# GitHub Copilot Projects at AI Tinkerers

> Canonical HTML: https://aitinkerers.org/technologies/github-copilot
> Markdown URL: https://aitinkerers.org/technologies/github-copilot.md
> Technology record last updated: 2026-09-18T15:13:46Z
> Generated: 2026-09-21T23:34:53Z

GitHub Copilot is your AI pair programmer, delivering real-time code suggestions, generating unit tests, and summarizing pull requests directly in your IDE.

GitHub Copilot acts as your generative AI pair programmer, accelerating development by suggesting lines and entire functions in real time, often appearing as 'ghost text' directly in your IDE (VS Code, Visual Studio, JetBrains IDEs). Leveraging models like GPT-4.1, it moves beyond simple completions: developers use Copilot Chat for complex tasks like generating unit tests, explaining code, or using Copilot Edits to make changes across multiple files from a single natural language prompt. This tool integrates deeply into the workflow, from code creation to AI-generated pull request summaries, significantly boosting developer productivity.

- Official technology site: https://github.com/features/copilot
- Public AI Tinkerers demos and talks: 20
- Result page: 1 of 1

## Recent Public Talks and Demos

### [Adaptive Tool Orchestration with On-Demand Discovery and Code Mode Execution](https://ho-chi-minh-city.aitinkerers.org/talks/rsvp_ha31N9dlK_A)

A unified MCP transform that replaces static tool catalogs with intelligent, on-demand discovery while enabling dynamic orchestration through code mode execution. Instead of exposing every tool upfront, the system allows the model to search and resolve tools contextually, then generate and execute controlled C# workflows to chain calls efficiently. Implemented using the GitHub Copilot C#/.NET SDK and the MCP .NET SDK, this approach minimizes prompt overhead, reduces round-trips, and enables scalable, runtime tool composition within enterprise-grade .NET environments.

- Event context: AI Tinkerers Ho Chi Minh City: AI Coding Agents & Orchestrators — 2026-04-18 — Ho Chi Minh City
- Public talk page: https://ho-chi-minh-city.aitinkerers.org/talks/rsvp_ha31N9dlK_A

### [Replacing a consultant with an AI Council](https://columbus.aitinkerers.org/talks/rsvp_HPzao1xqrvI)

We had an outside consultant to write code on a legacy platform that none of our developers knew. AI was able to write some of the code, with mixed accuracy, and us being unable to verify it. But using a mixture of models, we were able to get something better than any individual model could produce. In this talk, I'll show how we played models from different providers against each other to sharpen and improve results.

- Event context: AI Tinkerers - Columbus March Meetup — 2026-03-02 — Columbus
- Public talk page: https://columbus.aitinkerers.org/talks/rsvp_HPzao1xqrvI

### [Brief: build context infrastructure so agents stop guessing](https://seattle.aitinkerers.org/talks/rsvp_pul20-6rImI)

A CLI that gives coding agents a deterministic understanding of how your code works. Brief helps Claude Code complete tasks 30% faster and use up to 45% fewer tokens. When an AI agent needs to modify something in your codebase, it searches around - grepping, reading files, building a mental model one piece at a time. Brief replaces that with a single query. You ask `brief context "how does task creation work"` and it locates key information, dynamically traces execution paths, and returns a layered understanding of where everything is and how it works. The agent starts with a complete picture of what exists and how it works, rather than spending time and tokens figuring out what is usually an incomplete or flawed understanding before doing the actual work. Brief provides telescoping context across the codebase, zoomed to the correct level for each relevant part: AST parsed manifest of every class, function, and dependency, traced execution flows through the call chain, LLM summaries of what each method and file does, detected conventions/contracts, and related code. I'll demo the core loop, show how the static analysis and dynamic tracing work under the hood, and walk through what a real context package looks like at each layer - from high-level file descriptions down to traced execution paths with code. This is a working tool I use daily with Claude Code. I'll show where it works well, where it breaks, and how I think it could be improved or built upon.

