kiosa (@thegreatest_sv)

whoever built this realized we’ve been using our smartest AI for the dumbest possible jobs your $20-$200/mo frontier model is researching, writing code, planning… and then you’re paying the same brain to decide YES / NO. Jev flips that. it’s a tiny decision model that sits in front of the expensive stuff and handles the boring forks: -> which agent goes next? -> is this worth researching? -> reply or ignore? -> publish, wait or escalate? -> BUY / SELL / HOLD? -> click this or keep looking? then I saw the numbers people are reporting and the whole architecture started making a lot more sense. ~1,000 papers classified for around $0.08 ~500 emails sorted for around $0.035 browser-agent loops demonstrated around 7 seconds for ~$0.0039 and at the quoted pricing, roughly 10,000 ~1K-token decisions comes out around $0.42. that’s not because Jev became smarter than Claude. it’s because nobody asked it to be Claude. the setup is stupidly simple: -> big LLM gets the hard thinking, research and writing -> Jev gets the thousands of tiny decisions between those steps -> code actually clicks, saves, sends and executes and suddenly you start noticing these little decisions everywhere. > your inbox. > X feed. > support queue. > meetings. > leads. > video clips. > browser agents. > even paper-trading loops. that’s the part I think most agent builders are missing. the expensive model doesn’t need to touch every step just because it’s capable of touching every step. > let Claude think. > let Jev decide what deserves Claude. > let code do the actual work. I broke down 12 places you can wire this into an agent today + the exact router setup in the article below

SOMEONE GAVE CLAUDE CODE A PHYSICAL BODY ESP32 board, small screen, sitting right by the keyboard. They call it Clawd Mochi. A crab, styled after the Claude Code mascot, cycling through animated faces. Flip it into terminal mode for the dev look. You can even doodle on its screen live from your phone. Fully open source - files are on GitHub for anyone to print and build. Someone gave their coding agent a body, just because. A little crab watching you ship code all day. And if something's going to sit there watching Claude work, it might as well run cheap. Found a free tool that cuts token burn by up to 90%

CLAUDE PROMPTING IS DEAD. HERE ARE TOP 5 FACTS YOU DIDN'T KNOW ABOUT LOOPING. 1. A prompt stops the second Claude answers. A loop keeps going until it hits a goal you set. 2. In a loop, Claude checks its own mistakes and comes back to fix them - you stop being the error-checker. 3. Spotify's chief architect said loops took their AI agent from a 20–30% success rate to ~80%. Same models. Just a loop. 4. "Make it good" doesn't work - Claude can only grade itself against a number or a checklist. Give it a measurable goal. 5. Verification is the whole game: in a real loop, broken output never ships - it loops back and gets fixed. The future isn’t one perfect prompt. It’s Claude improving its own work until it passes your bar. I broke down the best Claude looping workflows below.

THIS JAPANESE STUDENT USED CLAUDE TO PROGRAM HIS DEVICE AND ACCIDENTALLY PROVED THE ONLY AI SKILL THAT MATTERS IN 2026. He did it in 15 minutes without knowing how to code. > a Pomodoro timer that tracks study sessions and tells him when to break > a menu to reach every feature on the device > retro video games "for the vibes" Claude coded all three. Exactly as described. In 15 minutes. His words: "now imagine what I could do in an hour." Here's what nobody points out though - the magic wasn't the model. It was how he asked. Clear task, clear outcome, zero jargon. That's the whole game. I broke down the 20 prompts I use to get results like this