AI Summary
→ WHAT IT COVERS Ben Coon, Wave employee and blogger, joins host Ben Orenstein to discuss developing a writing habit, applying effective altruism principles to career decisions, Wave's mobile money impact in Senegal, and building high-signal engineering interview processes that distinguish strong candidates from weak ones. → KEY INSIGHTS - **Writing for quantity over quality:** Publish on a consistent schedule — weekly at minimum — before optimizing for quality. Blog post readership follows a heavy-tailed distribution where top posts reach 100x more readers than average ones. Volume generates the samples needed to identify what resonates, and that pattern recognition eventually enables fewer, higher-quality posts per year. - **Effective altruism and scope neglect:** When comparing charitable causes, calculate the cost-per-outcome rigorously. A guide dog costs $40,000; a blindness-curing surgery costs $40. That is a 1,000x difference in impact per dollar. Most people skip this math entirely. Using a rough quantitative framework — even an imperfect one — catches order-of-magnitude errors that intuition misses. - **Career impact via 80,000hours.org:** Developers seeking high-impact career paths should start at 80000hours.org, which maps cause areas by scale and provides one-on-one career coaching. Direct-impact roles — like building financial infrastructure for unbanked populations — can outperform earn-to-give strategies by creating a tangible connection between daily work and measurable outcomes for large populations. - **Engineering interview design:** Give every candidate the same task — ideally extending an existing codebase rather than greenfield work — to enable calibration across candidates. The task should be conceptually tricky but completable within four hours. If interviewers frequently press the "weak yes" or "weak no" buttons in debriefs, the task is not generating sufficient signal and needs redesign. - **Behavioral interview precision:** For managerial roles, ask candidates to describe handling an underperforming direct report, then probe three specific timeline checkpoints: how quickly they detected the issue, how quickly they addressed it after detection, and how quickly they reached resolution. Defining good versus bad answers before the interview prevents vague responses and makes it harder for candidates to omit damaging gaps. → NOTABLE MOMENT After switching from a well-paying machine learning role to Wave, Ben Coon noticed a sharp increase in his own productivity — not because the work was more intellectually stimulating, but because the direct connection between his daily tasks and real user outcomes made even tedious accounting work feel worth completing. 💼 SPONSORS None detected 🏷️ Effective Altruism, Engineering Hiring, Writing Habits, Career Impact, Mobile Money