The Psychology of Technologists
summary
Presents empirical claims and usable tools: a LABS model (learning culture, agency, self-efficacy, belonging) that correlates with productivity from a 1,282-person open science study; an AI survey of ~5,000 devs linking lone-genius culture to doubled “AI skill threat”; analysis of 55k cycle times, 11k engineers, 216 orgs that finds no stable 10x developers; and an RCT code‑review workshop that yields about a 40% reduction in avoidance while boosting self‑efficacy and self‑compassion.
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chapters (19)
- 0:00Psychology of technologists
- 1:07Exercises for anxiety and focus
- 4:04Social learning in tech
- 8:23Social learning in teams
- 10:33Leadership vs developers' mismatch
- 13:48Unseen work and recognition
- 16:41Learning debt impact
- 18:29Psychological affordances
- 20:38Brains-in-jars traps
- 26:28Sustainable productivity factors
- 30:23Performance paradox in engineering
- 36:52Mindset and context metaphor
- 38:36Pressure in tech work
- 40:43AI skill threat impact
- 47:10Testing 10x developer myth
- 51:3410x developer flaws
- 54:24Code review anxiety trial
- 58:42Breaking brains-in-jars model
- 1:00:23Social learning in remote teams
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