Ask most developers about AI tools and Copilot Chat will come up within the first minute. It’s not just a chat window anymore—it’s embedded in code editors, office suites, and even operating systems. But what exactly is Copilot Chat? And why is everyone talking about it? This post breaks down the current state of Copilot Chat, the recent pricing changes, and how different teams are using it.
What is Copilot Chat?
Copilot Chat is the conversational layer built on top of the original Copilot code completion tool. Instead of just suggesting the next line, it lets you ask questions, get explanations, and give natural language commands. Today, the name covers two main products: GitHub Copilot Chat for developers and Microsoft 365 Copilot Chat for office workers. They share a similar approach but serve very different needs.
GitHub Copilot Chat
For developers, Copilot Chat lives inside VS Code, Visual Studio, and the GitHub website. You can select a function, hit a shortcut, and ask it to refactor code into a Promise-based pattern or explain a complex algorithm. It also generates unit tests, debugs errors, and can walk through unfamiliar codebases by answering questions line by line. One developer told me they used it to translate a Python script into JavaScript in under ten minutes, something that would have taken them hours with a search engine.
Microsoft 365 Copilot Chat
On the office side, Microsoft 365 Copilot Chat is tucked into Teams, Word, Outlook, and Excel. It summarizes meeting recordings, drafts replies, suggests formatting changes, and can even pull data from multiple documents to answer a question. The interface recently got a cleaner design and faster response times, making it less of a novelty and more of a daily driver for tasks you’d rather not do from scratch.
How Copilot Chat fits into a developer’s workflow
Copilot Chat isn’t just for beginners looking for syntax help. It’s becoming an essential tool for senior engineers and tech leads dealing with large, messy codebases. Here are some of the most practical ways developers are using it right now:
- Refactoring multi-file changes: Ask Copilot Chat to split a monolithic component into smaller, composable pieces, and it will suggest changes across your project structure.
- Writing edge-case-heavy tests: Instead of writing boilerplate, you can prompt it to generate test cases for null inputs, network failures, and timeout scenarios.
- Explaining inherited code: When you drop into a legacy module with outdated patterns, Copilot Chat can annotate what each block does and flag potential pitfalls.
- Language translation: Moving from Python to Go or Java to Kotlin? Copilot Chat can rewrite small functions and point out idiomatic differences.
But that convenience doesn’t come without a cost. As we’ll see, GitHub is radically changing how much you pay for that assistant.
The pricing shake-up: token-based billing
GitHub made headlines in early 2025 when it announced that Copilot Chat would move to a token-based billing model. Instead of paying a flat monthly fee, heavy users will pay based on “compute” and “token” usage. The reaction among developers was immediate and loud. Many took to forums and social media with words like “what a joke” after seeing the formula. The consternation among devs isn’t just about cost; it’s about predictability. A developer who asks Copilot Chat to review a multi-file pull request could burn through a day’s quota in twenty minutes.
The new model is also more complex. GitHub will charge differently for code completion versus chat interactions, and premium models will cost more per token. The company argues that this aligns pricing with actual AI usage, but for teams with tight budgets, the uncertainty is frustrating. GitHub’s new usage-based charging starts with an allowance, and anything above that is metered. If you’re a solo developer, you may need to keep an eye on your token consumption alongside your code quality.
Copilot Chat in the office: Microsoft 365 gets a speed boost
On the productivity side, Microsoft has been quietly improving Copilot Chat’s responsiveness. The recent update to Microsoft 365 Copilot reduced launch time by nearly half and made the UI more intuitive. For example, when you ask it to summarize a Teams meeting, the answer now includes inline citations that point to the exact timestamp, so you can verify without leaving the app. It also handles follow-up questions better. You can ask “What about action items?” and it knows you’re still talking about the same meeting.
These improvements matter because they address the biggest complaint with early Copilot Chat: it was fast enough to feel magical, but slow enough to annoy. Now, with the cleaner design, it feels like a native feature rather than a bolt-on experiment.
Beyond Copilot Chat: open-source alternatives worth watching
Not everyone is happy with the direction Microsoft and GitHub are taking. Some developers are looking for alternatives that don’t tie into a proprietary ecosystem or a metered billing system. One of the most interesting options is Alibaba’s Qwen Chat, which is open source and has drawn attention for its strong reasoning abilities. A recent comparison of Qwen Chat’s performance shows it holding its own against larger proprietary models on code generation and math tasks. For devs who want to self-host or simply avoid namespace confusion, Qwen is a credible option.
Open-source alternatives also give teams more control over data privacy. With Copilot Chat, your code snippets and prompts are processed by Microsoft servers, which is a deal-breaker for some enterprises. With a local model, sensitive code never leaves the building.
Where Copilot Chat is headed next
The future of Copilot Chat isn’t just about getting answers in a side panel. It’s about integrating the AI directly into the tools you already use. That’s the premise behind CopilotKit, an open-source framework that lets developers embed AI agents into their own apps. CopilotKit recently raised $27 million to help developers deploy these assistants without building them from scratch. This suggests a world where every app has its own native Copilot Chat, not just as a chat bubble but as an agent that can click buttons, fill forms, and run workflows on your behalf.
Microsoft’s broader roadmap also points in that direction. A recent analysis of Microsoft Copilot in 2025 highlights which features deliver real value and which are still gimmicks. The most successful implementations so far are the ones where Copilot Chat takes initiative, like automatically suggesting a document template or pre-populating a debugging session, rather than waiting for a prompt.
The challenge will be balancing that proactive behavior with user trust and cost. As Copilot Chat becomes more context-aware, it will need to manage when to ask for permission and how to consume tokens efficiently. The teams that figure out that balance will define the next wave of AI-assisted work.