot has a completely different context.

When I ask Copilot in Outlook to draft a response, or use Copilot in Teams to summarise a meeting, the AI is working with conversations, documents, calendars and organisational knowledge. It is focused on helping people communicate, collaborate and make decisions.

Trying to merge these two worlds into a single experience risks making both less useful.

A productivity worker doesn’t need a sophisticated coding assistant appearing in every interaction. In the same way, a developer probably doesn’t want meeting summaries and document drafting cluttering up their coding environment.

Specialisation Usually Wins

We’ve seen this pattern before.

Nobody expects Excel to become Visual Studio.

Nobody asks Word to become a network troubleshooting platform.

Microsoft succeeds because its tools are specialised while still working together.

I think AI will follow the same path.

GitHub Copilot should continue evolving as the specialist assistant for software creation. Microsoft 365 Copilot should remain focused on helping knowledge workers get through meetings, emails, documents and decision-making processes faster.

The mistake many organisations make is assuming every AI capability needs to be available to every employee.

In reality, most people only need the capabilities that relate directly to their role.

Adding more functionality doesn’t automatically create more value. Sometimes it just creates more complexity.

The Real Opportunity Is Connection

Where I do see value is in integration.

Imagine a project manager using Microsoft 365 Copilot to prepare for a software review meeting. The assistant could pull summaries of development activity from GitHub.

A developer could use GitHub Copilot to understand changes in a repository while still accessing relevant business context from Microsoft 365.

That’s very different from forcing both experiences into a single product.

The future isn’t one giant AI assistant trying to do everything.

It’s a collection of specialised agents and copilots that share information when necessary while remaining focused on their primary role.

We’re already starting to see this approach emerge across Microsoft’s ecosystem.

Keep The Tool Sharp

One lesson I’ve learned over many years working with Microsoft technologies is that the best tools are usually the ones with a clear purpose.

A hammer becomes less useful once you start turning it into a screwdriver, a saw and a wrench at the same time.

The same principle applies to AI.

GitHub Copilot should remain the coding expert. Microsoft 365 Copilot should remain the productivity expert.

The goal shouldn’t be to squeeze every AI capability into a single interface. The goal should be to put the right assistant in front of the right person at the right time.

That’s where the real productivity gains will come from.

Your Best Marketing Asset May Already Be Sitting in Teams

Most businesses I speak with think content creation starts with a blank page. That is usually the first mistake.

The better starting point is buried in work already being done. A client workshop. A recorded training session. A checklist built to explain something tricky. A Teams meeting where someone finally understood the issue and asked the question every other client is probably thinking as well.

That material may not have been created for marketing. Good. That is often why it works.

Real content comes from real work

I have never been a big fan of content that sounds manufactured. You can usually spot it quickly. It has the right keywords, the right structure, and no pulse.

The content that lands tends to come from delivery. It comes from explaining MFA to a business owner who wants fewer account compromises. It comes from walking a client through why SharePoint permissions matter before Copilot is enabled. It comes from showing someone how to use Outlook and Teams differently so their day is not ruled by the inbox.

Those moments have weight because they are connected to a real problem. If one client needed that explanation, another business owner probably needs it too.

That is where many MSPs and consultants miss the opportunity. They treat training as something that happens once, inside the client relationship, then disappears. I would rather see it as operational proof. It shows how you think, what you believe matters, and how you help people move from confusion to action.

Capture the explanation, not the performance

This does not mean every client session should become a public article. Confidentiality matters. Context matters. Permission matters.

But the lesson can often be separated from the client. The pattern can be reused without exposing the details.

After running a Copilot readiness session, I might open Word and ask Copilot to help turn rough notes into a plain-English outline. Not a finished post. Not something I publish without thinking. Just a starting structure based on what I actually explained.

I might then drop the key points into a private Teams channel, add the questions that came up, and use that as a source of future newsletter topics, blog ideas, short videos, or client conversation starters. SharePoint becomes the library. Teams becomes the capture point. Copilot becomes the drafting assistant. My job is still to apply judgement.

That workflow matters because it keeps content close to reality. You are not guessing what the market wants. You are listening to what clients already needed help understanding.

Proof beats polish

The market is full of polished noise. Everyone can publish more now. AI makes that easier. That also means the value of generic content keeps falling.

What still stands out is evidence of experience.

A session that helped a client understand sensitivity labels is more useful than a vague post about data protection. A walkthrough that helped a leadership team decide how to govern Teams is more useful than another article saying governance is important. A practical explanation of what Copilot can and cannot see in Microsoft 365 is more useful than a broad claim about AI productivity.

The trick is not to turn every client interaction into a campaign. The trick is to notice the teaching moments already happening in the business and preserve them before they vanish.

That may be a few notes after a meeting. It may be a transcript summary. It may be a reusable diagram. It may be a short internal explanation that later becomes external education.

