7 posts about agent workflows by 5 contributors.
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AI agents are moving beyond short conversations. Developers are building agents that inspect codebases, execute tools, run tests, investigate failures, and complete workflows that may take hours to finish. However, running an agent in production introduces a different set of engineering challenges.
AI coding tools have changed quite a bit. They are no longer limited to answering questions or suggesting a line of code. An agent can look at a task, decide what it needs to do, call tools, inspect files, and continue working based on the result. That becomes interesting when you want to put this k
Learn how to build production AI agents with Claude Web Fetch in Microsoft Foundry for grounded responses, real-time web content, and reliable agent workflows.
Learn how GitHub Copilot Agent Plugins 1.0 enable portable coding workflows across VS Code, Copilot CLI, and the Copilot app with reusable tools and automation.
Learn how to implement AI agent observability in .NET applications using monitoring, logging, tracing, OpenTelemetry, and best practices for production AI systems.
A detailed, publication-ready guide to Agent Engineering—its foundations, architecture, workflows, challenges, and future impact. Optimized for SEO and GEO for long-term visibility.
LangChain Polly automates the design, evaluation, and refinement of AI agents using structured specifications, scenario-based tests, and LangGraph workflows.
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