The Sequence Opinion #547: Best Practices I am Learning While Coding with AI Agents | By The Digital Insider

Software engineering practices are rapidly changing.

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Coding with AI agents is the new reality. Every software engineering team is incorporating AI agents to accelerate their engineering workflows and that’s just fascinating. An equally interesting fact is how software development practices are changing with AI agents. Are developers writing more documentation? different types of tests? These days, I’ve been learning a lot from the software development teams I worked with about their practices for incorporating AI agents. Although premature, I wanted to capture some of those ideas in this essay.

Previously considered merely as code-completion tools, agents today actively navigate repositories, generate production-ready code, run tests, and even perform automated pull-request management. Companies such as Block already utilize sophisticated agents like "Goose," powered by Claude and Model Context Protocol, to deploy code at scale, signaling a transformative shift toward agent-augmented development.

How AI Agents Redefine Core Software Engineering Practices

AI agents significantly influence core software engineering (SE) tasks, shifting roles from manual coding to strategic oversight:

  • Coding: Human developers increasingly transition to roles involving code review and specification writing, as agents reliably generate initial codebases.

  • Testing: Traditional post-implementation testing gives way to large-scale Test-Driven Development (TDD), where agents begin with failing tests and iteratively refine code.


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Published on The Digital Insider at https://is.gd/zFaaKV.

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