theaniketgiri

Hi HN — I'm Aniket, working on AIP.

As AI agents begin executing real-world actions (calling APIs, writing to databases, triggering workflows), there's currently no native identity or authorization layer for them.

AIP is an open protocol that gives every agent a cryptographic identity and requires actions to be signed and verified before execution.

The goal is simple: if an agent wants to act, the system should be able to verify who it is and what it's allowed to do — in milliseconds.

The repo includes a Python SDK, verification pipeline, and a decorator that can protect agent actions with a single line.

Curious to hear what the HN community thinks about identity and trust layers for autonomous systems.

Exactly — current platforms authenticate the account, but with agents the account isn’t the decision-maker anymore.

Two identical API calls can come from either intended behavior or a manipulated model, and today they look the same to the system. Permissions tied to a static identity don’t describe the real risk.

So the missing piece is verifying the agent’s declared intent and boundaries before execution, not just who sent the request.

That’s why this starts looking more like protocol infrastructure than a product feature.

Thanks a lot, really appreciate that Building something new always gets mixed reactions, but messages like yours keep me going.

Yeah, that’s how I see it too. LLMs are part of the toolkit now what matters is how you use them to actually ship something useful.

Yeah, I did! I trained a few small ones — mostly the “nano” and “tiny” templates (a few million params) on datasets like Shakespeare and Alpaca. The goal was to make sure the training loop, tokenizer, and evaluation all worked smoothly.

Didn’t go for massive models — more about making the whole setup process quick and reliable. You can actually train the nano one on CPU in a few minutes just to see it working.

Thanks everyone for the feedback and discussion. For those asking technical questions - happy to help! The tool works on Mac/Linux/Windows, check the README for setup. For those concerned about the architecture - it follows standard scaffolding patterns (create-next-app, etc). TypeScript CLI generates Python projects. 82+ stars in 24 hours - grateful for everyone trying it out. Keep the feedback coming!

Fair point I agree embedding code as strings isn’t ideal. I did it mainly to make npx create-llm portable without needing a Python setup during scaffolding. Definitely open to improving that happy to refactor if you have suggestions.

The Python-in-TS bit made me smile But to clarify, it’s a standard TypeScript CLI — no such hacks involved, just template-based generation.