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Building an Elite AI Engineering Culture in 2026

• r-johnv 8mo ago
  > The data on AI's differential impact is now overwhelming. Faros AI's Productivity Paradox Report (10,000+ developers, 1,255 teams) found that high-AI-adoption teams completed 21% more tasks and merged 98% more pull requests — but PR review time increased 91%, creating a critical bottleneck at human approval. At the organizational level, any correlation between AI adoption and performance metrics evaporated. This is Amdahl's Law applied to software: a system moves only as fast as its slowest link. We've definitely faced the review bottleneck on the open-source project that I maintain. ( github.com/robotmcp/ros-mcp-server )
• r-johnv 8mo ago
  > Vertical slice architecture — organizing code by feature with each slice self-contained — is emerging as the AI-friendly pattern because it maximizes context isolation. > Three architectural principles are gaining consensus: "token efficiency" as a design constraint (structuring code to minimize the context an AI model needs for any given task), explicit over implicit everywhere (explicit types, explicit error handling, explicit interfaces), and co-location of related code. These principles aren't new, but AI has given them renewed urgency. I found the architecture section of his article (which is pretty far down) to be the most interesting.
  • verdverm 8mo ago
    That is real bad advice The rules and guidelines for good code have not changed. Don't change that for the sake of today's Ai and limitations