# GPT-5 Projects at AI Tinkerers

> Canonical HTML: https://aitinkerers.org/technologies/gpt-5
> Markdown URL: https://aitinkerers.org/technologies/gpt-5.md
> Technology record last updated: 2026-02-23T10:00:13Z
> Generated: 2026-09-22T18:41:54Z

OpenAI's GPT-5: The unified, multimodal foundation model delivering PhD-level reasoning and state-of-the-art coding performance.

Copy that: GPT-5 is OpenAI's flagship multimodal model, launched August 7, 2025, as the successor to GPT-4. This is a major architectural shift: it unifies advanced reasoning capabilities (like the 'o-series' models) and rapid response times into a single system, eliminating the need for manual model switching (Source: OpenAI, August 2025). The model demonstrates state-of-the-art performance across technical benchmarks (math, programming, finance) and features a massive 272,000-token context window (Source: Jagran Josh, Voiceflow). Developers access it via the API in variants—including `gpt-5-mini` and `gpt-5-nano`—optimized for latency and cost trade-offs, making this frontier intelligence accessible across all ChatGPT tiers (Source: Botpress, Jagran Josh, Voiceflow).

- Official technology site: https://openai.com/gpt-5
- Public AI Tinkerers demos and talks: 30
- Result page: 1 of 2

## Recent Public Talks and Demos

### [From Meow to Mastery: Building MathCat’s Adaptive Learning Platform](https://hong-kong.aitinkerers.org/talks/rsvp_nk7cD0uzBpI)

MathCat.fun is an adaptive, bilingual math and science practice platform for Hong Kong primary school children, aligned to the EDB curriculum and playable as a Progressive Web App. For this demo, I’ll walk through the full stack, not just the game UI. Live, I’ll briefly show the working app (different play modes, leaderboard, rewards shop, etc); but will focus more on the backend: (1) the question-generation and validation workflow – the balance between deterministic and probabilistic models to achieve the best outcome and my learnings; (2) talk about the AI critic pipeline (Gemini + GPT-5) that scores each question template on Cantonese naturalness, HK school terminology, hint quality, and age fit (3) the adaptive progression architecture—mastery gates, recent-accuracy windows, skill unlocks, etc; (4) the overall architecture.

- Event context: AI Tinkerers Hong Kong: August Meetup with OAX Foundation and GMAsia — 2026-08-31 — Hong Kong
- Public talk page: https://hong-kong.aitinkerers.org/talks/rsvp_nk7cD0uzBpI

### [Prairie Engine and the Frontier of Simulation](https://atlanta.aitinkerers.org/talks/rsvp_OG4-D-AvZ7g)

I built a general simulation engine. Once a user puts in an API key, they can type something in and the engine will generate a full simulation complete with metrics, visuals, and a cohesive storyline. The central mechanism is having an LLM rewrite an entire .html page to render each "turn," as opposed to static text-only replies.

- Event context: AI Tinkerers Atlanta: 2-Year Anniversary & Best Demos of the Year — 2026-07-30 — Atlanta
- Public talk page: https://atlanta.aitinkerers.org/talks/rsvp_OG4-D-AvZ7g

### [Mac Companion](https://islamabad-rawalpindi.aitinkerers.org/talks/rsvp_TJdw2lkaKBQ)

Mac Companion is a native macOS voice agent, with three modes: Transcription (live, Parakeet/Whisper), Companion (notch-anchored async shell), and Assistance (voice-to-tool-calls, coming next)

- Event context: AI Tinkerers Islamabad - July 18, 2026 — 2026-07-18 — Islamabad Rawalpindi
- Public talk page: https://islamabad-rawalpindi.aitinkerers.org/talks/rsvp_TJdw2lkaKBQ

### [Hacking The Browser For Fun ~And Profit~](https://sf.aitinkerers.org/talks/rsvp_dZETAb_xF00)

We'll talk about XBOW's research into native application hacking: the agents' structure, objectives, and inner "iteration" patterns which worked to discover a few dozen high severity bugs in Chromium, including demoing an exploit of one vulnerability which has already been patched.

