AI Is Now Hiring Other AI: Is It Worth It?

A new AI model out of Japan, Sakana Fugu, does something we have not really seen before. Instead of answering you itself, it hires a team of the best AI models, gives each one a piece of the job, and merges their work into one answer. Harrison calls it a manager, or a conductor: you ask one question, and behind the scenes it quietly builds a team for you. In this episode, Harrison explains what model orchestration actually is in plain language, why he thinks this is where AI is heading, and then puts it to the test. He sends the same 8 questions to Fugu, to Claude Opus 4.8, and to GPT-5.5, and grades every answer. The result is honest, and the cost is the part that should give every builder pause. What you'll learn: \- What "orchestration" means, explained simply \- Why the future may be teams of models, not one genius model \- What happened when a team of models went head to head with single models \- The real speed and cost tradeoff, with actual numbers \- The hidden tokens you pay for but never see \- When an orchestrator is worth it, and when one good model is plenty \- A heads-up on AI pricing and subsidies most people are not thinking about CHAPTERS 0:00 A glimpse into the future 0:19 What is Sakana Fugu? 1:55 Not a smarter model, a manager 3:30 The test: 8 questions, three models 4:50 Speed: about 10x slower 5:30 Cost: about 49x more expensive 6:07 The hidden tokens you pay for 7:20 Inside the console 8:30 The questions, and why they're tricky 9:06 Is a team of models worth it? 9:27 When a team earns its place 10:09 The verdict 10:57 The subsidy nobody is talking about 11:18 Where this goes next 12:04 Wrap up Mentioned: Sakana Fugu — https://sakana.ai/fugu/ If you got something out of this, follow the show and send it to someone who's working to keep up with AI.