From the Horse’s Mouth: Anthropic Says AI Has Changed the SDLC

Anthropic, a company known for its AI development, has published a playbook outlining a new approach to the software development lifecycle (SDLC). The playbook, authored by Louis Claxton, argues that code is no longer the main bottleneck in the process. Traditionally, the SDLC has been organized around the time-consuming task of writing and implementing code.

However, with the advent of AI, code can now be generated, tested, and reviewed much more quickly. This doesn't mean that the rest of the process becomes obsolete, though. Requirements, architecture decisions, code reviews, testing, and production changes still need to be addressed. If these processes remain unchanged while coding speeds up, the bottleneck simply moves to other areas.

For instance, review queues may grow, security teams could become overwhelmed, testing infrastructure may be strained, and change approvals could hold up completed work. This could lead to situations where more code is produced, but software reliability decreases. DORA's research supports this, finding that while AI can improve productivity and delivery speed, it can also negatively impact software stability if not properly managed.

Anthropic's playbook proposes a more radical shift in the SDLC, turning it into a continuous loop rather than a sequence of stages. The proposed loop begins with capturing intent through an intent.md file, where a business user describes a problem in plain language. This intent is then turned into specifications, plans, code and tests, review and deployment evidence, incident records, and new intents.

This approach ensures a continuous flow of information and provides an audit trail showing all actions taken. While humans still play a crucial role, their tasks change from manually moving information between stages to evaluating intent, risk, exceptions, and consequential decisions.