- Event context: AI Tinkerers San Francisco: Offensive Security Demo Night — 2026-06-26 — San Francisco
- Public talk page: https://sf.aitinkerers.org/talks/rsvp_dZETAb_xF00

### [Building an AI publishing platform with an AI dev squad](https://tokyo.aitinkerers.org/talks/rsvp_CzSJETAJ9-4)

CloudAuthor — a full-stack AI authoring platform, 14 agents, 27 skills, 300+ tests, built in 2 months on .NET Aspire and TypeScript/Vite. Live demo in two halves. First, I'll run the end-to-end publishing pipeline through CloudAuthor's agents: ideation → research → quote-finding → drafting → editing → banner creation → Japanese translation → carousel generation. Each stage is a specialized agent handing off to the next, all streaming in front of you. Then I'll switch to Visual Studio Code and show the squad of 7 specialized coding agents I actually use to build CloudAuthor itself — the agents that wrote the agents.

- Event context: AI Tinkerers Tokyo - Shinagawa: May 26th Meetup — 2026-05-26 — Tokyo
- Public talk page: https://tokyo.aitinkerers.org/talks/rsvp_CzSJETAJ9-4

### [MakoraGenerate - AI Agent for Optimizing GPU Code](https://poland.aitinkerers.org/talks/rsvp_bSNP53ASxRc)

MakoraGenerate writes highly performant GPU kernels, low-level code that is the backbone of modern AI compute infrastructure.

- Event context: AI Tinkerers Poland - Meetup in Gdańsk #1 — 2026-04-23 — Poland
- Public talk page: https://poland.aitinkerers.org/talks/rsvp_bSNP53ASxRc

### [Deterministic tools, Non-Deterministic orchestration — Building a production AI Agent for auto parts lookup](https://poland.aitinkerers.org/talks/rsvp_8D7UFMN443Y)

An AI agent that takes a car's registration number and returns purchasable replacement parts, solving a problem of a fragmented Polish aftermarket where no single API covers all brands. The system splits the problem into deterministic source selection (which API to call, in what order, per brand) and an LLM-orchestrated agent asks clarifying questions when data is ambiguous, and combines partial results from multiple sources.

- Event context: AI Tinkerers Poland - Meetup in Gdańsk #1 — 2026-04-23 — Poland
- Public talk page: https://poland.aitinkerers.org/talks/rsvp_8D7UFMN443Y

### [Using Storybook To 10X Frontend Dev With Coding Agents](https://singapore.aitinkerers.org/talks/rsvp_Rgvf7fv-1Qg)

Implemented Storybook in an open source project where Storybook became the main development surface for frontend work. Experimented and over time, developed a heavily storybook driven approach for frontend development that works really well with frontier coding agents. Demo points: - Intro to storybook - Why storybook makes sense today with coding agents - Key benefits: Cleaner code structure, improved coding agent results, significantly less manual QA - How to use storybook descriptions to provide live intent to the coding agent - How to set up a long running task with feedback to solve a complex frontend problem

- Event context: AI Tinkerers Singapore: The Agentic Future & Dev/Eng Workflows — 2026-04-21 — Singapore
- Public talk page: https://singapore.aitinkerers.org/talks/rsvp_Rgvf7fv-1Qg

### [A language of logic](https://cologne.aitinkerers.org/talks/rsvp_E9bB1JtSMsU)

We're integrating LLMs with mathematical proof solvers/constrain optimizers to allow our LLM driven system to carry out specific logical tasks and calculations while maintaining explainability for the user.

- Event context: AI Tinkerers Cologne 4: Live Technical Demos — 2026-04-16 — Cologne
- Public talk page: https://cologne.aitinkerers.org/talks/rsvp_E9bB1JtSMsU

### [FuzzyClaw](https://cologne.aitinkerers.org/talks/rsvp_71A8QTW9ocg)

FuzzyClaw is an agent orchestration platform that turns markdown briefings into coordinated multi-agent work. A coordinator agent interprets the briefing, dispatches specialist agents running in isolated Docker containers, and routes their outputs into PostgreSQL, where they can be reviewed through a Django dashboard. Agents, the coordinator, and the human operator communicate in real time via a Redis-backed message board. The project is written in Python and draws inspiration from Steinberg’s OpenClaw and Qwibit.ai’s nanoclaw, with a strong focus on visibility, control, and practical day-to-day use.

