Slipway

The idea

Slipway is a cron-driven idea producer and orchestrator. On a schedule it watches what’s new — recent tech releases, what people are building, trending work — and combines that with the user’s personal context to surface software it thinks is worth building. It doesn’t just list ideas; it rates them, and for the ones the user approves it orchestrates a virtual dev team to actually build them.

The thesis is simple: idea quality = public signals (what’s new, what’s trending) × personal context (real friction, what you actually need). Grounding ideas in both is how you get combinations that are novel and useful, instead of generic AI slop.

The real differentiator: verification

The orchestration widget is the part everyone is racing to build, and it’s commoditizing fast. The defensible part of Slipway is the verification layer — and that’s the part I’m uniquely positioned to build, because it comes directly out of my year working as a QA / integration engineer on a real production system.

The research bears this out: AI coding agents do real work but are systematically overconfident and can’t certify their own “done.” Trust, not raw capability, is what gates adoption — most teams pilot agents but very few actually ship their output. So Slipway is built around a hard rule: never auto-ship. Every unit of work has to pass through a gate before a human sees it.

That gate produces a Proof of Work — a signed, reviewable bundle that answers one question: did the agent do what it claimed, correctly, and can I verify that without redoing it? It packages the raw test output, the exact diff, labeled before/after screenshots of the behavior that was exercised, the commands the agent actually ran with exit codes, independent check results, and provenance (model, prompt hash, git SHA) — so a reviewer can say yes fast, drift gets caught before it ships, and the whole thing survives later as an audit trail.

Full visibility into the dev team

Because I think in terms of DevOps and QA, Slipway is built so you can see the progress of a virtual dev team at every level — from the high-level agile board and backlog across many projects in parallel, down to the per-task proof of what was built and whether it passed its gate. Progress isn’t a vibe; it’s evidence you can inspect.

The long game

The verification layer is designed to stand on its own. The ambition: get it to enterprise grade and offer it as the trust/verification substrate other systems plug into — the logging, proof, and verification gate for AI-built software when a team doesn’t have its own. The pipeline that builds products becomes the standard for proving that AI-built work is actually correct and safe to ship.

Where it is now

Planning and design stage — the architecture, the verification-gate design, and the Proof-of-Work artifact format are specced out (grounded in a full research pass on agent autonomy and where humans must stay in the loop). The honest status: the concept and the verification design are real and detailed; the build is next.