Automated AI safety debate verdicts as a hosted API for teams shipping agentic products without red-team budgets.

Customer: Solo founder or 2-person team building an LLM-powered agent product (e.g. a browser automation SaaS, an AI coding assistant, or an autonomous outreach tool) who has reached ~100 beta users, is fielding safety/compliance questions from early enterprise prospects, and cannot afford a $15k/month red-team engagement.

Problem: When enterprise buyers ask ‘how do you evaluate whether your agent does something unsafe?’, indie AI founders have no credible answer — manual spot-checking doesn’t scale and formal red-teaming is priced for Series B companies. They ship anyway and hope nothing blows up, which kills deals and creates liability.

Pricing: saas-mrr — $800 MRR in 4 months (8 customers at $99/mo)

Why now

The Claude claude-sonnet-4-5 model tier makes running two-agent debate loops cheap enough (~$0.002/verdict) that the margin works at indie pricing. Enterprise procurement teams started asking for AI safety audit logs in 2025 as agentic products hit regulated verticals — the demand signal is brand new but the tooling isn’t.

Go-to-market

1. Post a detailed teardown on the r/LocalLLaMA and Hacker News ‘Show HN’ of a real debate transcript catching a PII-exfiltration edge case — link to a free 50-verdict trial, no credit card. Harvest emails from signups.
2. DM 20 founders in the ‘AI Agents’ and ‘LLM Apps’ Slack/Discord communities (e.g. Latent Space Discord, AI Tinkerers) who are actively selling to enterprise — offer a free ‘safety audit report’ of their agent in exchange for a 30-min call and a testimonial.
3. Ship a GitHub Action wrapper so teams can run verdicts in CI on every agent behavior change — open-source the action, gate the API behind a paid key. This turns every star into a top-of-funnel lead.
4. Write one cold email sequence targeting CTOs of 50-250 person SaaS companies whose job postings mention ‘AI agents’ — lead with the compliance angle (‘your enterprise prospects will ask for this’), not the tech.

Moat (or lack thereof)

No meaningful moat. Any team with Claude API access can replicate the debate loop in a weekend. The only durable advantages are: (1) a corpus of labeled verdicts that trains a faster/cheaper classifier over time, and (2) brand trust built by being first to publish real-world safety case studies. Neither is defensible against a well-funded competitor. That’s fine — the goal is to reach $5k MRR and either grow into a platform or get acqui-hired by a safety tooling company before the market consolidates.