- Event context: AI Tinkerers Cologne 4: Live Technical Demos — 2026-04-16 — Cologne
- Public talk page: https://cologne.aitinkerers.org/talks/rsvp_71A8QTW9ocg

### ["Saiba se sua campanha de mkt vai funcionar — antes de gastar R$ 1 em mídia."](https://saopaulo.aitinkerers.org/talks/rsvp_J6TWETVWK-U)

Ágora é um simulador de sucesso de campanha de mkt, com multiagentes que analisam, validam e comparam campanhas para identificar o que realmente gera resultado, aumentando a conversão de vendas sem depender de achismos. Através de um motor multi-agentes que funciona como um conselho de especialistas de marketing: 1. Um Analista Sociocomportamental que classifica sua campanha na era certa do marketing (1.0 ao 4.0), identifica de qual geração é seu público alvo (Z, Millennials, X, Boomers) e mapeia os vieses cognitivos a serem explorados. 2. Um Engenheiro de Oferta que desconstrói a promessa da sua campanha usando a matemática do Valor Percebido (Resultado x Probabilidade / Tempo x Esforço), apontando gargalos de fricção ou credibilidade. 3. Um Cientista de Dados de Performance que audita seus KPIs, punindo métricas de vaidade e definindo seu Timing Index para saber se "agora" é o momento certo para ir ao mercado. A Ágora oferece velocidade (análise em minutos, não semanas), previsibilidade (reduzindo em até 76% o custo de experimentação) e segurança para suas decisões, tudo isso com um custo até 90% menor que a pesquisa tradicional.

- Event context: AI Tinkerers SP e Banco BMG — 2026-03-26 — São Paulo
- Public talk page: https://saopaulo.aitinkerers.org/talks/rsvp_J6TWETVWK-U

### [Clawing My Way into Reddit](https://seattle.aitinkerers.org/talks/rsvp_USr7f6euQR0)

Am the creator of AI Game Master - https://aigamemaster.app - so naturally we're compelled to embrace AI when it comes. We've started utilizing F5Bot to listen for Reddit posts on interesting subjects. Now we're in the midst of setting up OpenClaw (previously ClawdBot previously Moltbook) to tap into those conversations independently and in effect become a vigilant marketer, plugging in our content in the right organic context.

- Event context: AI Tinkerers Seattle: GTM Track — March — 2026-03-26 — Seattle
- Public talk page: https://seattle.aitinkerers.org/talks/rsvp_USr7f6euQR0

### [Experience Vibing with metaMe](https://nyc.aitinkerers.org/talks/rsvp_fPIx41io4cs)

metaMe is a registry-driven agent runtime and studio that dynamically composes AI interfaces and experiences from structured context rather than fixed screens. For the demo, I’ll show how the metaMe Runtime, Studio, and Registry work together to generate live experience surfaces based on three active layers of context: persona, agent/model, and cartridge/codex. Instead of treating UI as a hardcoded frontend, the system resolves registry-defined primitives, policies, and active agents into runtime behavior such as smart menus, prompt surfaces, trust indicators, and domain-specific experience states. The demo will focus on the implementation: how context is modeled, how the runtime is hydrated, how dynamic rendering decisions are made, and how secure agent/tool execution is routed.

- Event context: March Demo Day, hosted by Flowglad — 2026-03-18 — New York City
- Public talk page: https://nyc.aitinkerers.org/talks/rsvp_fPIx41io4cs

### [Budget by Chatting: Building a multi-channel AI-powered expense tracker](https://upstate-ny.aitinkerers.org/talks/rsvp_tB4HZsZid7I)

SetForMoney is a household budgeting web app. Users text "groceries 45 Sams Club" to Telegram, WhatsApp, SMS, or a web chat and an LLM model parses the amount, matches the category, and detects intent from raw natural language. Three things worth looking at under the hood: 1. The prompt architecture that handles expenses, questions, commands, and gibberish from a single parsing call, with fuzzy category matching that recovers from typos. 2. Channel-aware response formatting: same AI brain, different output constraints (SMS under 300 chars vs. rich web formatting). 3. Silent feature request detection: the chat assistant answers users normally while flagging unmet feature requests behind the scenes, then a nightly job clusters them into a demand-ranked product roadmap. Live production demo.

