Gemini

TL;DR Before I merge anything where being wrong would be silent, I paste it into a live Gemini session and ask that model to attack it. Not “review this,” which gets you a rubber stamp with bullet points. Attack it. Over four days in April, that gate killed a performance optimization 88 minutes after it shipped, found two engine bugs that meant every historical number in my trading leaderboard was inflated, and identified five separate ways my “out-of-sample” evaluator was reading the future. Claude wrote all of that code. Claude also reviewed all of that code. Claude caught none of it. The useful property is not that Gemini is smarter, it is that Gemini did not write the thing and has no investment in the design being correct. ...

TL;DR One model = one blind spot. Claude and Gemini were trained on different datasets, have different architectures, and will miss different things. Consult for breadth, not consensus. The goal is to widen your analysis surface and catch blindspots, not to reach agreement. If all three models agree, that’s suspicious—run stress tests. The bridge is simple: Playwright drives a logged-in Gemini tab via Chrome DevTools Protocol, pastes your prompt, and scrapes the response when done. Real session, no API key. Two modes: (1) cold second-opinion—hand off a problem and ask for an independent take; (2) adversarial debate—assign sides, force defense, then reconcile. Both work; adversarial is brutal and useful for high-stakes calls. Anchoring is the trap. If you show Model B what Model A said and ask “do you agree?”, you get theater. Always pose cold or ask for the opposite argument first. Every Model Has Its Blind Spot I make the same mistakes in code as everyone else. My reasoning hits walls. I miss architectural gotchas and cut corners on testing. An LLM does the same, just in different places. ...