AI Native Dev
Influences
AI Native Dev is independently developed. These references shaped how we think about complexity, software fundamentals, and reviewable workflow artifacts; they do not imply endorsement, sponsorship, partnership, or affiliation.
Independent project
Influence here means learning credit. AI Native Dev is independently developed, and the people or projects listed here have not endorsed, sponsored, partnered with, or affiliated with AI Native Dev.
Sources
Hands-on coding-agent work across real repositories
The strongest influence is repeated practice: building with coding agents, watching where workflows fail, and turning those lessons into repo-native protocols that can be reviewed and reused.
John K. Ousterhout
Ousterhout's book sharpened the project's bias toward reducing complexity, preserving clear boundaries, and making design decisions reviewable instead of implicit.
Book pageMatt Pocock
This talk reinforces the product belief that AI-assisted development still depends on durable software fundamentals, explicit tradeoffs, and careful engineering judgment.
Watch videoGitHub project derived from Andrej Karpathy's observations on LLM coding pitfalls
The repository influenced how this project thinks about coding-agent instruction design, especially turning repeated failure modes into reusable, reviewable workflow guidance.
View repository