If your clients keep asking similar questions, that is not an interruption. That is your editorial calendar tapping you on the shoulder.

The best content is not always created in a marketing session. Sometimes it is created while you are helping someone understand their business better. Capture that, shape it carefully, and you will sound far more useful than the people still staring at a blank page.

Faster Leads Need Better Proof, Not More Noise

I see many businesses treat new leads like they are already convinced. Someone fills in a form, downloads a guide, books a call, or replies to a post, and the business immediately pushes for the next step.

That is often too early.

Most prospects do not arrive ready to buy. They arrive curious, sceptical, and carrying only a rough idea of the problem. If your follow-up assumes they are already sold, you force the sales conversation to do all the heavy lifting.

The better question is: what must this person see and trust before the sales conversation becomes easy?

Your best marketing is probably already sitting somewhere

In most businesses I work with, the useful material already exists. It is just scattered.

It might be in a proposal that explained the value clearly. It might be in an old webinar where someone answered the awkward question honestly. It might be in a customer onboarding email, a Teams meeting recap, a SharePoint document, or a PowerPoint deck that has been used quietly for years because it works.

The problem is not always content creation. Often, it is content discovery.

This is where Microsoft 365 Copilot becomes very practical. Instead of starting with a blank page and asking for more marketing content, I would start by asking Copilot to help identify patterns across Outlook, Teams, SharePoint, and OneDrive. What questions appear before prospects say yes? Which objections show up in email threads? Which documents get reused because they make the penny drop?

That is not a campaign yet. That is raw intelligence.

Sequence beats storage

Most businesses store useful content. Far fewer guide prospects through it in order.

A new lead does not need every case study, webinar, brochure, and feature sheet at once. That just creates a homework assignment. What they need is a path.

I would be looking for the small set of assets that change how the prospect sees the problem. The explainer that makes the risk obvious. The story that makes the outcome feel achievable. The short video that answers the awkward question. The document that shows the cost of waiting.

Then I would sequence those assets deliberately.

Not as spam. Not as a flood of automated noise. As a guided conversation that helps the prospect become ready faster.

A simple example: a lead comes in after reading a blog about Copilot readiness. Rather than sending them straight to a booking page, I might first send a short note from Outlook with a link to a SharePoint-hosted checklist. A few days later, I might follow with a Teams webinar recording that explains oversharing risk in plain language. Once the prospect has enough context, the consultation feels less like a pitch and more like the next sensible step.

Faster conversion comes from clearer thinking

I am not saying marketing automation fixes everything. It does not.

If the offer is weak, automation helps you annoy people at scale. If the message is vague, more content only increases the confusion. If the business has not done the work to understand buyer doubt, Copilot will not magically invent that understanding for you.

But used properly, Copilot can help you mine what your business already knows. It can surface recurring themes from meetings, summarise prospect questions from email, help reshape a useful document into a sharper follow-up, and keep the process grounded in real conversations rather than marketing theory.

That is the shift I care about.

Conversion is not just about more leads. It is about helping the right people reach belief sooner. The businesses that get better at that will not necessarily publish more. They will guide better.

That is where I would start.

CIAOPS Image comparison page

Every time a new image model from Microsoft becomes available I use the same test prompt to see what the result is and compare that to previous attempts. The last one of these was here:

https://blog.ciaops.com/2026/08/15/new-microsoft-image-model-2/

With new models coming out all the time, the latest is MAI-Image-2.6-Flash available today, I figured a better option going forward is to put them all on a single web page for comparison which I have now done here:

https://directorcia.github.io/Office365/image-comparison.html

You can view all the model results side by side as well compare the selection you want using the selector in the top left.

I’ll keep adding new results using my standard image test prompt and posting the results here to have a reference going forward.

Let me know if you have any other image models I should test and post.

The Inbox Tells the Truth

I have seen this happen more than once. A business owner turns up every day, answers the same messages, attends the same meetings, and wonders why the energy has disappeared. Nothing is technically broken. Clients remain. Invoices still go out. But the work has become something to survive rather than something to shape.

That is usually when people look for a new tool, market, or strategy. Sometimes that is needed. But I reckon there is a smaller test that tells the truth faster.

Look at the last thing you sent.

Not the polished proposal. I mean the ordinary email you sent to a client, supplier, or your own team. If it landed in your inbox from someone else, would you read it properly? Would it make the next step clearer?

If the honest answer is no, that is not just a writing problem. It is a leadership signal.

Your inbox reflects your business

Email is easy to dismiss because it feels routine. That is why it matters. The routine is where culture leaks out.

A vague email usually points to vague thinking. A rushed reply often means no one has stopped to decide what actually matters. A long message that says little normally means the sender is hoping volume will do the work that clarity should have done.

I am not judging that from a distance. I have written plenty of those messages myself. The kind where the subject line is weak, the point arrives too late, and the recipient has to work out what I want.

