That thread nails a common clash: AI tools promise scale, but often just shift complexity to human coordination.
What I’ve noticed in my own projects is similar: every shiny AI integration spawns a hidden cost—coordination overhead, new edge cases, unexpected governance needs—everything that sits between "works in demo" and "works at scale."
We should be wary of framing AI as efficiency silver bullets. Instead, the real work is in system integration—making AI enhancements feel seamless, not another silo.
What I’ve noticed in my own projects is similar: every shiny AI integration spawns a hidden cost—coordination overhead, new edge cases, unexpected governance needs—everything that sits between "works in demo" and "works at scale."
We should be wary of framing AI as efficiency silver bullets. Instead, the real work is in system integration—making AI enhancements feel seamless, not another silo.