- Event context: AI Tinkerers Upstate NY: March Meetup — 2026-03-10 — Upstate NY
- Public talk page: https://upstate-ny.aitinkerers.org/talks/rsvp_tB4HZsZid7I

### [AI + NSA tools = reverse-engineering fun!](https://poland.aitinkerers.org/talks/rsvp_rJtv5m7joDU)

With the newest models we can add reverse engineering to our list of everyday skills. We recently created an open-source BinaryAudit AI benchmark - seeing if models can find a backdoor from binary only, when given access to Ghidra - a decompilation program by NSA. But it is not only work! We can: - Get infinite lives in a classical Atari game River Ride by changing binary code directly with Claude (not even Claude Code!). - Take the binary old game Chromatron from PowerPC to Apple Silicon (and WASM). - Create a Bluetooth interface for an LED backpack. - Decode a thermal camera image format (data encoded in JPGs).

- Event context: AI Tinkerers Poland x Codex - Meetup in Warsaw #7 (4th March, Wednesday) — 2026-03-04 — Poland
- Public talk page: https://poland.aitinkerers.org/talks/rsvp_rJtv5m7joDU

### [JobsYo: Building an AI-based but Human-driven Job Search, Research and Apply Ecosystem](https://toronto.aitinkerers.org/talks/rsvp_kotKIOHzcrE)

Live demo of JobsYo, an AI-powered job search platform I built to automate & organize job hunt - built based on my own experience. I'll show the technical internals: 1. Multi-Model AI Chatbot dedicated for Customized Application and Connection: How I built a unified abstraction layer that routes between GPT-5, Gemini 3, and Claude based on user preferences, with encrypted API key storage and streaming response handling across all providers. 2. Context Engineering: The unified prompt system that dynamically injects user profiles, parsed job requirements, base resumes, and linked networking connections into a single context window - enabling AI to generate highly tailored responses. 3. Agentic Job Discovery: Orchestration function that coordinates 4 different job APIs (Adzuna, JSearch, RemoteOK, custom scrapers), handles deduplication, and generates AI recommendations for failed sources. 4. Profile-to-Job Matching: AI-powered analysis that compares parsed user profiles against job requirements and provides actionable improvement suggestions. All running on React + Supabase Edge Functions with real-time streaming.

- Event context: AI Tinkerers Toronto - January 2026 Meetup at Google! — 2026-01-29 — Toronto
- Public talk page: https://toronto.aitinkerers.org/talks/rsvp_kotKIOHzcrE

### [vibe MLing - e2e finetunes on arbitrary domains with claude code via carefully synthesized data](https://cologne.aitinkerers.org/talks/rsvp_q79JPVgHEdM)

Inspired by huggingface's recent blog post on using Claude code to fine tune a model with an existing dataset (via their new CC skill), I wanted to see how much more of the e2e finetune process could be captured in SKILLs. Had a few days over Xmas break and 150 commits later I have 3 new SKILLs to share with the community to help (1) extract domain knowledge (2) iteratively generate and filter synthetic data and (3) run the finetune and eval it Have lots of challenges and learnings to share how I did it. I chose therapeutic coaching as my domain (but the SKILLs apply generally) and the resulting 14b finetuned model competes with human text based therapy

- Event context: AI Tinkerers Cologne #2: Let's Build. — 2026-01-21 — Cologne
- Public talk page: https://cologne.aitinkerers.org/talks/rsvp_q79JPVgHEdM

### [Writing an arXiv Paper (in a Day)](https://tokyo.aitinkerers.org/talks/rsvp_giYhKcFdlUE)

Recently, we open-sourced several of the most useful evals we used for developing our Shisa V2 models. One of the most useful was JP-TL-Bench, our Japanese/English translation eval. It's notable because it introduces a brand new methodology for doing better scoring (combining the discriminative power of pair-wise completions, but avoiding both the quadratic scaling and the score drift that come with normal scoring, like ELO). It's worth writing a paper about. How can we best use AI to help us write a paper efficiently, without it being complete slop?

