Success Stories
The most useful education in building with AI is watching someone who just did it. Success Stories collects in-depth case studies of SaaS products, web apps, and micro-businesses built with AI assistance — the founder’s story, the tech stack, the real revenue milestones, and the lessons that only show up in hindsight. We dig past the launch tweet into what actually happened: what broke, what they’d do differently, and the specific decisions that compounded. Read enough of these and you start to see the pattern behind the outliers.
How a solo founder built a $14k/month micro-SaaS with AI in five months
No funding, no team, no prior SaaS experience. A breakdown of the product, the stack, the growth, and the three…
Claude Skills, explained: how reusable agent playbooks change AI workflows
Skills let you package a process once and have Claude run it the same way every time. Here’s the mental model, the…
GitHub Weekly Wins: five repos worth starring this week
A local-first agent runtime, a tiny vector store, a terminal LLM client, and two libraries quietly becoming…
The new LLM pricing math: how to cut your API bill without changing models
Token prices dropped again, but the real savings are in routing, caching, and context discipline. A practical…
How to sell AI automation services to local businesses (a starter playbook)
You don’t need a SaaS to earn with AI. Packaging a repeatable automation as a service is the fastest path to real…