The tools we use to optimize our workflows including API-level observability, automated auditing workflows, MCP tool pruning, and CLI substitution are all available today in the GitHub Agentic Workflows framework. Another upcoming optimization is refactoring monolithic agents into teams of subagents using smaller and cheaper models. The next step is to move from workflow-level optimization to system-level optimization. A workflow run is not really one flat sequence of API calls. It is a chain of episodes: short phases of work like gathering context, reading artifacts, retrying after a failure,
Improving token efficiency in GitHub Agentic Workflows… Related posts AI & ML Improving token efficiency in GitHub Agentic Workflows Agentic workflows that run on every pull request can quietly accumulate large API bills. Here’s how we instrumented our own production workflows, found the inefficiencies, and built agents to fix them. …
… Workflows optimizing workflows With token data in hand, we built two daily optimization workflows. A Daily Token Usage Auditor reads token usage artifacts from recent workflow runs, aggregates consumption by workflow, and posts a structured report. …
… Tags: agentic workflows AI agents automation continuous integration developer productivity GitHub Actions GitHub Copilot Written by Senior Principal Researcher, Microsoft Research Senior Software Engineer Related posts AI & ML Improving token efficiency in GitHub Agentic Workflows Agentic workflows… …
… Related posts AI & ML Improving token efficiency in GitHub Agentic Workflows Agentic workflows that run on every pull request can quietly accumulate large API bills. Here’s how we instrumented our own production workflows, found the inefficiencies, and built agents to fix them. …
… See how the GitHub Copilot SDK enables agentic workflows directly inside your applications. Under the hood: Security architecture of GitHub Agentic Workflows GitHub Agentic Workflows are built with isolation, constrained outputs, and comprehensive logging. …
… This eliminates uncertainty about what’s happening behind the scenes, reduces the risk of accidental data exposure, and helps teams maintain control in sensitive environments. Better accessibility : Slash commands fit seamlessly into keyboard-driven and accessible workflows. …
… According to Gartner, “By 2028, asynchronous AI coding agent workflows will improve software engineering team productivity by 30% to 50%, surpassing the 0% to 20% gains from AI code assistants in 2025.” We believe realizing those gains requires agentic capabilities across every stage of the SDLC—no… …
… Related posts AI & ML Improving token efficiency in GitHub Agentic Workflows Agentic workflows that run on every pull request can quietly accumulate large API bills. Here’s how we instrumented our own production workflows, found the inefficiencies, and built agents to fix them. …
… Under the hood: Security architecture of GitHub Agentic Workflows GitHub Agentic Workflows are built with isolation, constrained outputs, and comprehensive logging. …