Applying Small Business Principles to Fix an AI Codebase
The author applied principles from their book 'Run on Rhythm' to an AI software project, leading to immediate improvements in planning, risk management, and quality.
Why it matters
The article demonstrates how applying simple, non-technical principles can have a significant impact on the success of an AI software project.
Key Points
- 1Planned sprint capacity was reduced from 155 to 42 points, focusing on infrastructure and quality first
- 2Introduced a 'Risk Radar' to proactively identify and mitigate potential issues
- 3Adopted a 'repair over blame' approach to quickly fix problems instead of investigating root causes
Details
The author's AI project was facing several challenges, including overcommitment, failing tests, quality issues, and a broken memory system. By applying principles from their 'Run on Rhythm' book, they were able to make significant improvements. Key changes included scheduling the team at 80% capacity to account for reality, introducing a weekly 'Risk Radar' to proactively identify and mitigate potential issues, and focusing on 'repair over blame' to quickly fix problems instead of investigating root causes. These operational principles, originally developed for small businesses, were found to translate directly to software development, helping the team regain control of the project.
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