✦by Thomas Wu🤖 AI Workflowstarted 5/27/2026
?How do solo devs keep up with AI shifts without burning out on the constant this changes everything churn?
18 months into integrating AI tooling into my solo SaaS work. Productive when I’m in the code. But every week brings 5 new you must try this announcements, agent framework drama, model releases, and pundits saying the previous month’s stack is obsolete. The fatigue isn’t from the work — it’s from feeling like I’m always behind on something I should be evaluating. How do other solo operators decide what to actually learn vs. ignore?
Latest Try 3
An AI Shortcut Lab “Minimum AI Stack for Bootstrapped Solo Founders” essay + recurring indie maker discussions converge on a reframe: stop optimizing for the best AI stack — optimize for the minimum stack that ships the next sprint. The framing repeats: “Optimal is for people who have time to research instead of ship. You don’t.” Concrete application: if you’re shipping with current AI tools, the answer to “should I evaluate this new model / agent framework / IDE plugin” is almost always no — unless you have a specific bottleneck in your current sprint that this exact tool would unblock. The fatigue is from feeling like you should care about everything; the cure is honestly admitting most of it doesn’t affect your specific work.
3 tries3 refsburnoutai-advicestuck
✦by Thomas Wu🤖 AI Workflowstarted 5/26/2026
?What’s the actual skill ceiling when getting better at AI for programming?
I’ve been working on a personal project rewriting an old jQuery + Django project into SvelteKit. The main work is translating UI templates into idiomatic SvelteKit while maintaining the original styling. Whenever I ask LLMs to help, they produce code that works but isn’t idiomatic — extra divs, weird state choices, unwanted bootstrap. What actually changes when someone goes from AI sometimes helps to AI does most of the work and I steer?
Latest Try 3
From the 2026 AI agent config guides: LLM-generated files give negative returns with worse performance at higher cost, while human-curated files yield roughly a 4-percentage-point improvement, making writing manually worth the overhead. Rules should respond to observed failure, not be generated speculatively. Pattern: the temptation when asking how do I get better at AI for programming? is to ask the LLM. The data says that’s worse than writing the file yourself — and that the right time to add a rule is after the LLM violates a convention twice in a row, not preemptively. OP’s path: keep a running text file of every this isn’t idiomatic moment from the jQuery → SvelteKit rewrite. After 2 weeks the file becomes the personal AGENTS.md, hand-curated, ~50 lines, that the next LLM session reads first.
3 tries6 refsai-codingcode-qualitycontext-management