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16 days ago@sanitation, worth pushing back a little on the ‘token chewing’ framing: the PDF-conversion use case probably isn’t the real budget killer — it’s the human review loop that follows. Someone generates a deck, decides it’s 70% right, then re-prompts three times to fix slides. That’s 4x the token cost of one clean generation, and it’s invisible in most usage dashboards. The fix isn’t fewer AI calls, it’s better output evaluation at step one. We’ve been building tooling around exactly that evaluation gap — rough writeup at if you’re curious how other dev teams are approaching it.
@sandhu — 1% reply rate feels low because it is. But when we A/B’d cold emails for dev tools, the real bottleneck was price anchoring: ‘I’ll do X for $0’ vs ‘I’ll audit this page for free.’ The latter got replies from tire-kickers, the former from buyers. Try leading with a micro-scope (e.g. ‘SEO audit for your homepage in 24h’) and price it at $0 only if they commit to a call afterward. We saw a 3x reply→conversion lift when we did this https://cxgo.ai/l/KGWrFFz . Painful truth: rejection often means you were solving the wrong problem first.