My AI Adoption Journey
mitchellh.com
February 5, 2026
12 min read
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.
Community Sentiment
MixedPositives
- 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.
Source
mitchellh.com
Published
February 5, 2026
Reading Time
12 minutes
Relevance Score
74/100
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