GTD was criticized by creatives as too manager-oriented. Individual contributors had one job, one codebase — GTD’s complexity felt like overhead. But GTD wasn’t designed for managers. It was designed for knowledge workers managing complexity across multiple horizons. In 2005, that was mostly managers. In 2026, that’s everyone working with AI.

The bottleneck shifted. Raw capability stopped being the constraint — the constraint is now cognitive architecture: how much you can concurrently think about across different altitudes. When you’re managing a fleet of AI agents, you need to capture what’s on your mind, break visions into delegatable chunks, review what worked, and shift between strategic decisions and tactical verification. 1.1.1 My job is thinking, then AI executes in the system I build. GTD’s Horizons of Focus, Weekly Reviews, and Projects → Next Actions map directly to what successful AI-augmented builders are rediscovering.

The GTD workflow also reframes along human vs. AI capabilities. Capture stays human — these are your raw thoughts. But AI can now handle clarify and organize, turning rambles into projects and next actions. Reflect and engage stay human — you decide priorities and direction. 2.6.5.3.1 A Zettelkasten workflow is felosztható a GTD lépéseire — and now AI can take over some of those steps. 1.1.1.3 AI reframes depth from execution to directing, which means GTD’s orchestration framework is no longer overhead — it’s the cognitive infrastructure you need to not drown when the machines handle most of the execution.

#GTD #AI