- Event context: AI Tinkerers Ginza Meetup – January 15, 2026 — 2026-01-15 — Tokyo
- Public talk page: https://tokyo.aitinkerers.org/talks/rsvp_giYhKcFdlUE

### [DnDnAI, Game Master creation at the speed of tokens](https://denver-boulder.aitinkerers.org/talks/rsvp_121evH4Fx6I)

DungeonMind.net, I've got a number of tools from item card generation to statblock generation. All using image generation and text generation.

- Event context: AI Tinkerers Denver Meetup - November 24, 2025 — 2025-11-25 — Denver
- Public talk page: https://denver-boulder.aitinkerers.org/talks/rsvp_121evH4Fx6I

### [Readback: ATC Communication Training with an AI for Pilots](https://berlin.aitinkerers.org/talks/rsvp_qgOUsztbvzI)

Radio calls with ATC is stressful for a lot of student and private pilots especially if there are other experienced pros on the same frequency. The best way to overcome this nervousness is practice, practice, practice. Readback provides pilots with a calm, professional and infinitely patient ATC controller to practice with.

- Event context: AI Tinkerers Berlin Meetup - November 12th, 2025 — 2025-11-12 — Berlin
- Public talk page: https://berlin.aitinkerers.org/talks/rsvp_qgOUsztbvzI

### [Back2Back: Collaborative DJing With AI](https://nyc.aitinkerers.org/talks/rsvp_Oe4Utq0vULQ)

I made an iOS app that uses GPT-5 (high thinking with web search) to generate a DJ 'persona' based on a user description. This persona is used to pick selections from Apple Music. The user and AI trade off picking songs, and the AI is influenced by both the persona and the session picks. Or, you can just let the AI handle all the selections and it becomes more of a music discovery tool.

- Event context: Auth0 x AI Tinkerers: Fall Social Demo Night 🍁 ft. Hex — 2025-11-06 — New York City
- Public talk page: https://nyc.aitinkerers.org/talks/rsvp_Oe4Utq0vULQ

### [Blueprints, re-imagined](https://cologne.aitinkerers.org/talks/rsvp_stwBaO458Iw)

I will show how we are building a gen AI-based tool that can read a process flow diagram of a chemical factory and generate a rigorous process description. Explaining the background + showing code + doing a live demo should take about 10 minutes, shorter also possible but maybe less useful...

- Event context: AI Tinkerers Cologne – Inaugural Meetup — 2025-11-05 — Cologne
- Public talk page: https://cologne.aitinkerers.org/talks/rsvp_stwBaO458Iw

### [Codex as a MCP Tool](https://seattle.aitinkerers.org/talks/rsvp_3HZGii6peu0)

I’ll show an example of how to use Codex as a tool for a bug fixing agent that you can assign bugs to in a kanban board

- Event context: AI Tinkerers Seattle Meetup: Dev Tools Track — November 3, 2025 — 2025-11-04 — Seattle
- Public talk page: https://seattle.aitinkerers.org/talks/rsvp_3HZGii6peu0

### [Deceiving LLMs in a videogame into surrendering passwords](https://london.aitinkerers.org/talks/rsvp_TRHHph3-9v4)

Previously I wrote a free hacking game where you chat to NPCs to get password info, clues, etc ... then I upgraded it to use an LLM for each NPC, and now you use social engineering techniques to trick the LLMs into giving you their passwords, their personal email addresses, etc. Legacy GPT-4o worked great. GPT-5 caused me some problems ... LLMs get 'too clever' and the NPC's narrate how they're "walking down the hallway to go talk to IT" when you're trying to get them to give you a password (player pretending to be the IT dept). (everything is fake - obviously! This is a game! NO real servers were harmed!)

- Event context: AI Tinkerers London Meetup - 29th October 2025 — 2025-10-29 — London
- Public talk page: https://london.aitinkerers.org/talks/rsvp_TRHHph3-9v4

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## More Results

- Next: https://aitinkerers.org/technologies/gpt-5.md?page=2