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All digests tagged Coding Agents
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AI is drastically changing software development. The focus is shifting from writing code to mastering system architecture, process governance, and the role of the forward-deployed engineer.
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Building rigorous evaluation systems for AI coding agents is complex. The talk details why public benchmarks fail and how to balance measurable vs. representative tasks, emphasizing observability and trace analysis.
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Learn how Postman mapped 115 microservices into an API context graph to enable coding agents to function across complex, distributed systems. Discover how to improve API discovery and impact assessment.
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Learn LangChain using a custom tutor skill integrated into coding agents. The LCA Tutors repo allows structured learning through quizzes and labs for foundational concepts.
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Tau is a Python port of the coding agent Pi, featuring a Textual TUI. It allows users to manage sessions as tree-structured data, export them as JSONL for analysis, and utilize skills and custom prompts.
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dcode introduces the /goal command for long-running tasks. It establishes visible acceptance criteria and uses a 'goal loop' to guide agents over hours, allowing mid-run steering and inspection via LangSmith tracing.
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Pi Agent offers superior flexibility over competitors like Cloud Code and CodeX. Its core strength is its extension system, allowing programmatic modification of tools, contexts, and hooks to build highly customized, autonomous AI systems.
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