10 LESSONS FROM 112 DAYS OF SHIPPING AN APP
A solo developer documented 112 straight days of building and shipping an app toward a $1M goal and distilled 10 lessons from the process. The focus is sustaini...
A solo developer documented 112 straight days of building and shipping an app toward a $1M goal and distilled 10 lessons from the process. The focus is sustaining daily progress, keeping scope small, and deciding what to ship next to maintain momentum.
It sets a realistic benchmark for how fast small teams can iterate with disciplined workflows.
The habits and feedback loops translate directly to backend and data teams aiming for shorter cycle times.
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Pilot AI assistants on boilerplate backend tasks (API scaffolding, schema migrations, ETL skeletons) and measure time-to-PR and defect rates.
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Add automated evals (unit/property tests, type/SQL checks) to score AI-generated changes and track hallucinations and latency.
Legacy codebase integration strategies...
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Start with AI-assisted PR comments and test generation on a single service to avoid risky auto-commits.
- 02.
Gate AI changes with codeowners and CI quality bars to control dependency churn and build times in monorepos.
Fresh architecture paradigms...
- 01.
Set up an AI-first repo structure (clear modules, templates, prompt examples) and enforce IaC for fast, repeatable envs.
- 02.
Use ephemeral preview environments so AI-suggested changes can be built, tested, and benchmarked safely by default.
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