# OpenSpec Projects at AI Tinkerers

> Canonical HTML: https://aitinkerers.org/technologies/openspec
> Markdown URL: https://aitinkerers.org/technologies/openspec.md
> Technology record last updated: 2026-03-28T09:24:48Z
> Generated: 2026-09-20T22:34:56Z

OpenSpec is an open-source standard for defining hardware interface specifications through machine-readable YAML files.

OpenSpec eliminates manual documentation bottlenecks by converting hardware registers and memory maps into actionable code. By utilizing a unified YAML schema, teams generate C headers, Python drivers, and RTL logic directly from a single source of truth. It supports complex bitfield mappings and nested address spaces (ideal for FPGA and SoC development) to ensure hardware and software teams remain perfectly synchronized throughout the silicon lifecycle.

- Official technology site: https://openspec.org
- Public AI Tinkerers demos and talks: 2
- Result page: 1 of 1

## Recent Public Talks and Demos

### [Self-healing and self-driving product](https://boston.aitinkerers.org/talks/rsvp_yNLFxyhExLs)

At PostHog, we use recurring agentic loops to help nearly twenty SDKs behave like one product. Each loop handles a focused job, and its output becomes input for another loop. Together, they form a small agentic economy that makes the system self-healing. Accepted changes to either the product or its specification feed back through the loops, keeping shared requirements and all affected SDKs aligned. One loop audits accepted code changes and proposes specification updates. Another audits SDK code against the specification and writes compliance reports. A third audits those reports and proposes code changes. All of their work is version-controlled, so each run can start fresh. Humans review the proposals and decide what ships. PostHog's self-driving agents turn product signals into proposed fixes. The self-healing system asks what happens after those fixes are accepted: what should the rest of the product learn? Through the core architecture and real world examples, I show a reusable pattern for keeping intended behavior and reality aligned.

- Event context: Back from Summer: AI GTM Builders — 2026-09-03 — Boston
- Public talk page: https://boston.aitinkerers.org/talks/rsvp_yNLFxyhExLs

### [Adventures in Dark Software Factories and Building Sundai Claw](https://boston.aitinkerers.org/talks/rsvp_rYByyNllwL4)

I will share my adventures trying to build a software factory, and a solution that I landed on that I'm pretty happy with. It's a rapidly evolving space and it seems like every week there's a new project attempting to streamline the process of building software using autonomous AI coding agents. If you've read Dan Shapiro's "The Five Levels" post (https://www.danshapiro.com/blog/2026/01/the-five-levels-from-spicy-autocomplete-to-the-software-factory/), you know about the Fanuc Dark Factory, the robot factory staffed by robots. It's dark because it's a place humans are neither needed nor welcome. As an example of how such a factory can be built, I'll share a concrete use case in building Sundai Claw. Sundai Claw is an OpenClaw agent that you can message via Telegram. You describe your software project in natural language and when you submit a request, the claw agent dutifully begins to create a Sundai.club project card, a Github repo, a spec doc and then builds and deploys the software. This happens completely autonomously, but we're exploring where appropriate human-in-the-loop steps would be helpful to steer the claw agent and refine the specifications before and during building.

- Event context: AI Tinkerers Boston: March 2026 Meetup — 2026-03-30 — Boston
- Public talk page: https://boston.aitinkerers.org/talks/rsvp_rYByyNllwL4

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