Getting a coding agent productive is less about the prompt and more about whether the machine in front of it can actually build, run, and reach the systems the work depends on. Cursor, Claude, Codex, and the rest are fast when the local world is already honest: dependencies install, the app boots, tests can run,... Continue reading →

The text emphasizes the importance of a structured workflow for coding agents to prevent unintended changes. By introducing a three-step gating process—Ask, Plan, and Confirm—developers can ensure that agents check for ambiguities, outline necessary changes, and obtain explicit approval before implementation. This approach mitigates risks and enhances code quality. Continue reading →

Part 8 emphasizes building a supervised AI agent within a structured workflow using Temporal, focusing on retrieval, reasoning, and drafting without overspending on model tokens. The author outlines the importance of sequencing the development, integrating guardrails like budget limits, and asserts that trust in the agent comes from structured testing and supervision, not vague prompts.... Continue reading →

Part 6 of 8: Durable AI for InterlinedList Every serverless AI feature I’ve built hits the same wall the second someone wants it at scale. “Can it tag all my untagged messages?” Sure, one message. “All of them?” Now we’re talking about a job that runs for minutes, touches hundreds of items, and will absolutely... Continue reading →

Adron expresses a little bit of frustration over societal ignorance regarding language and concepts like “DevOps” and “Agile,” highlighting the dangers of misinterpretation and the arrogance of those who dismiss expertise. They advocate for humility, encouraging continuous learning and listening, while humorously reflecting on the absurdity of confidently incorrect assertions by others. Continue reading →