44za12
Philosophy: Brutally Efficient
More: https://aazar.me
Horcrux – Distributed, Zero-Trust Secret Manager
Lattice Deduction Transformers
MiniMax M3
Δ-Mem: Efficient Online Memory for Large Language Models
Beyond Semantic Similarity
Here’s the more honest one i wrote a while back:
In Defense of Boring Technology
Show HN: RightSize CLI, Find the cheapest LLM that works for your prompt
https://github.com/NehmeAILabs/rightsize-cli
RightSize runs your prompt against candidate models (Kimi, GLM, Qwen, Gemma etc.) in parallel via OpenRouter. Then it uses a stronger model as a Judge to score accuracy against a baseline model.Happy to answer questions.
I map them by task type:
Tiny (<3B): Gemma 3 1B (could try 4B as well), Phi-4-mini (Good for classification). Small (8B-17B): Qwen 3 8B, Llama 4 Scout (Good for RAG/Extraction). Frontier: GPT-5, Llama 4 Maverick, GLM, Kimi
Is that what you meant?
Show HN: LLM Sanity Checks – A practical guide to not over-engineering AI
https://github.com/NehmeAILabs/llm-sanity-checks
I keep seeing teams use frontier models for tasks a regex or a 4B model could do cheaper and faster.This repo is a collection of opinionated patterns and heuristics to help you rethink the architecture of your AI workflows and ease the decision-making process while ensuring maximum efficiency.It covers:- A decision tree for architectural sanity checks. - Tradeoffs between JSON and...
Stop using JSON for LLM structured output
FlashCheck-270M: Open weights for fact verification (Apache 2.0, WASM Demo)
I’ve been using a cli tool i had created for over 2 years now, it just works. I had more ideas but never got to incorporate those.