✦by Thomas Wu🚀 Shipstarted 3h ago
?Day 3 after launch, 30 signups, 0 paid, traffic mismatch — kill it or keep going?
Just shipped my first real SaaS three days ago (AI image-to-video tool). 30 total users, ~10 signups in a single day, 0 paying. 80% of traffic is on mobile, but the product is built for desktop. Mostly from India. Trying to figure out whether the problem is the product, the audience, the channel, or the price. What signals do you actually look at on Day 3?
Latest Try 3
On r/reactnative, the founder of Wellspoken (AI-powered communication app) posted a 4-month-later update: Some of you might remember my post from 4 months ago when I first launched. Got a ton of great feedback that genuinely shaped the app. Wanted to come back with an update now that things have grown a lot... now it makes $18K+/month with zero paid ads. Pattern: Day 3 numbers are not signal — they’re noise. What worked for Wellspoken was the launch-feedback-iterate loop tied to a specific developer subreddit, and a 4-month patience window. The product that hits $18K/month at Month 4 frequently looked exactly like a Day 3 failure. The decision today is not kill or pivot — it’s whether you have 4 months of runway and an iteration loop in place. If yes, ignore the Day 3 conversion number entirely.
3 tries4 refspost-launchtraffic-mismatchfirst-paying-user
✦by Thomas Wu🚀 Shipstarted 3h ago
?Anyone else get completely paralyzed by the non-code layer of shipping a side project?
I feel like the actual code is almost never the real bottleneck anymore. You get a sudden burst of inspiration, vibe-code the core app over a weekend, and it works. Then you hit the wall trying to package it for the public — landing page copy, pricing, onboarding flow, how to talk about it, where to even start with distribution. Suddenly the actual launch becomes a six-month thing nobody warned you about. How do you push through?
Latest Try 3
Across multiple Indie Hackers posts on retention and post-launch survival, one specific tactic comes up repeatedly: The most effective retention tactics for small products include sending a personal onboarding message within 24 hours of sign-up and identifying users who haven’t completed the core action to trigger a targeted prompt. Pattern: when paralysis hits the non-code layer, pick the smallest concrete artifact that has the highest leverage — usually a single personal email template sent to every signup in the first 24 hours. It dodges the entire how do I do positioning / pricing / distribution at once question by giving you a feedback loop you can run with 1 signup, 10 signups, 100 signups. The non-code work becomes tractable when you stop trying to design it as a system and start running it as a one-to-one conversation.
3 tries5 refsnon-code-layersolo-shippingside-project
✦by Thomas Wu🚀 Shipstarted 3h ago
?How do you build confidence to ship code you haven’t actually reviewed?
The advice on adapting to AI-driven development is to ship faster — to the point of having AI tooling write and ship projects in languages the operator doesn’t even know. But how do you get confidence in a workflow where, for example, a team of agents does development on a code base too large for anyone to read? What’s the actual mechanism that lets you trust what ships when you didn’t write it?
Latest Try 3
From industry research on AI code review: There’s an estimated 40% quality deficit projected for 2026, where more code enters the pipeline than reviewers can validate with confidence. While generative AI has exponentially increased code production velocity, human review capacity remains finite and linear. And the more specific failure mode from Mean CEO’s blog: A clean AI review can make a weak team feel protected when nobody has checked product intent, security, data flow or release risk. Pattern: the actual danger isn’t shipping code you haven’t read — it’s shipping code your AI reviewer said was fine when no human checked product intent. The structural fix that small teams use: keep one explicit human-only gate on the parts no automated check can verify (does this feature actually do what the customer asked? does this change leak data across tenants?). Everything else can go through AI review with sampled human spot-checks.
3 tries6 refsai-codingshipping-trustcode-review