llm-engineering

Open-source implementation of AlphaEvolve

OpenAlpha_Evolve is an open-source Python framework inspired by the groundbreaking research on autonomous coding agents like DeepMind's AlphaEvolve.

Learn LLM Inference Engineering step by step - from KV cache, PagedAttention, and continuous batching to vLLM, SGLang, and GPUs.

200+ AI, Gen AI, LLM, agentic AI, Forward Deployed Engineer (FDE), AI systems architect, applied AI, LLMOps and AI platform engineering interview questions across 10 topics. Each has a short answer, in-depth detail, a worked example and interview tips.

LLM Engineering Claude Skills

An experiment-driven LLM engineering lab with 9 reproducible Python experiments exploring token economics, API costs, caching, context growth, latency, model routing, rate limits, concurrency, and batching using Groq.

Open course on LLM engineering and customization, in Portuguese, from scratch to production, with reproducible labs.

Burgonet Gateway is an enterprise LLM gateway that provides secure access and compliance controls for AI systems

Live-updating tracker of prompt engineering tools, libraries, and techniques — refreshed every 15 mi

Timeless principles and best practices for working with language models - tooling-agnostic, future-proof, and clear.

Build software with AI agent teams that use fewer tokens than a single agent.

Complete hands-on Agentic AI bootcamp repository covering LangGraph, LangChain, AI Agents, multi-agent workflows, RAG pipelines, tool-augmented LLM systems, memory architectures, and production-grade AI application engineering for real-world intelligent systems.

This course provides a comprehensive guide to mastering AI, focusing on Large Language Models (LLMs) and agents. It covers essential concepts, practical coding exercises, and comparisons of leading LLMs to equip participants with the skills needed to build and deploy LLM-based solutions.

Everything you need to learn Claude Code: deep notes, real assignments, working solutions. From agentic loops to parallel multi-agent systems.

A human–AI collaboration framework that works with LLM nature, not around it — natural language and purpose make RAG and agent orchestration unnecessary. Home of the Pang Principle.

A proactive AI assistant using Qwen-Agent to learn your writing style and manage Google Calendar & Gmail.

AI PDF Assistant that extracts, chunks, and answers questions grounded strictly in an uploaded document — with built-in hallucination control. Week 3 of a 90-day AI Engineering roadmap.

DSSential is an advanced decision support system that leverages AI, time series forecasting, and scenario analysis to empower businesses with data-driven insights and optimization. Make smarter decisions with cutting-edge tools for forecasting, sensitivity analysis, and goal setting.

A decision-oriented LLM engineering knowledge base — from Attention to production. 291 cards, 36-card path: fundamentals, RAG, Agents, and shipping.