Author name: Yar

I stumbled on a post that completely reframed how I think about AI in design. Most people still treat AI […]

What if your worst LLM outputs could quietly teach your system to write better prompts? A new open-source tool called

Yesterday a developer named SrMugre shipped a small CLI tool that solves one of the most annoying problems in production

A new optimizer dropped this week. It doesn’t ask you to write better prompts. It reads your failures and rewrites

Fresh off ProductHunt, a new open-source tool just flipped the script on prompt engineering. Instead of guessing why your LLM

TL;DR: Adding one line to your debugging prompt, “explain why your previous solution failed”, breaks the endless error loop and

Batch-processing jobs have a nasty habit of teaching budget lessons the expensive way. One oversized prompt, one wrong model choice,

A new open-source tool just dropped that tackles one of the most annoying problems in prompt engineering: figuring out how

Yesterday a clever build shipped in r/PromptEngineering. A developer added a Cost and Latency Estimator to their prompt compiler. That