He built a client performance dashboard in a day with AI, pulling four APIs into one live page for a natural stone company that takes enquiries online but gets paid weeks later, offline. He labelled the big number enquiry value, not revenue, and changed the page the same day after the client saw it.
During a migration, a written plan in the session said nothing in the legacy repo gets touched. The plan was re-shown in full mid-session. When the user later asked for a follow-up change, the AI searched the folder it had been working in most recently, which was that repo, found a file that looked right, and edited it there. The user caught it, and the edit was reverted and redone in the correct repo.
This one went wrong. See what happened before you try it.
After hackers hit their research site meta-analysis.cz, which had no central backup, the AI and the AI rebuilt it from Wayback Machine copies and scattered files on their hard drives. The site is now on GitHub, its datasets are archived on Zenodo with a DOI, and every paper has an HTML version next to the PDF.
His agent writes every sales call into the call log and the CRM, and before anyone on the team gets a number to call, it checks the log first. That stopped the team calling the same people twice.
Working with AI on his NeoBox emulator, he found setjmp was eating 81 percent of frame time, switched to _setjmp for a roughly 130x per-call gain, and the fix was merged upstream in Geolith.
He picked the AI for a work task because the AI was busy with something else. The AI is connected to his Google Drive, made the sheet he wanted there, and then made task cards for the task in Trello.
With the AI doing the grunt work he built a compiler for his own language that runs on Mac, Linux and Windows and cross-produces for those plus WASM, iOS, Android, Zynq, m68k and 6502, with a signed binary running on his phone.
Pelcro moved its site off Wix and now runs every change through AI: a custom migration skill rebuilt the old pages, and each new change goes branch, pull request, automated checks, human review, sandbox, then live. Nothing ships unless lint, type, build and content checks all pass.
Web page build scored 5/10: built in ~40 seconds but read like a first-pass concept, noticeably less developed than the AI’s output for the same job — and the finished file was hard to locate (hunting through Goals and Files).
This only partly worked. Worth knowing before you try it.
He gave the AI a paper and its Lean proofs. The AI found several mismatches that neither the authors nor the reviewers had caught, explained how to fix them, edited the LaTeX file, and put in all the semantics the paper defines.