# Playwright Projects at AI Tinkerers

> Canonical HTML: https://aitinkerers.org/technologies/playwright
> Markdown URL: https://aitinkerers.org/technologies/playwright.md
> Technology record last updated: 2026-09-18T15:14:00Z
> Generated: 2026-09-20T13:42:03Z

Playwright is the Microsoft-developed, cross-browser automation framework: it drives Chromium, Firefox, and WebKit with one unified API for fast, reliable end-to-end testing.

Playwright delivers robust, cross-platform end-to-end testing, supporting all major rendering engines: Chromium, Firefox, and WebKit. Launched by Microsoft in January 2020, its core strength is a single API for multiple languages (TypeScript, Python, Java, .NET). The framework eliminates flaky tests through automatic waiting and provides full test isolation by creating a new browser context (a brand-new browser profile) for each test. Key tooling includes Codegen for recording actions and the Trace Viewer for deep post-mortem analysis of test failures (screencasts, live DOM snapshots). This architecture ensures reliable, high-speed execution across Windows, Linux, and macOS.

- Official technology site: https://playwright.dev
- Public AI Tinkerers demos and talks: 32
- Result page: 1 of 2

## Recent Public Talks and Demos

### [I made my own slide deck engine](https://tokyo.aitinkerers.org/talks/rsvp_lE7fweh6jg0)

A presentation engine for UX design interviews: I designed slides in Figma, then ported them to web with 1) GSAP transitions, 2) live prototypes embedded in the slides, 3) a gallery/slide/fullscreen view, 4) a presenter popup with speaker notes, 5) and a cat-paw cursor 🐾. I'll show the tools: the Figma initialization, the in-product control panel where every slide-pair transition is a one-line row I can toggle live from a panel. I'll also show the motion lab I built first: a GSAP sandbox.

- Event context: AI Tinkerers Tokyo — October 5 Meetup — 2026-10-05 — Tokyo
- Public talk page: https://tokyo.aitinkerers.org/talks/rsvp_lE7fweh6jg0

### [The browser is all you need: an agent harness inside a Chrome extension](https://seattle.aitinkerers.org/talks/rsvp_JPy6ltZ-97s)

If you want to deploy an agent safely today, the normal answer is to glue together a VM or container, a sandbox, a filesystem, an identity broker, a credential manager, a browser, and some kind of durable workflow engine. Even after all of that, most harnesses inherit the identity of the person running them. You end up approving every action or giving a model the credentials of an over-provisioned developer. Rook takes a different approach. Treat the agent as a user and make the browser the harness. Rook runs entirely inside a Chrome extension and is encapsulated by the Chrome profile it is installed in. The profile gives it an identity, SSO, passkeys, password management, enterprise policy, tabs, and existing permissions. There is no remote browser, VM, separate credential broker, or server-side orchestrator. The identity and credentials stay in the browser profile instead of being brokered through us. The extension fills in the rest: an actor runtime, MCP host, code mode, memory, scheduled work, browser automation, file transfer, and first-party SDKs for services like Google Workspace. It has an Origin Private File System with Bash and git running directly in the browser. Local folders can be mounted explicitly, which lets the agent work with real files without giving it access to the rest of the computer. For the demo I will use Rook itself. I will have it work across a mounted folder, Google Workspace, and logged-in websites, run several agents at the same time, and then kill the MV3 service worker while they are working. After Chrome wakes the extension again, the same actors will reconnect to their SQLite databases, reclaim their tabs, resume their token streams, and continue.

- Event context: AI Tinkerers Seattle: August Demo Night w/ NVIDIA — 2026-08-20 — Seattle
- Public talk page: https://seattle.aitinkerers.org/talks/rsvp_JPy6ltZ-97s

### [Directed by Claude — Let AI use your App](https://bremen.aitinkerers.org/talks/rsvp_rk1k-89-Avk)

An agent that operates our product through its own UI — logs in, opens menus, types, reads the screen. Three uses came out of that: it finds its own bugs while building, the runs became an end-to-end suite, and the same rig shoots our demo videos. The video I'll play is one of its outputs.

