yOptions — meta self-audit
We ran yOptions through yOptions. Same product, two goal profiles, two honest verdicts.
Idea Forge — a $29 honest-verdict consumer AI service for solo founders. The wedge: ChatGPT cheerleads, friends won't tell the truth, Reddit has no signal. Founders submit an idea and receive one cited verdict — confidence number, flip-conditions, real fetched competitor pricing pages, hard questions, and a goal-aware rubric (lifestyle vs. venture vs. replacement-income). The brand promise is honesty under fire, demonstrated through a published eval harness, visible system prompts, and citation receipts. Currently calibration mode (operator writes verdicts manually); planning Tier 2 with real LLM, then Vercel AI Gateway for multi-model resilience. Built solo by Derek Johnson at Ekow Solutions Group.
Two rubrics. Two verdicts.
The audit didn't change its mind. It answered a different question.
Could this be a fundable, scaling business?
Could one person at <10h/week reach $1–5k/month?
Same facts. Inverted signal weights. The audit doesn't reconsider the evidence — it reweights it. What counts as a positive signal under one rubric can be a fatal negative under the other:
- Small TAMconcern (no path to scale)fine (only ~100 customers needed at $20/mo)
- No moatconcern (incumbents will copy)fine (organic discovery + niche knowledge IS the moat)
- 6–12 month sales cycleacceptable for B2B SaaSfatal (no revenue within time budget)
- Ops linear to revenuefixable with team at scalefatal (no time budget for support)
- Security-review burdenamortize over many customersfatal (same friction at any scale)
Why this matters for honesty. A single-rubric service that defaults to venture framing would tell a stay-at-home parent or a side-hustler that their idea has “no moat” or “small TAM” — technically correct, but irrelevant to their actual goal. That's being right inside the wrong question. We'd rather ask the question first.