AI Agent Costs Are a Black Box, So I Built AgentMeter

AgentMeter tracks AI agent costs in GitHub Actions, bringing transparency to Claude, Codex & GitHub Agentic Workflows spending. Software engineering is undergoing a fundamental shift. We're not talking about another framework or cloud service—this is about how we write code itself. AI agents are moving from experimental toys to production infrastructure. Take GitHub Agentic Workflows (gh-aw), developed by GitHub Next and Microsoft Research. It lets you write repository automation in markdown, running AI agents like Claude, Codex, or Copilot inside GitHub Actions with proper guardrails and sandboxed execution. Teams are using it right now to auto-implement issues, review PRs, maintain documentation, and analyze CI failures—triggered by events or running on schedules. The trajectory is clear: agentic developer workflows are becoming standard CI/CD components. Just like we automated testing and deployment, we're now automating implementation and review. The infrastructure is mature, the s