Opportunity area · theme founders discuss · intermediate

Distribution approach for don see

Distribution · Don see: partnerships with the tool people already open beat hoping an algorithm loves your launch post. Reject “for everyone in ai ml.” Original insight: threads optimize for cleverness; products optimize for repeated completion.

Problem

bootstrappers watching runway describe the same loop: notice the mess late, patch it manually, promise a system later, repeat next month. Unexpected challenge: support load rises when it works—users shove messier edge cases into the pipe. Hidden cost: rewriting the offer every week instead of iterating the same wedge.

Target user

Builders with domain scars related to “don see”

Proposed solution

Run a concierge cohort first. Deliver the result manually, log every exception, automate only what repeated three times. Distribution rule: track conversations started and pilots dated, not impressions. Counter-intuitive advice: a supervised correct workflow beats a flashy autonomous demo that needs babysitting. Distribution bottleneck: content without a next step becomes a magazine. End with a pilot CTA or a useful template. One caution: shipping unreliable automation in a trust-sensitive job burns the only channel that mattered. One recommendation: ship a concierge version, log exceptions, automate only the repeats. Practical next step: sketch trigger → mess → your path → proof. If proof is vague, you still have a vibe. Real-world pattern: Stripe won by removing friction on a job merchants already had—copy the posture, not the category. Straight take: one paid pilot beats a polished multi-feature build with zero distribution reps.