- Event context: AI Tinkerers Bremen — 2026-08-14 — Bremen
- Public talk page: https://bremen.aitinkerers.org/talks/rsvp_rk1k-89-Avk

### ["QA a la velocidad de la luz (y sin fuga de datos): potenciando testing exploratorio con modelos de IA ejecutados 100% en local](https://panama.aitinkerers.org/talks/rsvp_RO5JPx08rOc)

FullQA.ai es una plataforma de QA asistida por IA que genera, documenta y automatiza casos de prueba a partir de la exploración de una aplicación web, ejecutando los modelos de lenguaje y visión completamente en local — sin depender de APIs externas ni exponer datos sensibles. En la demo mostraré en vivo un flujo completo de punta a punta: El sistema funcionando en tiempo real: una extensión de navegador captura la sesión exploratoria (clics, navegación, formularios) y el backend la convierte en documentación de QA estructurada con capturas por paso. Arquitectura: cómo se conectan la extensión, la app de escritorio, el servicio API y los modelos locales servidos vía Ollama, con fallback a disco y generación de imágenes deterministas por paso. Generación de código: cómo se produce automáticamente un script de Playwright listo para ejecutar a partir de la sesión grabada. Repo y logs: enseñaré el código real, la estructura de proyectos con contexto, y los logs de inferencia local corriendo sobre la GPU.

- Event context: AI Tinkerers Panamá: Construyendo el futuro con inteligencia artificial — 2026-07-31 — Panama
- Public talk page: https://panama.aitinkerers.org/talks/rsvp_RO5JPx08rOc

### [Quality in the age of AI](https://islamabad-rawalpindi.aitinkerers.org/talks/rsvp_L3a9baolTt0)

Orcastrator is an agentic QA automation system built to help teams keep software quality aligned with the speed of AI-assisted development. I began by discussing the quality challenges the software industry is facing as AI accelerates the delivery of code and features. I highlighted the concerns being reported by technology companies and research teams, and why maintaining quality is becoming increasingly important as development continues to move faster. From there, I used a live demo application to show how quality automation can now be authored through just a few prompts. The demonstration focused on how teams can move from understanding what needs to be tested to creating and executing meaningful automated tests with far less manual effort. I then showed how we have approached this problem with Orcastrator. The platform enables agentic quality automation that can operate at a speed much closer to modern software delivery, while remaining structured and powerful enough to provide meaningful coverage. The demo showed how application areas, test cases, execution runs, logs, screenshots, traces, and product health reporting can be connected within a single quality model. This makes the process of creating, running, and understanding tests as seamless as possible without sacrificing the depth needed to identify genuine product risks. The broader point was that, as software delivery becomes increasingly agentic, quality assurance must evolve alongside it. Testing cannot remain a slow, disconnected stage at the end of development. It needs to become an integrated and equally agentic part of how software is built and delivered.

- Event context: AI Tinkerers Islamabad - July 18, 2026 — 2026-07-18 — Islamabad Rawalpindi
- Public talk page: https://islamabad-rawalpindi.aitinkerers.org/talks/rsvp_L3a9baolTt0

### [Inhabited-design: an adversarial-persona Claude Code skill that produces delightful AI design (not slop)](https://seattle.aitinkerers.org/talks/rsvp_r_8j0_bmQOg)

Inhabited-design is a Claude Code skill that fights the AI Slop problem: the purple gradients, 3 column CTAs, rounded buttons. It turns "build me an X for Y" into a delightful design with unique UI that actually has a personality. Instead of one-shotting that, the skill samples a different real designer to inhabit on every run. So an energy drink for finance bros came back as Peter Zumthor with actual references, then critiques its own work in the voice of another inhabited critic: Tanner, the 26 year old investment banker living in midtown. The skill uses two established techniques, verbalized sampling (https://arxiv.org/abs/2510.01171) and Intent Factored Generation (https://arxiv.org/abs/2506.09659) to coax the model out the same old design attractors that are models often gets trapped in when designing content. Burns a silly number of tokens. Turns out unique design is expensive. Code: github.com/Shimin-Zhang/inhabited-design

- Event context: AI Dev Tools Track - Seattle - June 8 — 2026-06-09 — Seattle
- Public talk page: https://seattle.aitinkerers.org/talks/rsvp_r_8j0_bmQOg

### [MARSYS: Multi-Agent Workflows Without the Plumbing](https://lausanne.aitinkerers.org/talks/rsvp_eigQG2pH8qI)

MARSYS is an open-source Python framework for building multi-agent workflows. Define your agents and who talks to who -- the framework handles parallel execution, branch isolation, convergence, context management, and routing automatically. It works with 7+ LLM providers out of the box (OpenAI, Anthropic, Google, local models), ships with ready-to-use agents (browser, file operations, code executor, data analyst), and lets you fine-tune local models directly from execution traces. `pip install marsys` and you're running.

