Research-focused agent item on why token usage in coding agents varies dramatically and does not reliably map to accuracy.
This is one of the most concrete sources because it moves the discussion from vibes to measured agent behavior on coding work.
The paper supports a core site thesis: agent token burn can vary sharply, and more tokens do not automatically mean better results.
A primary source for agent-burn pages, especially when explaining why budgets, traces, and evals matter for long-running coding agents.
langchain-ai/langgraph
A framework for building resilient stateful agents with explicit graphs, persistence, human-in-the-loop flows, and controllable execution.
promptfoo/promptfoo
A CLI and CI workflow for testing prompts, agents, and RAG systems across models, with evals and red-team style checks.
stanfordnlp/dspy
A framework for programming and optimizing language-model pipelines rather than hand-tuning one prompt at a time.
Help Net Security covers Microsoft's WinUI agent plugin for GitHub Copilot CLI and Claude Code, aiming to make WinUI 3 app loops (build/run/test/package) agent-friendly.
Anthropic ties higher Claude Code and API limits to new compute capacity, making capacity itself part of the agent-product story.
Augment Code rounds up model routing options for agent systems - tools that decide which model to call per step to balance quality, latency, and cost.