AISTAB — Mission-to-Evidence Agent Execution System

Inspiration Founders increasingly work with multiple AI tools and agents, but the hard part was never generating more output. The hard part is turning an ambiguous goal into coordinated work, keeping ownership clear, reviewing the result independently, and proving what actually happened — without leaking private context along the way. We wanted a system where the agent that does the work is never the one that grades it.

What it does AISTAB turns a founder's goal into coordinated agent execution, independent review, and an evidence-backed result. It runs a Mission-to-Evidence flow:

Mission → Intake → Plan → Routing → Execution → Review → Evidence → Accepted Result → Notification.

In the Build Week demo, one mission (launching an AIDGART reference pack) is captured, decomposed into workstreams, routed across specialist agent roles, executed into a real artifact, checked through an independent review gate, connected to evidence, and returned as a human-gated accepted result. Pricing, cover art approval, and publishing stay strictly human-only.

How we built it AISTAB is an adapter/read layer over an existing multi-agent operations system that already runs founder operations, trading analysis, and a visual-intelligence commerce pipeline (AIDGART). For Build Week we consolidated that runtime into one judge-testable product slice:

a replay-safe Mission-to-Evidence runner (build_week/demo/run_mission_to_evidence.py); a canonical, reproducible evidence run (two consecutive runs under 100s); an evidence chain (E-01..E-14) tying every claim to a path, timestamp, and proof statement; a Claude independent review gate with a real PASS/FIX/REJECT trail; a public, no-login demo at getaistab.com/demo/; a claims ledger and privacy/security guardrails. Codex acted as execution lead: it built the runner, generated the evidence files, fixed review gaps, and deployed the landing to Cloudflare Pages. Claude acted as the independent review/acceptance gate — the same separation of roles the product itself demonstrates.

Challenges we ran into The first canonical demo run was too weak to be convincing — an empty artifact and a self-referential mission. We rebuilt it around a real, verifiable business mission (an AIDGART reference-pack launch) with a real 2-page artifact, and made the review gate demonstrate something concrete: the draft contained one unsupported claim ("bestselling style pack"); the review step caught it, rejected it, and Codex fixed the wording to "curated style pack" before acceptance. That single before/after is now the core proof point of the whole demo.

Accomplishments that we're proud of A judge can watch the exact same mission run twice from a clean terminal, inspect the draft-vs-reviewed-vs-final files directly, and then open the same result on a public URL with no setup and no login — no staged screenshots, just an inspectable run.

What we learned Review has to produce an artifact, not just a verdict. A single caught claim, preserved in the run's own files, is more convincing evidence of "independent review" than any amount of description of the process.

What's next for AISTAB Extending the same Mission-to-Evidence pattern to more of AISTAB's existing operating surfaces (trading analysis, commerce operations), and turning the evidence chain into a reusable acceptance-gate pattern other founder-led teams can adopt for their own agent workflows.