TFA falls into a few traps, like a reducto argument about text prediction. There's no reason text prediction can't do these things, fundamentally. But I pretty

TFA falls into a few traps, like a reducto argument about text prediction. There's no reason text prediction can't do these things, fundamentally. But I pretty much agree with what they are saying. The missing "thing" is the developer context. Each agent I kick off needs a nonlinearly increasing amount of coaching, as a function of feature complexity. The sweet spot for productivity is currently the first 3 steps (from TFA), to get things into _my head_, then using the writing abilities more as ubersed or ubergrep with LSP integration. Love it for that. For example, I'll often write the first 5th to 3rd of a feature by hand, then ask the agent to extrapolate from there. The "Core" contains the important bits but in a large system there's a lot of corner cases and wiring, and agents are good a discovering those. I interrupt when it tries to fix things by departing from the design and instead nudge or write a better solution quickly. I absolutely hate the "Spin a cadre of agents to design/implement a feature from a concise spec" workflow. It involves so much planning to get the automatic execution working that it's often just easier to switch to hybrid planning/execution with both AI and people.