THE MODEL THAT FAILED MY TASK TWICE SHIPPED IT 6 MINUTES LATER. same prompt, same weights. in a chat box it failed twice. on the second try it forgot a decision it made 3 minutes earlier. "model's not good enough," i thought. then i listed what it had to work with: no contract, no map, no tools list, no state, no sensors, no policy, no traces. 7 rows, all "missing". so i stopped editing the prompt and built the room around it. i wrote a contract with 1 goal, 3 constraints and 4 checks for "done", and locked deploy and delete behind a human. first run inside the harness: red tests, fail. second run: 42 passed, 0 failed, $3.84. here's what got me: a human took the last step. deploy sat on "waiting human" until a reviewer said yes. and that's when it hit me - i'd burned 2 attempts on a prompt, and the bug was those 7 empty rows. i haven't touched that prompt since. the full loop is mapped out in the video - 7 jobs, 3 attempts, then a human. full breakdown + 12-point checklist in the article below

there are bugs on github with cash on them i went to bed. my agent went hunting by 8am: 1,200 found. 31 fixes ready. $10,000 if they merge the ones it kept paid $250-$350 a fix. $322 on average the video is that night mapped out the trick is what it threw away: 788 nobody had touched in 60+ days 252 where someone already sent a fix anything bigger than a day of work it only cloned the 31 that were left. ~1.9m tokens for the whole night every monday at 23:00 it goes again on fresh bounties. i don't even start it the catch: none of it pays until a maintainer merges. and it opened 0 prs - it's not allowed to without me one repo it kept says "no ai-generated prs". so it's 30, not 31 how much do you think this does in a month?

GOOGLE BUILT A SELF-IMPROVING AGENT. THE PART THAT DOES THE IMPROVING IS CLAUDE. harness² went open source this weekend. the default editor is claude opus 4.8. it never touches the weights. after every task it rewrites everything around them - prompt, tools, memory, skills. glm-5 went from 64.2 to 75.7 after one rewrite. → runs the task once as a reference → tries 2 rewrites of its own setup → keeps what the runs back up, no grader needed → saves the lessons to EXPERIENCE.md for the next task watch 0:12, that's where the new harness gets assembled. the catch is every task runs 3 times, and google doesn't say what that costs. remember that part. stock gemini lost to glm-5 wearing a better setup. google published that table themselves. would you let claude rewrite your agent's setup after every task, or only after it fails?

20 REVERSE-ENGINEERING REPOS AROUND ONE CLAUDE CODE SESSION, AND THE AGENT ONLY TOUCHES 11 the center is REA - 300k+ github stars, MIT license, runs on your own disk this is the loop mapped out: one prompt, 20 tools on the shelf, opus 5.5 picks → type one prompt: reverse ./target with REA, rebuild it clean-room → pull mitmproxy to replay the login call and see what the app sends → map the functions with rizin, split the logic with ghidra + angr → hook live calls with frida, check registers at the breakpoint with x64dbg → write SPEC.md - behavior only, zero copied code → rebuild against an oracle and retry until the outputs match stripped c++ binaries still fight back. the loop runs smooth on .net and electron apps, slow on the hard targets. remember that part most people install all 20 tools and never finish a target. here the agent pulls 11 and leaves 9 on the shelf $0 for REA, ghidra, frida and radare2 - ida and hopper are the only paid pieces which app would you point it at first?

He can't code. He built a $2.8M/year tool in one weekend. And I'll show you the exact 4 steps to copy him 👇 Everyone reading this was told the same lie: you need to code, you need a degree, you need years. It's gatekeeping. Here's the proof. His name is David Bressler. He used Bubble — the no-code "toy" real engineers mock. His tool, Formula Bot, just turns plain English into Excel formulas. The most boring problem alive. How he did it — and how you copy it: 1. Find a boring, painful task people already pay to avoid. Not sexy. Painful. (His: writing Excel formulas.) 2. Wrap an AI model in a dead-simple interface. No code needed — Bubble, Bolt, or Lovable do it for you. 3. Charge a monthly fee. Boring problems = people pay every month to make them disappear. 4. Ship in a weekend. Not a polished product. A working one. He improved it AFTER people paid. They spent years learning to build. He spent a weekend building. The gate was never locked. You just believed the people standing in front of it. Which boring task would you automate first?