Capstone 05 — Autonomous Research Agent (AI-Scientist Class)
Sakana's AI-Scientist-v2 published full papers. Agent Laboratory ran the experiments. Allen AI shared traces. The 2026 shape is plan-execute-verify tree search over experiments, budgeted cost, sandboxed code execution, a vision-feedback LaTeX writer, and an automated NeurIPS-style reviewer ensemble. The capstone is to build one, run it end to end within $30 per paper, and survive the sandbox-escape red team that Sakana documented. Phases exercised: P0 · P2 · P3 · P7 · P10 · P14 · P15 · P16 · P18 Autonomous research agents crossed a threshold in 2026. Sakana AI's AI-Scientist-v2 was published in Nature with generated papers that cleared workshop peer review. ShinkaEvolve (ICLR 2026) extended the line to evolving hypotheses. AMD's Agent Laboratory shipped reproducible traces. The agents are not magic — they are a plan-execute-verify loop running over a tree of candidate experiments, with cost caps, seed-bound sandboxes, and automated review. The craft is in the loop, the budget, and the safety story. You learn the loop by implementing one against a seed idea in a narrow domain (for example, attention-sparsity ablations on a 100M-parameter transformer). The value is not in discovering something new on the first run. The value is in the infrastructure: the tree-search, the experiment sandbox, the writer-reviewer loop, the red-team report. The Sakana team documented sandbox-escape failures; your agent must pass the…
Capstone 05 — Autonomous Research Agent (AI-Scientist Class): Sakana's AI-Scientist-v2 published full papers. Agent Laboratory ran the experiments. Allen AI…
This free lesson is part of the AI Engineering from Scratch curriculum. Read the full explanation, run the lesson code, and verify the result in the interactive reader or from the repository source.
Browse the complete course catalog or open this lesson on GitHub.