When that becomes normal, I give away control.

Copilot should challenge the thinking

This is where Microsoft 365 Copilot becomes interesting, but not for the reason many people expect.

The lazy version is to ask Copilot in Outlook to write the email and then send whatever appears. That may save time, but it does not fix the real problem. It can make it worse, because unclear thinking is now wrapped in cleaner sentences.

The better use is to make Copilot test your intent.

Before sending an important reply, ask: what is the decision in this message? What action am I asking for? What could the reader misunderstand? Can this be shorter without becoming blunt?

That is a different relationship with the tool. Copilot is not the ghost-writer. It is the mirror. It helps me see where I have avoided making the point.

The same applies in Teams. If a channel conversation needs ten messages to agree on one next step, the issue is probably not Teams. It is the absence of a clear owner, decision, or sentence.

Small standards rebuild confidence

When a business feels flat, the temptation is to chase a big reset.

Momentum often returns through smaller acts of discipline.

Write the subject line like it matters. Put the decision near the top. Tell people what happens next. Use Copilot to tighten your thinking, not decorate your uncertainty. Move the discussion into Teams when the email thread has become a swamp, then summarise the decision so the next person does not have to excavate it.

That may sound basic. It is. That is the point.

Businesses rarely lose their edge all at once. They drift. Standards slip in small places first. The inbox gets dull. Meetings become foggy. Documents become harder to read. Everyone keeps moving, but fewer people know why.

The way back starts in one ordinary place.

Open your sent items. Read your own work as if you were the client. If it would not earn your attention, fix the standard there.

That is where authority starts to return: with one clearer message, one cleaner decision, and one less piece of work that asks the reader to do your thinking for you.

The Algorithm Is Choosing for You

A few weeks ago, I caught myself doing something I suspect many people do every day. I opened LinkedIn looking for one thing and, twenty minutes later, realised I’d spent my time reading something completely different.

It wasn’t an accident.

The platform had quietly decided what it thought I should see. The posts, the comments, the videos, the suggested connections. All selected and arranged by an algorithm making thousands of decisions on my behalf.

And it’s not just social media anymore.

The same thing is now happening with AI.

The New Digital Gatekeepers

For years, we worried about search engines deciding which websites appeared on the first page of results. Today, that influence runs much deeper.

Your social media feed determines which opinions receive your attention. News aggregators decide which stories deserve prominence. Video platforms choose what appears next. Every click, pause and interaction becomes data that fine-tunes the content delivered back to you.

Most people believe they’re making independent choices about what they consume.

In reality, they’re often choosing from a menu that someone else prepared.

The concerning part isn’t that algorithms exist. We need them. The volume of information available today makes manual filtering impossible.

The concern is that most people rarely stop to consider who is tuning the filter.

AI Is Taking This Further

The shift becomes even more interesting when we look at AI chatbots.

When you ask a question in ChatGPT, Copilot, Gemini or another AI tool, you’re not receiving the entire internet. You’re receiving a curated response generated from a combination of training data, system instructions, ranking mechanisms and safety controls.

Again, none of this is inherently bad. In fact, it’s often incredibly useful.

But it does mean that the answer you see is the result of countless decisions made before you ever typed your prompt.

I’ve noticed this in my own work with Microsoft 365 Copilot.

Ask Copilot to summarise a long Teams meeting and it determines what information is important enough to include. Ask it to analyse an email thread in Outlook and it decides which points deserve emphasis. Ask it to draft a document in Word and it makes choices about structure, tone and content.

The productivity benefits are enormous.

However, it also means we’re increasingly consuming information that has already been filtered, prioritised and interpreted on our behalf.

The Real Skill Is Learning to Challenge the Output

I don’t think the answer is to reject algorithms or AI.

That ship has sailed.

The answer is developing the habit of questioning what you’re shown.

When I read something that strongly reinforces my existing view, I ask myself whether I’m being shown an opposing perspective. When Copilot gives me an answer, I often ask a follow-up question from a different angle. When an AI summary highlights a particular issue, I sometimes go back to the original source material.

The organisations that get the most value from AI will be the ones that understand this distinction.

Using AI well isn’t simply about writing better prompts.

It’s about recognising that every response is a starting point, not a final truth.

Don’t Outsource Your Thinking

One of the biggest risks I see isn’t that AI becomes smarter.

It’s that people become less curious.

Algorithms are incredibly good at feeding us information that feels familiar. AI is incredibly good at giving us answers that sound complete. Together, they can create the illusion that we’re seeing the whole picture when we’re really seeing a carefully filtered version of it.

The irony is that tools like Microsoft 365 Copilot can actually help us become better thinkers when used correctly. Ask it to challenge your assumptions. Ask it to find alternative viewpoints in a SharePoint document library. Ask it to identify gaps in a proposal you’re drafting in Word.

