Read recent articles on AI in our blog. Discover the latest AI-based tools for optimized engineering and other ways to adopt AI technology in the SDLC.
Comparing two ways of completing the same upgrade: migrating a Node.js 14 project to Node.js 18 by chatting with an AI assistant and performing the same migration through a spec-driven development approach, with a strict, pre-written plan.
Stop losing your best AI workflows to random markdown files.
Runbooks doesn’t replace Claude Code; it transforms AI from an individual tool into a multiplayer development platform through spec-driven development.
Spec-driven development replaces the chaos of ad hoc, prompt-driven vibe coding with a structured, durable way for engineering teams to work on AI coding projects.
The future of AI coding in enterprise lies in spec-driven development, shared context, and collaboration, not vibe coding.
AI adoption is nearly universal, but the 2025 DORA Report shows that faster coding doesn’t always mean increased productivity.
Spec-driven development is not a choice but a necessity as we move from vibe coding a cool app to building real-world brownfield projects.
Building software with AI agents isn’t a solo sport, especially when projects touch multiple repos, services, and prompt engineering knowledge.
Runbooks capture context from repositories or code reviews, combine it with the team's AI prompting knowledge and get smarter with each use.
AI is a developer productivity force multiplier, but poor documentation, unclear ownership and fragmented tooling don’t magically disappear with AI.
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