Related reading
The Bitter Lesson
Rich Sutton’s essay argues that over the past 70 years AI progress has consistently come from methods that can scale with more computation—search and learning—while hand‑crafted, human‑knowledge approaches give only short‑term gains. The piece uses chess, Go, speech and vision as case studies to warn researchers to favor general, compute‑driven techniques.
Hall of Fameincompleteideas.net5 minHN15253How I Support Humans in the AI Era
An engineering manager shares her approach to integrating AI tools into her team's workflow by creating dedicated spaces for connection, collaboration, and discussion, rather than imposing new policies. This strategy fostered psychological safety and autonomy, allowing the team to organically explore and define their own AI norms and practices.
Honeycombhoneycomb.io5 minAI vs. automation: What's the difference?
This article clarifies the distinctions between automation (fixed rules), AI (data-driven decisions), and agentic AI (adaptive multi-step planning). It demonstrates how integrating AI with automation creates more intelligent and cost-effective workflows by applying AI only where judgment is required.
Zapier Engineeringzapier.com10 minEven with LLMs, Let’s Pair Together
This article argues that pair programming remains valuable even with the rise of LLMs, helping engineers critically evaluate AI output, improve tool interaction, and preserve essential human collaboration. It suggests pairing can transform LLM downtime into productive planning or tool improvement.
Atomic Objectatomicobject.com3 min


