Time-Blocking Is Broken: 5 Adaptive Planning Methods That Work Better (TPS625)
Summary
Tan and Brooks discuss how AI agents are reshaping productivity, shifting focus from single-tasking to managing multiple concurrent workflows. They explore new challenges like "knowledge debt" and agent-induced distractions, while debating the evolution of time blocking and the enduring value of buffer blocks. The episode also covers strategies for maintaining deep work, such as designating specific meeting days and aligning tasks with energy levels.
Topics discussed
Intro: Tension between intended and actual work
Tech gear: USB-C adapters, mice, and UPS batteries
Power reliability and the importance of uptime
Theming mornings and afternovs for focus
AI workflow: Defining vision and reviewing output
Disrupting time blocking with AI agents
Increased output and Masterclass ad break
Managing multiple AI agents and attention limits
Knowledge debt and trusting AI-generated code
Manual vs. automated tasks and MITs
Carving out uninterrupted time for top priorities
11Labs and Notion sponsor segments
Breaking down large tasks and calendar analysis
Meeting days and day theming strategies
The power of buffer blocks between meetings
Sticking to buffers and planning by energy levels
Matching task urgency to available energy
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