February 7, 2026
Bot Battle Royale: devs grab popcorn
Selection Rather Than Prediction
Stop guessing—run a bot bake‑off and let humans crown the winner
TLDR: Teams stop picking one coding bot and instead run several, letting the best result win—top‑7 wins 91% vs top‑1’s 24%. Commenters cheer the bot battle but spar over token costs, orchestration pain, terms‑of‑service worries, and whether smart delegation beats spinning up seven models.
Forget picking a single “best” coding bot—this team says run a mini tournament and ship the winner. In real TypeScript work, the leaderboard is noisy: even top models like gpt‑5‑2‑high and gpt‑5‑2‑codex‑high are neck‑and‑neck. The kicker? One bot wins 24% of tasks; a squad of seven nails 91%. Translation: stop betting, start selecting.
The comments lit up like AI Hunger Games. tomtom1337 wants a playbook for wrangling seven pull requests without chaos. jmalicki asks if doing this with a Claude backend could get their subscription nuked—cue a terms‑of‑service panic. bisonbear swears by a “boss bot + helper bots” strategy to dodge 7x token bills, claiming smart delegation beats brute force. And fph drops the meme of the day: “AI is like XML—if it doesn’t solve your problem, you’re not using enough of it.”
Fans love the human judge twist—agents compete, humans arbitrate—calling it a “robot bake‑off” that turns work into live ratings. Skeptics warn it’s a management nightmare without good tooling. One takeaway unites both sides: leaderboards are fun, but cohorts ship better code.
Key Points
- •The authors run best-of-N: multiple agents work in parallel, each producing a candidate solution, with a human selecting the best diff to merge.
- •Data spans 211 real coding tasks across 18 agents, mostly full-stack TypeScript work completed within minutes to about an hour.
- •Agent performance is ranked via a Bradley–Terry model mapped to an Elo-style rating with 90% bootstrap confidence intervals.
- •Top-tier agents show overlapping confidence intervals; the top two (gpt-5-2-high and gpt-5-2-codex-high) are not statistically separable.
- •Cohort selection yields large gains: top-1 wins 24%, top-3 wins 51%, top-7 wins 91%, with diminishing returns beyond seven agents.