- Event context: AI Tinkerers Lausanne April 2026 Meetup — 2026-04-30 — Lausanne
- Public talk page: https://lausanne.aitinkerers.org/talks/rsvp_eigQG2pH8qI

### [From Messy Inputs to Reliable Community Data: Human-in-the-Loop AI](https://denver-boulder.aitinkerers.org/talks/rsvp_EuM3A-aBwJ4)

I built Colorado Songwriters Collective, a human-in-the-loop AI workflow that converts messy event/member inputs (DMs, forms, and web pages) into structured, publish-ready community data. In the demo, I’ll show the ingestion pipeline, review checkpoints, and how we keep updates accurate before they go live.

- Event context: AI Tinkerers Denver - April Meeting — 2026-04-27 — Denver
- Public talk page: https://denver-boulder.aitinkerers.org/talks/rsvp_EuM3A-aBwJ4

### [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

### [Building a Real-Time Terminal Messenger on LinkedIn's Private APIs with Bun, Ink, and a Git-Backed Message Store](https://seattle.aitinkerers.org/talks/rsvp_0AqXN-gxTTM)

Allman is a two-layer system for LinkedIn messaging from the terminal: a CLI that syncs, sends, and streams LinkedIn messages into a git-versioned file store, and a TUI that renders it as a full two-pane Ink/React terminal messenger with live updates, auto-backfill, and real-time presence. The demo shows the TUI in action — navigating conversations, composing replies, watching the status bar update as messages stream in over LinkedIn's SSE channel, and kicking off a sync that backfills an entire conversation history while showing live progress counts. Under the hood, the TUI never touches the network directly. Every write — sends, syncs, searches — shells out to the lilac binary, which is embedded inside the compiled TUI executable as a bundled asset. Every read — conversation list, message thread, slug lookup — goes straight to JSONL files on disk, so navigation is instant with zero subprocess overhead per keystroke. The key learning or takeaway is that private APIs, even when obfuscated, are easily reverse-engineered by coding harnesses. Claude Opus 4.6 processed the compiled LinkedIn binary overnight, completely autonomously.

- Event context: AI Tinkerers Seattle: GTM Engineering — April Meetup — 2026-04-23 — Seattle
- Public talk page: https://seattle.aitinkerers.org/talks/rsvp_0AqXN-gxTTM

### [From Chat to CASE: Building an AI Agent That Scouts and Fills Real Complaint Forms](https://singapore.aitinkerers.org/talks/rsvp_y-Gl78fWqSw)

I built Onestop, a chat-first complaint agent that turns a user’s issue into an execution workflow: it extracts the complaint from natural language, plans the escalation path, drafts the complaint email, and for verified portals like CASE Singapore, scouts the live web form and attempts a browser fill through a Form Genome pipeline. The demo is intentionally technical and code-first: a FastAPI orchestrator, structured complaint state, Playwright-based browser execution, and truthful fallbacks when a route is not production-safe.

- Event context: AI Tinkerers Singapore: The Agentic Future & Dev/Eng Workflows — 2026-04-21 — Singapore
- Public talk page: https://singapore.aitinkerers.org/talks/rsvp_y-Gl78fWqSw

### [Openclaw for token-efficient business needs](https://ho-chi-minh-city.aitinkerers.org/talks/rsvp_gbkGqEbMvy8)

I built flowser, a platform that enable non-technical users to use openclaw easily with built-in integrations, security, and real life business workflows.

- 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_gbkGqEbMvy8

### [Boomerang: why I built my own agentic browser infra](https://cologne.aitinkerers.org/talks/rsvp_XEuIAGK7fdA)

I built a replacement for browserbase, notte, firecrawl and the many other agentic web-use browser infra providers. I walk through the story of trying out various systems, then deciding to build my own, the trials and tribulations of battling cloudflare, how agents go wrong, and more.

- Event context: AI Tinkerers Cologne 4: Live Technical Demos — 2026-04-16 — Cologne
- Public talk page: https://cologne.aitinkerers.org/talks/rsvp_XEuIAGK7fdA

### [Building an end-to-end agentic coding workflow in sandbox](https://seattle.aitinkerers.org/talks/rsvp_A0CI_bsvMlY)

I’ll do a live technical walkthrough of an AI-assisted developer workflow that turns a task into code changes, tests, and a PR-ready diff. I’ll show the actual implementation: task orchestration, sandboxed execution, tool-calling, retry/failure handling, and human-in-the-loop checkpoints. This is a code-only demo (no slides), including what broke, what was hacked together, and what made the workflow reliable enough for daily use.

