Sell rubric-based LLM evaluation as a productized service to content teams that need audit-proof quality scores for AI-generated copy.

Customer: Solo or small-team content ops manager at a 10-50 person DTC or SaaS company who ships 50-200 AI-generated pieces per month (product descriptions, email copy, blog posts) and is being asked by their CMO to prove quality isn’t slipping as they scale with AI.

Problem: They’re eyeballing AI output or running one-off vibes checks. There’s no repeatable, defensible way to say ‘this batch of 80 product descriptions met our quality bar’—so every review cycle is manual, inconsistent, and undocumented.

Pricing: saas-mrr — $800 MRR in 4 months (8 customers at $99/mo on a 500-eval/month plan)

Why now

The cluster signals that even researchers can’t agree on how to evaluate creative/subjective outputs—which means practitioners have zero off-the-shelf tools. The gap between ‘we use AI for content’ and ‘we can prove AI content is good’ is widening as AI content volume explodes in 2025-2026, making any credible scoring layer immediately valuable.

Go-to-market

1. Post a free ‘rubric starter kit’ (5 pre-built rubrics for email copy, product descriptions, blog intros, ad headlines, social posts) on r/ChatGPTPromptEngineering and relevant Slack communities—collect emails in exchange for the download.
2. DM 20 content ops people on LinkedIn who post about AI content workflows; offer a free 30-eval audit of their existing AI output using your tool in exchange for a 20-minute feedback call.
3. Write one specific teardown post (‘We scored 100 AI product descriptions with a rubric—here’s what failed most’) and publish on Substack + cross-post to Indie Hackers to drive SEO and credibility.
4. Offer the first 10 paying customers a ‘custom rubric setup’ session (1 hour async Loom + Notion doc) as a white-glove onboarding hook to reduce churn and gather testimonials.

Moat (or lack thereof)

No meaningful moat. Any developer can call the Anthropic API with a rubric prompt. The defensibility is entirely operational: your pre-built rubric library, the UX for non-technical content managers, and the human-vs-LLM divergence reporting (which is genuinely novel as a feature). First-mover advantage is thin—focus on distribution and niche positioning, not technology.