My AI Adoption Journey
mitchellh.com
February 5, 2026
12 min read
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74/100
Summary
Adopting new tools often involves three phases: a period of inefficiency, followed by a period of adequacy, and finally a phase of significant workflow improvement and discovery. Initial resistance to adopting new tools is common due to existing comfort with current workflows.
Key Takeaways
- Adopting AI tools typically involves three phases: inefficiency, adequacy, and workflow discovery.
- The author emphasizes the limited utility of chatbots for coding tasks, finding them inefficient compared to manual work.
- To effectively use AI agents, they must be capable of reading files, executing programs, and making HTTP requests.
- The author recommends breaking down tasks into clear, actionable steps and separating planning from execution to improve results with AI agents.
Coverage & discussions
Hacker News · mitchellh.com
Community discussions
Community Sentiment
Positives
- The article presents a balanced view on AI adoption, highlighting how even skeptics have found value in integrating AI tools into their workflows.
- The suggestion to break down tasks into clear, actionable steps emphasizes the importance of manageable scopes for AI applications, enhancing usability.
- The author's experience with treating AI as a tool for shaping plans rather than a complete solution reflects a pragmatic approach to AI integration.
Concerns
- There is a notable frustration with AI agents requiring constant guidance for improvement, indicating limitations in their adaptability and learning capabilities.
- The mention of drift in AI outputs suggests that while AI may seem plausible, it can diverge from actual project constraints, leading to potential pitfalls.
