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I wrote the manual Karpathy said was missing for agentic AI

43 points| nick2837 | 1 month ago |github.com

41 comments

order

nick2837|1 month ago

I've been building with CLI AI agents (Claude Code specifically) for several months and noticed some powerful patterns emerging that have 10x’d my productivity.

Stuff like …

1. Morphability - natural language as executable, morphable code 2. Abstraction - encapsulating tasks into reusable commands 3. Recursion - stacking abstractions for leverage 4. Internal Consistency - the immune system of your AI system 5. Reproducibility - crash-resilient by design 6. Morphic Complexity - knowing when you've over-engineered 7. End-to-End Autonomy - what your system can do without human intervention 8. Token Efficiency - maximizing useful work per token 9. Mutation & Exploration - controlled self-improvement

Link: https://github.com/nicolasahar/morphic-programming

its free and i dont need anything from you except genuine feedback

also included system design patterns, psychological tips, and example commands :)

PaulHoule|1 month ago

You have source code for this kind of system?

MattDaEskimo|1 month ago

English - or better put: human language - is not the "new code". Since the inception of programming a person could ask another to write code.

This manual is hallucinated nonsense.

The only interesting part is how people uneducated in computers and mathematics always seem to fall into the topic of recursion with AI

nick2837|1 month ago

you can continue to believe in the old paradigm, or accept reality for what it is.

someone who abstracts themselves up will be able to move and ship 100x faster than you in the next 12 months.

npalli|1 month ago

LOL, this is the list to keep in your head for this so called "manual". Best of luck of those who will work through this. BTW, Karpathy made that comment in 2025 not 2024.

  Morphability - natural language as morphable code
  Abstraction - tasks become reusable commands
  Recursion - stack abstractions for leverage
  Internal Consistency - prevent system drift
  Reproducibility - crash-resilient design
  Morphic Complexity - recognize over-engineering
  E2E Autonomy - measure actual capabilities
  Token Efficiency - maximize work per token
  Mutation & Exploration - controlled self-improvement

jennyholzer3|1 month ago

AI in 2026 is really all about morphability.

If you aren't using multiple agents, subagents, and autonomous MCP abstractions to construct a detailed morphological model of your codebase, you'll never appreciate the sublime bliss of man-machine union that the enlightened among us here have come to know.

_air|1 month ago

It would be nice if there were a domain specific language that could help with the internal consistency problem

nick2837|1 month ago

i agree. it's still very early with AI programming in general, so this might evolve in the next few years

johnnyfived|1 month ago

Pls consider donating this to the Linux foundation and making tons of announcements about it.

Tag them in tweets too

nick2837|1 month ago

Thanks, will do that!

Havoc|1 month ago

Thanks for sharing

OutOfHere|1 month ago

No. Just no. You wrote a manual for using AI for software development is all, limited to a specific approach.

You did not write a manual for applying agentic AI more broadly and generally, which is what it is about. You completely missed the mark.

nick2837|1 month ago

right at the top of Part 2: "The examples I give are going to be software engineering/coding specific, but they can be applied to any digital task."

you can genuinely use these principles for anything you want to do on your computer. I don't just use Claude Code for programming.