I woke up one morning in February & had a genuinely uncomfortable realization. AI was now good enough to do a meaningful portion of what I do as a CTO in AI. Not everything, but enough to make me wonder how I could stay relevant over the next year or two. If AI teams can help us discover, evaluate, and deploy AI tools better than I can manually than what is needed to make it easier and safer? What's the Consumer Reports for AI? I couldn't find it, so I started building it. Every weekend since, I've been falling asleep clicking the "Approve" button across Anthropic Claude Code, Cursor, OpenAI Codex, Google Antigravity, and their chat options until I maxed out credits across most of them (sometimes Friday, Sat, and Sunday... And I pay for all of them.). It's built on Microsoft Azure for security. The pain Bad Labels solves: AI adoption fails today for four compounding reasons. ✓ Tools are discovered too late, through reactive search rather than proactive context. ✓ Trust is unclear, with no consistent quality or risk signal. ✓ Billing is opaque, leading to cost surprises. ✓ Contributors like us are unpaid for downstream value. Bad Labels addresses all four.

Bad Labels

Tame the AI frontier. Harness AI & earn while you run.

Tame the AI frontier. Harness AI & earn while you run.