proomt

Search

Search posts, papers, and topics

All posts

Josh Sherman6 min readintro

I stopped drinking the AI Kool-Aid

Summary

A personal opinion piece where the author reflects on his over‑enthusiasm for AI tools, describes a recent eye‑opening conversation, and declares he’s stepping back from the AI hype.

  • The article is a subjective rant with no technical details, code, or data.
  • It offers a cultural critique of AI hype rather than actionable engineering guidance.

While it captures a sentiment many engineers feel, it doesn’t provide concrete lessons or insights that can be applied to software development.

3/10

Related reading

  1. Everybody's Lost Their Minds

    The author argues that the AI hype wave is draining engineering resources without improving security, and that basic practices like inventory and automated patching are far more valuable. He warns that over‑reliance on AI‑generated code erodes understanding and makes debugging harder.

    Lobstersnetmeister.org6 minHN368338lobste.rs193
  2. Use Curiosity, Craft, and Care to Decide What AI Should Write

    The post proposes a three‑principle framework—Curiosity, Craft, and Care—to decide how much AI should author each artifact in a software development workflow. It argues that AI can be used aggressively for exploratory, disposable outputs (Curiosity) but should be limited for artifacts that commit the team to decisions (Craft) and for communications that require personal ownership (Care). The auth…

    Atomic Objectatomicobject.com4 min
  3. The AI magic words

    The Stack Overflow Podcast interview with Tim O'Reilly discusses books as knowledge interfaces, the concept of "magic words" for prompting AI, and the rising value of human curation. It offers high‑level observations but no concrete engineering guidance.

    Stack Overflowstackoverflow.blog1 min
  4. Agentic Skill Decay

    Addy Osmani warns that AI agents can short‑circuit the hands‑on practice (“reps”) that builds deep expertise and judgment. He recommends deliberately inserting hypothesis‑forming, “why” questioning, diff inspection, failure prediction, and occasional manual coding into the workflow, especially for junior engineers. A 2026 Anthropic study showed junior developers using AI scored 17 % lower on a fo…

    Addy Osmaniaddyosmani.com16 min
  5. Should you read the code, is RAG dead, and did Skills kill MCP?

    The article debunks five common AI‑tool hot takes, arguing you still must read AI‑generated code, AI fluency matters in hiring, MCP and Skills serve different purposes, RAG remains useful, and needing fine‑tuning signals a messy codebase. It offers concrete rules for reviewing generated code and integrating AI components responsibly.

    GitHub Oldgithub.blog5 minHN3