Use the technology to expand your perspective rather than narrow it.

Because whether it’s your social media feed or your favourite AI assistant, someone or something is helping determine what you see.

The important question is whether you’re still deciding what to think.

The Work Is Good. The Offer Is Invisible.

I see this pattern a lot with coaches, consultants, trainers, and specialist advisers.

They know their craft. They care about the people they serve. They have a method that actually helps. Yet the market barely notices them.

Not because they are bad at the work.

Because the work has been presented in a way that makes the buyer do too much effort.

That is the uncomfortable bit. You can be excellent and still be unclear. You can have years of experience and still make people guess what problem you solve. You can have a strong programme and still describe it like a collection of calls, worksheets, and vague outcomes.

Clients do not buy your internal process. They buy the change they can recognise.

The offer has to do more work

A weak offer is not always cheap, thin, or poorly intentioned. Often it is simply under-shaped.

It says too much about what is included and not enough about what changes. It talks about sessions, modules, access, frameworks, and support. Those things matter, but they are not usually what makes someone lean forward.

The buyer is asking a much simpler question: “Will this help me fix the problem that is costing me money, energy, time, or confidence?”

If the answer is hidden inside a long page of inclusions, the offer is making the prospect assemble the value for themselves. Most people will not do that. They are busy. They are distracted. They are comparing you against every other message in their inbox, feed, and calendar.

That is where I think many good operators get caught. They assume quality will eventually be discovered. Sometimes it is. But usually only after too much time has been wasted.

Copilot can help, but only if the thinking is clear

This is where Microsoft 365 Copilot can be useful, but not as a magic marketing machine.

The better use is as a thinking partner inside the work you already do. I would start with a rough offer document in Word and ask Copilot to identify the actual promise, the likely buyer objections, and the parts that sound like internal delivery rather than client value.

Then I would take notes from recent sales calls, anonymised client feedback, and proposal language, and work through them in a dedicated Teams channel. Not to produce shiny slogans, but to find the repeated pain points that buyers already understand.

That is the point. Copilot should not invent your positioning. It should help you see what is already sitting in your material but buried under vague language and service-provider habits.

A good coach should not need to become a full-time marketer. But they do need to make the value easier to recognise.

Packaging is not decoration

I think people often misunderstand packaging. They hear the word and think polish, branding, graphics, colours, and headlines.

Packaging is the shape of the decision. It explains who the offer is for, what problem it addresses, what changes, how the buyer will experience the work, and why now is the sensible time to act.

That does not mean making wild promises. In fact, the best offers are usually more honest, not less. They remove fog. They reduce friction. They make the next step feel practical.

If you are good at what you do but the market is quiet, the answer may not be to post more, discount harder, or build another lead magnet. It may be to take the work you already believe in and make it easier for the right people to understand.

Being good is not enough if the value is hidden.

The job is to make the useful thing visible.

We have a new LLM in Copilot winner

A while back I compared all the different LLM’s (i.e. GPT, Claude) in various Copilot services (i.e. Chat, Cowork) here:

https://blog.ciaops.com/2026/08/17/comparing-llms-in-copilot-services-round-7-final/

The ultimate winner was:

Opus 5 (Cowork)

which cost US$22 to complete the work.

Microsoft has just announced that Fable 5.1 is available in Cowork so I took it for a spin through the same prompt I used in the recent testing. The results are here (as judged by Grok):

https://github.com/directorcia/general/blob/master/Copilot/Comparisons/20260902-Cowork-Fable51-Grok-eval.md

and the new winner is now:

Fable 5.1 (Cowork)

you can see the result for yourself here:

https://github.com/directorcia/general/blob/master/Copilot/Comparisons/20260816/20260902-Cowork-Fable-51.docx

along with all the others outputs:

https://github.com/directorcia/general/tree/master/Copilot/Comparisons/20260816

Here is an update on the costs in Cowork for each model:

Fable 5.1 = 3,453 credits

Fable 5 (Preview) = 3,387 credits [Model no longer shown]
Fable 5 (Copilot)(Preview) = 3,373.8 credits [Model no longer shown]

GPT 5.6 Sol = 2,800.50 credits
Sonnet 5 = 2,509.3 credits
Opus 4.8 = 2,487 credits [Model no longer shown]
Opus 5 = 2,240 credits

GPT 5.5 = 1,200 credits
GPT 5.6 Terra = 260 credits

In summary then, the new best model, Fable 5.1, produces the best results from my standard prompt and is also the most expensive to use using that prompt.

The comparison report for all document paramteres has been updated here:

https://github.com/directorcia/general/blob/master/Copilot/Comparisons/20260816-File-paramters.md

The next updated model that we expect to see will probably be GPT 6.0 which is expected in the October timeframe if not sooner. As soon as it becomes available I’ll test it and update this information.