- Event context: AI Tinkerers Seattle: January Meetup — 2026-01-31 — Seattle
- Public talk page: https://seattle.aitinkerers.org/talks/rsvp_pul20-6rImI

### [Code Less, Create More: AI's productivity Revolution](https://manchester-nh.aitinkerers.org/talks/rsvp___SyeaCKrk0)

In this demonstration we'll explore how organizations are leveraging AI-powered development tools to accelerate delivery, reduce technical debt, and empower their workforce to shift from their role as just "code writers" and "programmers" to innovators. We'll examine real-world examples of productivity gains, discuss the paradigm shift in how we approach software development, and reveal how organizations are reclaiming time for their teams to do what humans do best—think creatively, collaborate meaningfully, and drive transformational change

- Event context: AI Tinkerers – Manchester/Bedford Inaugural Meetup · January 20, 2026 — 2026-01-20 — Manchester NH
- Public talk page: https://manchester-nh.aitinkerers.org/talks/rsvp___SyeaCKrk0

### [Uplift Entrepreneurs & Businesses in ways only dreamed possible.](https://toronto.aitinkerers.org/talks/rsvp_5ZeIl1ne2c0)

Originally conceptualized for the Google AI Hackathon weeks ago .. Atticus fills a huge privacy & capability void for startups (and existing businesses). Tooling helps builders, build great things ..

- Event context: AI Tinkerers Toronto - December Meetup sponsored by Auth0 and TribalScale! — 2025-12-03 — Toronto
- Public talk page: https://toronto.aitinkerers.org/talks/rsvp_5ZeIl1ne2c0

### [Unified AI Rules Management: How to Prevent Vendor Lock-In Across AI Coding Tools](https://denver-boulder.aitinkerers.org/talks/rsvp_QKi_t-f5j0A)

A live demonstration of rulesync, a Node.js CLI tool that solves the growing problem of AI development tool fragmentation. I'll show how to maintain consistent AI coding assistant rules across Claude Code, Cursor, GitHub Copilot, Cline, and 15+ other tools from a single source of truth. The demo will include: - Generating unified rules, MCP servers, commands, and subagents - Demonstrating how teams can switch between AI tools without redefining rules - Practical patterns for team-wide AI governance and consistency

- Event context: AI Tinkerers Denver Meetup - November 24, 2025 — 2025-11-25 — Denver
- Public talk page: https://denver-boulder.aitinkerers.org/talks/rsvp_QKi_t-f5j0A

### [Building a vibe-coding community](https://hong-kong.aitinkerers.org/talks/rsvp_-fkHAQKFZ8o)

We built websites with the help of AI to allow everyone to generate apps/games/art and share and learn such creations from one another on a social media platform. We've encountered various challenges along the way and will share our journey.

- Event context: AI Tinkerers Hong Kong Meetup - October 22nd — 2025-10-22 — Hong Kong
- Public talk page: https://hong-kong.aitinkerers.org/talks/rsvp_-fkHAQKFZ8o

### [AutoLearn-What happens when we make Agents deterministic](https://seattle.aitinkerers.org/talks/rsvp_qsVCSui3bOE)

AI agent reasoning loops are expensive and fail often (5%+). What if we could move those conditions off of the transformer and into deterministic code, automatically?

- Event context: AI Tinkerers Seattle Meetup: Dev Tools Track — October 6, 2025 — 2025-10-07 — Seattle
- Public talk page: https://seattle.aitinkerers.org/talks/rsvp_qsVCSui3bOE

### [AI Insights and Applications](https://orange-county.aitinkerers.org/talks/rsvp_ZVuuYqph8yQ)

I will use PPT to Share unique prompt inquiries such as: Johari Window, Theory of Constraints, Theory of Invention, Quantum mechanics, Phase space with a variety of objects.

- Event context: AI Tinkerers - Orange County Meetup- Thursday July 31st 2025 — 2025-08-01 — Orange County
- Public talk page: https://orange-county.aitinkerers.org/talks/rsvp_ZVuuYqph8yQ

### [Our Successful Bootstrap Journey (so far)](https://seattle.aitinkerers.org/talks/rsvp_qJzQqPjnyzU)

AI Game Master is really hitting it off with traction and monetization. We're a 2-man (1-developer) team with no funding - I think this could speak to a lot of people

- Event context: AI Tinkerers Seattle - March Meetup — 2025-03-28 — Seattle
- Public talk page: https://seattle.aitinkerers.org/talks/rsvp_qJzQqPjnyzU

### [Next level AI-driven development with Cursor - .cursorrules, Notepads and MCP services](https://boston.aitinkerers.org/talks/rsvp_QxwOEL8ufAw)

