practice guides (best/worst): 22 curated resources
practice guides (best/worst)
22 resources · page 1 of 1
12-Factor Agents (humanlayer)
by HumanLayer
12-Factor Agents GitHub repo (HumanLayer): principles for building reliable LLM-powered software.
a16z AI
Andreessen Horowitz AI page collecting the firm's essays, market maps and podcasts on AI infrastructure and applications.
Ahead of AI
Sebastian Raschka's Ahead of AI newsletter on LLM research, architectures and training.
Answer.AI
by Answer.AI
Answer.AI: R&D lab building practical AI products and open-source tools from research.
宝玉 baoyu.io
Baoyu's Chinese blog on LLMs, prompt engineering and software engineering.
Chip Huyen blog
by Chip Huyen
Chip Huyen's blog: posts on AI engineering, agents and ML system design.
Сиолошная (Telegram web preview)
by Сиолошная (Telegram web preview)
Web view of the Сиолошная Telegram channel by Igor Kotenkov: Russian-language news and analysis on NLP and AI.
Every: Chain of Thought
by Every
Every's Chain of Thought column on AI tools and their use.
Lenny's Newsletter (AI product)
Lenny's Newsletter: product, growth and career writing for product managers and founders, including AI product topics.
levelsio blog
Pieter Levels' blog on bootstrapping solo internet businesses, including AI products.
Mitchell Hashimoto writing
Mitchell Hashimoto's writing index, including posts on AI-assisted programming practice.
Peter Steinberger blog
Peter Steinberger's blog on building AI-powered developer tools, creator of OpenClaw.
Sebastian Raschka
Sebastian Raschka's blog archive: posts on LLMs, AI research and PyTorch.
AI in 2025: Building Blocks Firmly in Place (Sequoia Capital)
Sequoia Capital essay on the state of AI in 2025, covering foundation models, applications and market structure.
AIAAIC Repository
by AIAAIC
AIAAIC Repository: independent register of AI incidents and controversies with case entries.
CS自学指南 csdiy.wiki
by csdiy.wiki community (PKUFlyingPig)
CS自学指南 (csdiy.wiki): Chinese self-study map of computer science courses, including ML systems and LLM courses.
Illustrated Transformer (Alammar)
by Jay Alammar
Jay Alammar's Illustrated Transformer: visual explanation of attention and the transformer architecture.
LLM Visualization (bbycroft)
LLM Visualization by Brendan Bycroft: interactive 3D walkthrough of GPT-style inference step by step.
Transformer Explainer (Georgia Tech)
by Polo Club of Data Science, Georgia Tech
Georgia Tech Transformer Explainer: interactive in-browser visualisation of how a GPT-2 transformer works.
Habr ML hub
by Habr
Habr machine learning hub: Russian-language articles on ML from practitioners and companies.
Why Do Multi-Agent LLM Systems Fail?
by Mert Cemri et al. (UC Berkeley)
arXiv paper (2025) analysing why multi-agent LLM systems fail, with a taxonomy of 14 failure modes.
Convex Optimization
by Stephen Boyd and Lieven Vandenberghe (Stanford University)
Boyd and Vandenberghe's Convex Optimization book site with free PDF, slides and exercises.