About

Michael Woodworth

I'm an engineering executive and founder in Toronto. I've spent more than 15 years building software, from cloud SaaS and ML platforms to the systems that run a factory floor.

The short version

I was the technical co-founder of Upverter (Y Combinator W11), one of three founders. Upverter was a cloud-based hardware design tool for PCB and circuit schematics. We built the company over about six and a half years and sold it to Altium in 2017, and I stayed on as VP of Product for the Upverter line.

After that I spent nearly four years at SRTX (Sheertex) as their top technical executive, effectively the CTO. I led a 46-person technology organization across software, automation engineering, material science, and IT. I architected Cortex, a complete rewrite of the factory's earlier system, and built it with my team. It became the company's system of record for production control, real-time machine data, ML quality inspection, and ERP. When we brought material production in-house, Cortex connected and automated that too.

Since leaving SRTX I've been building AI products under Lunoa Labs. Headless HQ is an agent platform for business operations. It shipped first as campaign management across the Meta, Google, and TikTok APIs with LLM-powered creative analysis. An HQ agent routes work to specialist teams, and marketing and M&A diligence are the deepest so far. PageWeaver makes personalized children's storybooks and prints them as softcover or hardcover books. Get Indexed tracks how often ChatGPT, Claude, Gemini, and Perplexity cite a brand.

These are build-and-learn projects, not a venture studio. I'm the only engineer on all three, which is the point: I wanted to know what one person can actually ship now that the tooling has changed, and I'd rather test that against real products with real users than argue about it in the abstract. Nearly four years of factory software taught me not to trust a thesis that hasn't survived production.

I also care about manufacturing and innovation in Canada. My time at Sheertex showed me how much potential there is.

Building independently has been the right way to spend this year. It isn't a permanent plan. I'm open to a full-time CTO, VP Engineering, or Head of AI role at a company where the hard part is genuinely technical and the mandate to solve it is real. It's the kind of seat I held at SRTX as its top technical executive, and the one I'd take again for the right team. Get in touch.

How I work

Product and engineering are one job

I've owned both sides. I led sales at Upverter for a year, ran product for the Upverter line at Altium, and built Cortex alongside the people running the factory. The fastest way to waste an engineering team is to point it at a problem nobody has, so I find the problem first, then build the smallest thing that tests the answer.

Shipped means it works in production

A demo isn't finished software. Cortex ran a live factory, so we shipped weekly and timed hotfixes around production. I hold AI products to the same bar: tested, reviewed, and behind approval limits the customer controls before anything touches real money or data.

I build the team, then get out of its way

At SRTX I grew the software team from 2 to 9, added a product owner and a project manager, and promoted an engineer into a lead role. I stay close to the code so I know what good looks like, and I measure myself by how well the team runs when I'm not in the room.

I say what I think, then I commit

I'd rather raise a disagreement early than discover it in production. Once the team makes the call, I'm all in on it, and I'd rather be corrected than agreed with.

Technical depth

Physical World

  • Manufacturing and factory automation
  • Machine data integration
  • ERP
  • Electronic design automation (EDA)
  • Advanced materials

Software

  • Python, FastAPI
  • TypeScript, Next.js
  • Postgres, pgvector, Redis
  • GCP, AWS, Terraform
  • Real-time data pipelines

AI & Agents

  • Multi-agent systems
  • LLM routing across Anthropic, OpenAI, and Google
  • Evaluation and adversarial validation
  • AI coding agents and review process
  • Computer vision in production