At the last AI tinkerers, I was convinced by another attendee to switch IDEs from VSCode to Cursor. Since then I've been learning how to get the most from Cursor and want to share several of my findings. 1) Agent Mode - Cursor's superpower (but now in Co-Pilot) - Quick basics - how to use it, how is composer + agent (+ yolo?) different from chatting. - how to get agent mode to work better - context, @ 2) Building / working with larger projects, frameworks like NextJS - The .cursorrules file - why you should have one in all your projects - The FORMAT matters - markdown is not best! JSON is better - Several repositories for best practice cursor rules files. - Notepads - what happens when you do and don't use these. - Model Context Protocol servers and services and when/why you would use these while developing 3) Time permitting - the AI Secretary .cursorrules file - going beyond coding in Cursor

- Event context: AI Tinkerers Boston February 2025 — 2025-02-24 — Boston
- Public talk page: https://boston.aitinkerers.org/talks/rsvp_QxwOEL8ufAw

### [⏩ v0 + Windsurf agentic workflow ⏩](https://seattle.aitinkerers.org/talks/rsvp_vP863RVH9tU)

It’s tricky to find time to discover all the new AI tools out there - yet alone try them out. I’ll demo a workflow I used to quickly and easily spin up holiday party RSVP and guest chat site using AI tools for planning and design and an AI agent-enabled IDE.

- Event context: AI Tinkerers Seattle - Women in AI Gathering — 2024-12-06 — Seattle
- Public talk page: https://seattle.aitinkerers.org/talks/rsvp_vP863RVH9tU

### [AI in course prep and student usage](https://phoenix.aitinkerers.org/talks/rsvp_UC0gF8RHCn0)

AI's are great tools to help us formulate thoughts for presentations and also good tools to show students how to create/modify software. I use Gemini/CoPilot/ChatGPT to set up outlines for presentations and show the students how to take a program and modify a couple of ways.

- Event context: November 14th- AI Tinkerers PHX! — 2024-11-15 — Phoenix
- Public talk page: https://phoenix.aitinkerers.org/talks/rsvp_UC0gF8RHCn0

### [ai-fun: The LLM-powered function builder for TypeScript](https://vienna.aitinkerers.org/talks/rsvp_y5v5W6yDd4M)

ai-fun is an experimental LLM-powered function library. It lets you define the function purpose, the parameters and the output schema and generates and executes the code for you in the background. Think Cursor/GitHub Copilot but as a pluggable library.

- Event context: AI Tinkerers Vienna ICML Edition — 2024-07-24 — Vienna
- Public talk page: https://vienna.aitinkerers.org/talks/rsvp_y5v5W6yDd4M

### [Plan Quest Demo](https://seattle.aitinkerers.org/talks/rsvp_Om-GA1Q2CG4)

Plan Quest helps with planning, tracking progress and retrospection. It uses AI to: - Turn an aspiration (ex: I want to run a marathon) into a detailed plan with a clear timeline and milestones. Each milestone is an objective with multiple key results. - Helps you identify new key results for an objective. For example, it would generate something like "Run 10 miles without stopping" - Helps you set clearer goals that are outcome base rather than activity based. For example, if your goal is "Run 10 miles without stopping", it would suggest something like "Complete 10-mile run in under 1 hour 30 minutes" - Automatically break down a goal (key result) into a task list, such as 'Run 5 miles twice this week,' 'Incorporate interval training,' and 'Increase distance by 1 mile each week.'

- Event context: AI Tinkerers Seattle - May 2024 — 2024-05-21 — Seattle
- Public talk page: https://seattle.aitinkerers.org/talks/rsvp_Om-GA1Q2CG4

### [AI Fundamentals and Best Practices](https://boston.aitinkerers.org/talks/rsvp_IG8YsirTKPs)

Goal of this is to provide high level information while also showing some basic tips and tricks to make the most out of using AI whether you're brand new to AI or you've been creating your own models. I'll go through some ways i've been using chatGPT/Co-Pilot and take questions.

- Event context: March 2024 Meetup at C10 Labs — 2024-03-25 — Boston
- Public talk page: https://boston.aitinkerers.org/talks/rsvp_IG8YsirTKPs

### [AI Coding with repository context](https://london.aitinkerers.org/talks/rsvp_mJJgD012OXc)

The world of AI assisted coding is moving at a blazing fast speed. There are numerous products and models which excel at various different aspects of the coding experience. We will go from copilot based code generation, to using AI to convert your prompt to edits in the codebase and possible ideas to fine-tune on a codebase and make LLMs understand a new codebase. The rise of open source models has also made it possible for anyone to run their own local copilot, these models can be coached to fit your own usecase quite easily when prompted and fine-tuned for your usecase.

