Agent performance is increasingly determined by the executable control layer around the model. TTHE improves fixed large language models (LLMs) by editing their harnesses from unlabeled traces, while…
Agent teams can cut inference cost by adapting the control program to a bounded workflow, improve deployed behavior through trace-driven harness edits, and diagnose long runs with checkpoint-level grading.
The day’s clearest signal is productization under evaluation pressure. Coding and security agents advertise guardrails, repair loops, and audit trails, while model-routing arguments put cost and latency beside quality.
Agent teams now have concrete control patterns to test: deterministic replay for stale-state failures, pre-release source audits for multi-file security flaws, and session-locked model routing for routine knowledge work.