45 Meaningful Comments In: What I Learned About Distribution on Indie Hackers
I started intentionally engaging on Indie Hackers about 6 weeks ago with one goal: understand what actually moves the needle for indie founders.
After 45 substantive comments on posts I genuinely connected with, here's what stood out:
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Distribution beats product. Multiple founders built great things, got zero sales due to visibility. Jack Builds went from $0 to paying customers by building in public on Twitter. Same code, different reach.
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Customer pain beats features. The winners weren't chasing "cool" - they were solving real business headaches. Jordan's multi-channel inventory sync exists because small sellers lose money when stock goes out of sync across channels.
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AI gives confident wrong answers. Dave's ChatGPT pivoted him from narrow to broad to narrow again - each with total conviction. Market feedback beats any strategy framework.
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Specificity converts. South African sellers. Freelancers billing clients. People losing money on inventory. When you know exactly who suffers, everything clicks.
The real MVP isn't the code. It's finding people who have been waiting for someone to solve their specific problem.
I'm not there yet, but watching 45 different founder journeys taught me more than any playbook could.
Forty-five comments are a useful learning set, but they are selected for stories that attracted discussion. Tag each one by the next observable step: reply, conversation, trial, paid, or no movement, then revisit after 30 days. Distribution creates evidence only when engagement is connected to behavior; otherwise you learn what gets comments.
I like that your takeaway wasn't "distribution matters"—it was why.
The pattern across those founders seems to be that distribution doesn't just create customers. It creates the evidence that tells you which parts of the product actually deserve to exist.
Exactly - you've hit on something that kept showing up in those 45 comments. The data comes from distribution, not before it. Dave's journey with ChatGPT is the perfect example - he had no idea what the market actually wanted until he got real feedback from real people using it in public.
Watching Jack and Jordan build in public, the product roadmap basically got written by the community response. That's the leverage I missed for years.
I'm glad it resonated.
Reading your reply gave me one thought about the kind of evidence distribution creates—and, just as importantly, the kind it doesn't. I'd rather explain it in the context of those examples than try to compress it into a thread.
If you're interested, what's the best email to reach you on?