- Event context: AI Dev Tool Track — Seattle Meetup - April 13th, 2026 — 2026-04-14 — Seattle
- Public talk page: https://seattle.aitinkerers.org/talks/rsvp_A0CI_bsvMlY

### [Playwright MCP vs CLI? Benchmarking for performance & effectiveness](https://denver-boulder.aitinkerers.org/talks/rsvp_ZkszEZey4aY)

I benchmarked an agent using Playwright MCP vs Playwright CLI vs agent-browser. The CLIs were much more context efficient, but they were--surprisingly--also much slower! I dug into why that might be and the answer came down to tool calls, which turned out to be driven directly from the interface designs of each tool. The MCP used up a lot of the context window by returning all state information on every run. The CLI and agent-browser both returned much less information, leaving it up to the agent to directly query the information it needed. That meant less of the context window was used, but more tool calls were required and tool calls were the most direct corollary to timing. The biggest surprises were that context efficient != faster, and it _also_ didn't mean cheaper. ![](https://outpost.ranger.net/_astro/2-runtime-dots.RG7TW8g3_1jz1a2.webp) ![](https://outpost.ranger.net/_astro/6-tool-call-type-bars.CD3GEom5_Z2lR38P.webp) ![](https://outpost.ranger.net/_astro/9-cost-slope.CQX0e7Dr_1twtqz.webp)

- Event context: AI Tinkerers Denver Meetup - March 25, 2026 — 2026-03-25 — Denver
- Public talk page: https://denver-boulder.aitinkerers.org/talks/rsvp_ZkszEZey4aY

### [Eliminating Waste in the AI Augmented SDLC](https://nashville.aitinkerers.org/talks/rsvp_uMKhslYmRfU)

When AI can use the same tools you use - Jira, GitHub, Sentry - the bottleneck in software development shifts from writing code to everything around the code. I applied lean manufacturing principles (Toyota Production System) to my own AI-augmented workflow and systematically removed entire categories of waste: manual ticket management, error triage, deployment monitoring, and ambiguous specifications that lead to expensive rework. I’ll walk through the specific patterns - MCP tool handoff, Gherkin specs as agent contracts, pre-flight checklists derived from PR review audits - and show how each elimination is permanent and reveals the next layer.

- Event context: AI Tinkerers Nashville – Software Development in the Age of AI — 2026-03-25 — Nashville
- Public talk page: https://nashville.aitinkerers.org/talks/rsvp_uMKhslYmRfU

### [Getting UI Agents to run reliably in enterprise environments](https://bremen.aitinkerers.org/talks/rsvp_QBsx2rF5lCQ)

We built a system that enables you to run agents in secure sandboxes with security policies and easily monitor/evaluate their progress. The demo shows this along the path of work inside a claims processing task.

- Event context: AI Tinkerers Bremen — 2026-03-25 — Bremen
- Public talk page: https://bremen.aitinkerers.org/talks/rsvp_QBsx2rF5lCQ

### [Flexible RPA with Playwright MCP and Deep Agents](https://columbus.aitinkerers.org/talks/rsvp_gJn6jUGLYFQ)

How do we build RPA that doesn't take more time fixing it, than writing it? By using LLMs! Let me show you how I built out sessionized, distinct, parallelisable RPA process using pydantic deep-agents, the Playwright MCP, and a little bit of creativity to take web automation to the next level!

- Event context: AI Tinkerers - Columbus March Meetup — 2026-03-02 — Columbus
- Public talk page: https://columbus.aitinkerers.org/talks/rsvp_gJn6jUGLYFQ

### [From Screenshot to Code: AI-Powered Design Cloning and Verification](https://nyc.aitinkerers.org/talks/rsvp_oSYfxCynLls)

Live demo of an AI pipeline I made that takes any website URL and recreates it in an editable sandbox. The system: 1. Captures a live site using Playwright (screenshots, DOM, styles) 2. Uses Claude to analyze the design and generate a React clone 3. Creates an instant editable sandbox with the cloned site 4. Verifies the clone matches the original using design contracts 5. Suggests and applies CSS fixes for any differences I'll show the full loop: paste a URL → AI analyzes it → generates code → live preview appears → iterate with chat to refine. No Figma access needed, no manual coding - just point at any site and get an editable clone.

