Decision-first: Per new model, sweep temperature (don’t assume 0.3), try reasoning off for builders, test echo_reasoning both ways, and on budget_exceeded check turns-vs-tokens before changing either. The right config is model-specific — assume nothing.

Scope & freshness: Local + cloud models for agentic coding, 2026-05. Findings are per-model (see the specific models named); treat them as examples of shape, not universal constants — re-sweep for any new model.

Agentic Workflow Patterns#

An agent without a workflow pattern is a chatbot. What separates an agent from a single-turn LLM call is the loop: observe the environment, reason about what to do, act, observe the result, and decide whether to continue. The loop structure determines everything – how the agent plans, how it recovers from errors, when it stops, and whether it can handle tasks that take minutes or hours.