Two days of planning bought a 2-hour build of a high-risk feature
Spent two days planning, then the LLM built a complex high-risk feature in under 2 hours, putting deployment at 4 days instead of about 4 weeks.
A random mix from the whole library. Shuffle for a new set.
Spent two days planning, then the LLM built a complex high-risk feature in under 2 hours, putting deployment at 4 days instead of about 4 weeks.
Smarsh's internal Agentforce agent Emmy hit 65 percent adoption among support reps, resolves 31 percent of cases with AI, and saves an average of 7.5 hours per case.
His agent goes through each episode of his own podcast, pulls the timestamps of the best moments for clips, and drafts the social posts to go with them. Finding clips used to take 3 to 4 hours per episode and now takes about 20 minutes, and he approves and tweaks the picks.
He let the AI run on its own for 40 minutes on a billing refactor. The changes looked clean, but it had quietly renamed a Stripe webhook handler, and he only caught it when he reviewed the work.
Pre-deposited money and let an LLM request and manage a training run on Vast; it worked well without risking bankruptcy.
He used Fable to rewrite 65kLoC of Go in Rust at a cost of $400.
Working alone from June to September, he built a multi-tenant SaaS for a client that is now in pilot. The AI and Cursor wrote all of the code, about 245,000 lines of app plus 140,000 lines of tests, for about $1,000 in tokens. Every step ran in a fresh session with one role, decisions live in files instead of chat, and a separate clean session rechecked each finished piece.
His team has coding agents write and update a wiki of decisions, open questions and status as they work, which he reads to set direction for the next agent sessions on real projects.
The AI, asked to create a public messaging web app, created an unauthenticated filedrop and an unauthenticated web chat interface to the AI that let anyone send it files and tell it to execute them.
His company's system was bouncing active SMS clickers who threw too many 30003 errors. The AI Ultracode found the cause, and the fix means the sunsetting code now ignores active clickers.
Every idea is a real post from someone who tried it, summarized in our words, with a link to the original. App names are swapped for plain words.