- Event context: Feb Demo Day: How are you turning design into code? (with Baz) — 2026-02-04 — New York City
- Public talk page: https://nyc.aitinkerers.org/talks/rsvp_oSYfxCynLls

### [Let AI Agents Dogfood Their Code With WebMCP](https://seattle.aitinkerers.org/talks/rsvp_vfxXvJAND7k)

I wrote a fork of the chrome dev tool MCP server that treats the CDP websocket as an MCP transport layer. This allows to coding agents to call WebMCP tools embedded in web applications. If you want Claude code to test a functionality it just wrote on your web app, it has to take screenshots and simulate clicks. However, with WebMCP, the model can leave tools for itself in the front end code that it can then call via MCP proxy. This is up to 90% more token efficient and considerably faster for the agentic development feedback loop. (More info in the repo readme)

- Event context: AI Tinkerers Seattle Meetup: Dev Tools Track — January 12th, 2026 — 2026-01-13 — Seattle
- Public talk page: https://seattle.aitinkerers.org/talks/rsvp_vfxXvJAND7k

### [Giving Agents Eyes & Hands](https://tel-aviv.aitinkerers.org/talks/rsvp_SPmhgz5QYTE)

Code review today is blind to intent. It can see diffs, but not whether an implementation actually matches the product spec, design, or real user behavior. This talk introduces Spec Reviewer, an AI code-review agent that gives agents eyes and hands. The agent collects requirements from tickets (Jira, Linear etc) and designs (Figma), maps them into a contract, then spawns AI agents which manipulate isolated browser session to interact with the preview environment and validate each requirement end-to-end. The agent then provides clear feedback, pinned to the exact code paths responsible, with screenshots from the agent’s sandboxes session showing what it observed.

- Event context: AI Tinkerers Tel Aviv: End of Year Demo Party (feat AI21, CopilotKit, MCP-UI, and more!) — 2025-12-23 — Tel Aviv
- Public talk page: https://tel-aviv.aitinkerers.org/talks/rsvp_SPmhgz5QYTE

### [Claude Draws (/ how to automate Claude for Chrome)](https://sf.aitinkerers.org/talks/rsvp_zvyMJwwAAEI)

Claude Draws is an interactive community art project which challenges Claude to bring your idea to life using the hottest graphic design software from 1989, Kid Pix. I'll give a live demo of Claude Draws, built on top of the Claude for Chrome research preview. I'll also talk about how I built Claude Draws, some best practices for building browser agents, and a few lessons I learned along the way.

- Event context: Agents in Production: Human in the Loop Orchestration w/ Temporal — 2025-10-17 — San Francisco
- Public talk page: https://sf.aitinkerers.org/talks/rsvp_zvyMJwwAAEI

### [How to lose in fantasy football (A tutorial for programmers)](https://nyc.aitinkerers.org/talks/rsvp_wIsF1SMces8)

I'll be presenting a full-stack MCP application that enables Claude to autonomously manage ESPN Fantasy Football teams through natural conversation. This system demonstrates advanced MCP patterns including real-time tool execution monitoring, optimized context management (achieving 77% faster response times through static week context injection), and comprehensive API integration (36 specialized tools spanning roster management, trade proposals, waiver claims, and live player analytics). The live demo will showcase Claude analyzing rosters, making lineup decisions, and executing transactions against real ESPN leagues—illustrating the end-to-end workflow from user query to API write operations.

- Event context: NYC October Demo Day — 2025-10-02 — New York City
- Public talk page: https://nyc.aitinkerers.org/talks/rsvp_wIsF1SMces8

### [AI that edits your resume](https://seattle.aitinkerers.org/talks/rsvp_HGAE1liMtbc)

I'll be presenting a resume builder with human-in-the-loop editing that works like Cursor for your resume. The demo walks through the complete workflow from job scraping and resume import to targeted edits and user approval. I'll show how conflict-free AI suggestions get generated with streaming tool-calls and updates the UI. The interface gives users close control with "preview before apply" edits so you can finalize your draft exactly how you want.

- Event context: Friday - AI Tinkerers Seattle - May Meetup — 2025-05-31 — Seattle
- Public talk page: https://seattle.aitinkerers.org/talks/rsvp_HGAE1liMtbc

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