FIG 0.1
Specs that compound
Each spec inherits context from the ones beneath it. Your codebase becomes a layered record, not a graveyard of tickets.
A product platform that enables shipping at AI engineering speed.
01 / 05 — Intake
Unstructured customer feedback, bug reports — saved and indexed.
Grouped by intent. Drag to reprioritize.
03 / 05 — Technically Aware
Powerful Product Knowlege Graph behind the scenes.
04 / 05 — Spec & Execute
Acceptance criteria, edge cases, and technical context — generated from signal.
05 / 05 — Track
Every spec auto-syncs status, diffs, tests, and reviews back to the Slack thread that started it. Your team finds out by reading their own channels.
acme/billingCustomer feedback, bug reports, and code changes flow in. Structured specs and sprint plans flow out.
Unstructured data in, structured sprint-ready specs out. Every edge case covered before your engineers start coding.
The cost of building collapsed. The cost of deciding didn't.
The execution layer ate steroids. The decision layer is still on dial-up. Closing that gap is the whole job now.
What stonewall reads, writes, ships, learns.
Each spec inherits context from the ones beneath it. Your codebase becomes a layered record, not a graveyard of tickets.
Stonewall reads your repo as a structured volume — modules on one axis, files on another. Specs reference exact lines.
Spec Writer, Codebase Scanner, Competitor Radar, Sprint Planner — each handles its domain and keeps the others informed.
Signals become specs, specs become commits, commits create new signals. Stonewall makes the loop visible — and short.
Stonewall traces every spec to the exact lines that fulfill it. The AI doesn't describe code — it points at it.
Less time gathering signal, less time clarifying scope, less time chasing status. Each spec ships faster than the last.
Close the loop.