Executive summary: Making good career decisions requires systematically testing key uncertainties through data-rich experiments, iterative exploration, and regular reflection to update plans based on new information.
Key points:
Use “data-rich experiments” to test key uncertainties with real-world scenarios that yield detailed feedback.
Apply “iterated depth” by starting with cheap, shallow explorations of many options before diving deeper into promising ones.
“Close the loop” by regularly reflecting on learnings and updating plans/hypotheses accordingly.
Structure efforts to reduce uncertainty most quickly, tackling biggest unknowns first.
Maintain a broad “top of funnel” of options initially to enable comparison and avoid premature commitment.
Develop systems (e.g. weekly reviews) to consistently gather data and reassess career directions.
This comment was auto-generated by the EA Forum Team. Feel free to point out issues with this summary by replying to the comment, andcontact us if you have feedback.
Executive summary: Making good career decisions requires systematically testing key uncertainties through data-rich experiments, iterative exploration, and regular reflection to update plans based on new information.
Key points:
Use “data-rich experiments” to test key uncertainties with real-world scenarios that yield detailed feedback.
Apply “iterated depth” by starting with cheap, shallow explorations of many options before diving deeper into promising ones.
“Close the loop” by regularly reflecting on learnings and updating plans/hypotheses accordingly.
Structure efforts to reduce uncertainty most quickly, tackling biggest unknowns first.
Maintain a broad “top of funnel” of options initially to enable comparison and avoid premature commitment.
Develop systems (e.g. weekly reviews) to consistently gather data and reassess career directions.
This comment was auto-generated by the EA Forum Team. Feel free to point out issues with this summary by replying to the comment, and contact us if you have feedback.