Tag
This article by yan5xu (former ManusAI) proposes a spiral evolution model for LLM engineering paradigms: from Prompt Engineering (2022-2024) to Context Engineering (2025), then to Harness Engineering (2026-), and discusses the bottlenecks and driving factors at each stage.
A page from Modal's LLM Engineer's Almanac that provides an interactive explorer for understanding low-precision floating-point formats like bf16 and fp4.
A free, open-source 8-week hands-on LLM engineering course by Ed Donner, featuring weekly projects and covering topics like Ollama, Llama 3.2, and AI coding tools.
The article discusses Andrej Karpathy's advice on leveraging LLMs despite their cognitive deficits, highlighting a case study where custom configuration (CLAUDE.md) significantly reduced error rates.
This article outlines a 2026 roadmap for LLM engineering, detailing eight key pillars including prompt engineering, RAG systems, and context management, while providing curated free and open-source resources for each.
A project-based roadmap for learning LLM engineering by building key components from tokenizers to serving stacks, including hardware foundations and post-training techniques.
Anthropic publishes engineering guidelines for building effective AI agents, advocating for simple, composable patterns and direct API usage over complex frameworks. The article distinguishes between workflows and autonomous agents, providing practical advice on when to use each architecture.