- Event context: AI Tinkerers London - January Meetup — 2024-01-30 — London
- Public talk page: https://london.aitinkerers.org/talks/rsvp_mJJgD012OXc

### [ZenCoder - Convert your scripts into MLOps pipelines](https://munich.aitinkerers.org/talks/rsvp_d9dijtVwpU0)

One of the first jobs of somebody entering MLOps is to convert their manual scripts or notebooks into pipelines that can be deployed on the cloud. This job is tedious and can take time. Frameworks like [ZenML](https://github.com/zenml-io/zenml) go a long way in alleviating this burden by abstracting much of the complexity away. However, recent advancements in Large Language Model-based Copilots offer hope that even more repetitive aspects of this task can be automated. Unfortunately, most open source or proprietary models like GitHub Copilot are often lagging behind the most recent versions of ML libraries, therefore giving erroneous our outdated syntax when asked simple commands. This project aims to fine-tune an open-source LLM that performs better than off-the-shelf solutions in giving the right output for the latest version of ZenML. Just to make it a bit more fun, we're going to be building ZenML pipelines to achieve this task! That way we write ZenML pipelines to train a model that can produce ZenML pipelines 🐍! Sounds fun!

- Event context: AI Tinkerers Munich - January 18 — 2024-01-18 — Munich
- Public talk page: https://munich.aitinkerers.org/talks/rsvp_d9dijtVwpU0

### [Rolling your own copilot](https://london.aitinkerers.org/talks/rsvp_1SKYfGm3vNI)

I think it might be fun to share a proof of concept I built over a few evenings recently. I was curious how easy it would be to develop copilot-like functionality with a vscode extension by finetuning gpt on your codebase. I prioritised speed of inference and the results are surprisingly good..

- Event context: AI Tinkerers London - November Meetup — 2023-11-28 — London
- Public talk page: https://london.aitinkerers.org/talks/rsvp_1SKYfGm3vNI

### [Experiences building a copilot for a specialized domain](https://seattle.aitinkerers.org/talks/rsvp_JcsEGqOZ6bk)

Existing approaches to understanding, developing and researching specialized domains like modern wireless communication technologies involves time-intensive and arduous process of sifting through numerous webpages and technical specification documents, gathering the required information and synthesizing it. This paper presents NextGen Communications Copilot, a conversational artificial intelligence tool for information synthesis of wireless communication specifications. The system builds on top of recent advancements in foundation models and consists of three key additional components: a domain-specific database, a context extractor, and a feedback mechanism. The system appends user queries with concise and query-dependant contextual information extracted from a database of wireless technical specifications and incorporates tools for expert feedback and data contributions. On evaluation using a benchmark dataset of queries and reference responses created by subject matter experts, the system demonstrated more relevant and accurate answers with an average BLEU score and BERTScore F1-measure of 0.37 and 0.79 respectively compared to the corresponding values of 0.07 and 0.59 achieved by state-of-the-art tools like ChatGPT.

- Event context: AI Tinkerers Seattle - August Meetup — 2023-08-09 — Seattle
- Public talk page: https://seattle.aitinkerers.org/talks/rsvp_JcsEGqOZ6bk

## Related Technologies

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- [Gemini](https://aitinkerers.org/technologies/gemini) ([Markdown](https://aitinkerers.org/technologies/gemini.md)) — 188 public demos
- [Next](https://aitinkerers.org/technologies/next) ([Markdown](https://aitinkerers.org/technologies/next.md)) — 186 public demos
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- [Claude Code](https://aitinkerers.org/technologies/claude-code) ([Markdown](https://aitinkerers.org/technologies/claude-code.md)) — 215 public demos
- [Fine-tuning](https://aitinkerers.org/technologies/fine-tuning) ([Markdown](https://aitinkerers.org/technologies/fine-tuning.md)) — 20 public demos
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- [TypeScript](https://aitinkerers.org/technologies/typescript) ([Markdown](https://aitinkerers.org/technologies/typescript.md)) — 205 public demos
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- [BERTScore](https://aitinkerers.org/technologies/bertscore) ([Markdown](https://aitinkerers.org/technologies/bertscore.md)) — 1 public demo
- [BLEU](https://aitinkerers.org/technologies/bleu) ([Markdown](https://aitinkerers.org/technologies/bleu.md)) — 1 public demo