Reading List
Created: 2025-06-16 00:00:00
Agents
- 12 Factor Agents- https://github.com/humanlayer/12-factor-agents/tree/main
- How to build an Agent - https://ampcode.com/how-to-build-an-agent
- How any agent works in 2025- https://x.com/NielsRogge/status/1945489588522250349
- How to Build an Agent or: The Emperor Has No Clothes, https://x.com/jxnlco/status/1947715035460927630
Voice AI
- Voice AI Guide - https://voiceaiandvoiceagents.com/
- Pipecat tutorial - https://x.com/sathvikdivili/status/1939404933192970473
- Evaluating voice agents - Hamel/Kwindla webinar
Multi-agent systems
- Anthropic – https://www.anthropic.com/engineering/built-multi-agent-research-system
- LangChain blog – https://blog.langchain.dev/how-and-when-to-build-multi-agent-systems/
Evals
- Evals are all we need – https://www.strangeloopcanon.com/p/evaluations-are-all-we-need
- Hrishi’s blog on evals - https://olickel.com/everything-about-evals
- Eugene’s Intro to Evals - https://x.com/eugeneyan/status/1937679133301178814
- Hamel’s Evals FAQ - https://hamel.dev/blog/posts/evals-faq/
- Rohit Krishnan’s blog – https://www.strangeloopcanon.com/p/notes-on-friction
- Bitter Lesson - http://www.incompleteideas.net/IncIdeas/BitterLesson.html
- Evals 101 - Doug Guthrie, Braintrust
Claude Code
Chorus uses CC- https://x.com/charliebholtz/status/1935029747815432505
CC Best practices - https://x.com/kieranklaassen/status/1935379089671770285
Mckay Wrigley - How To 10x Your Notes: Obsidian + Claude AI Agents - https://www.youtube.com/watch?v=d7Pb73dbcIM
Context Engineering - https://rlancemartin.github.io/2025/06/23/context_engineering/
LLMs
- Attention from Scratch - https://benjaminwarner.dev/2023/07/01/attention-mechanism
- Transformers from Scratch - https://peterbloem.nl/blog/transformers
Pretraining LLMs
- Pretraining LLMs: Lessons from Cohere, https://www.youtube.com/watch?v=Tv4xuIXwDMA
- Stanford CS25: V4 I Behind the Scenes of LLM Pre-training: StarCoder Use Case, https://www.youtube.com/watch?v=jm2hyJLFfN8
RL
- State of RL for LLM Reasoning - https://magazine.sebastianraschka.com/p/the-state-of-llm-reasoning-model-training
- AI Engineer Workshop by Daniel Han- https://www.youtube.com/watch?v=OkEGJ5G3foU&list=PLcfpQ4tk2k0V16VYYwnwF2g-EsKRIkJaC&index=7
- How to Train Your Agent: Building Reliable Agents with RL — Kyle Corbitt, OpenPipe, https://www.youtube.com/watch?v=gEDl9C8s_-4 and code at https://x.com/akseljoonas/status/1946904916242694579
Model Deepdives
- Kimi-K2 Tech report - https://github.com/MoonshotAI/Kimi-K2/blob/main/tech_report.pdf
- Latent Space Kimi-K2 Tech Report (Full Breakdown /w Vibhu Sapra) - https://www.youtube.com/watch?v=VHwZa7lZhK8
- SmolLM v3- https://x.com/_lewtun/status/1942620294797222236
DsPy & Prompting
- https://saiyashwanth.tech/ai_playbooks/dspy_playbook
- https://saiyashwanth.tech/ai_playbooks/prompting_playbook
- A Guide to Hacking DSPy into doing Automatic System Prompt Optimization, https://x.com/MaximeRivest/status/1948024214763548883
Newsletters / Blogs
- Smartbear – https://longform.asmartbear.com/
- Simon Willison – https://simonwillison.net/
- Alex Strick van Linschoten – https://mlops.systems/
Books
- Building a LM from Scratch - Sebastian Raschka
- Alice’s Adventures in a differentiable wonderland, A primer on designing neural networks - Simone Scardapane
- The Hundred-Page Language Models Book - Andriy Burkov
Courses
- HF courses- https://huggingface.co/learn/llm-course/en/chapter12/1
- DeepLearning.ai short courses
- Stanford CS336 “Language Modeling from Scratch” | Spring 2025"