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How Much of a Harness Does a Strong Agent Need for Autonomous ML Engineering?

Recent autonomous machine learning engineering (MLE) agents have made significant progress on public leaderboards. Often motivated by progress stagnation over long-horizon cycles and limited Large Language Model (LLM) primitives, modern MLE agents are deployed on top of increasingly elaborate machinery: multi-agent orchestrators, dedicated retrieval subagents, and more. While such harnesses…

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What happens when an LLM loop runs away: the guardrail pattern

Nobody budgets for the runaway loop. Every AI SaaS has a line item for "expected LLM spend" and nobody has a line item for "the Friday night a bug turned our agent into a money printer." I've seen the…

  • Implement guardrail pattern to prevent runaway LLM loops
  • Price every call using pricing table per model
  • Maintain pre-aggregated spend ledger for fast cost checks

Scaling Laws for Looped Mixture of Experts

Looped transformers and Mixture-of-Experts (MoE) offer complementary routes to efficient scaling: recurrence increases computational depth at fixed parameters, while MoE sparsity expands total…

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