resources

Index

• README

• blog-ideas/2026/ideas/202608-how-do-MOE-LLM-models-work/how-do-MOE-LLM-models-work

• blog-ideas/2026/ideas/202608-jeff-dean-google-trends-in-AI/1-jeff-dean-trends-in-AI-summary

• blog-ideas/2026/ideas/202608-jeff-dean-google-trends-in-AI/2-jeff-dean-trends-in-AI-interpretation

• blog-ideas/2026/ideas/202608-logical-vs-physical-architecture/1-architecture-terminology-reddit-summary

• blog-ideas/2026/ideas/202608-logical-vs-physical-architecture/2-preferred-mental-model

• blog-ideas/2026/ideas/202608-logical-vs-physical-architecture/3-resources

• blog-ideas/2026/ideas/202608-logical-vs-physical-architecture/4-blogpost-search-pipeline-logical-architecture

• blog-ideas/2026/ideas/202608-veritasium-success/1 Summary of Veritasium - why he still gets views

• blog-ideas/2026/ideas/202608-veritasium-success/2 Concrete example of Veritasium formula

• blog-ideas/2026/ideas/202608-veritasium-success/3 Veritasium skill

• blog-ideas/2026/wip/Red-teaming agentic LLMs/dr/DR - A Pragmatic Engineer’s Guide to Defending Agentic LLM Systems

• blog-ideas/2026/wip/Red-teaming agentic LLMs/raw/blogpost

• blog-ideas/2026/wip/Red-teaming agentic LLMs/raw/outline

• blog-ideas/2026/wip/Red-teaming agentic LLMs/raw/publishing

• blog-ideas/2026/wip/Red-teaming agentic LLMs/raw/references

• blog-ideas/2026/wip/Red-teaming agentic LLMs/raw/repos

• books/The Oxford Handbook of Philosophy of Mathematics and Logic (Shapiro, 2005)/summary_gemini-2.5-flash

• books/The Oxford Handbook of Philosophy of Mathematics and Logic (Shapiro, 2005)/summary_gpt5_std

• deep-research/js-simulation/DR - Modern JavaScript Libraries for Browser Games, Graphics, Simulation, CAD_BIM and Scientific Visualis

• index/list_all

• ml/Agentic AI

• ml/Data Attribution

• ml/Deep Research

• ml/Foundational Models

• ml/Free Energy Principle

• ml/Geometric Deep Learning (GDL)

• ml/LLM Evaluation

• ml/LLM Training

• ml/Prompt Optimisation

• ml/Representation Engineering

• ml/Search and IR

• ml/WIP AI Explainability

• ml/WIP LLM Inference

• ml/WIP Mechanistic Interpretability

• ml/WIP Model Calibration

• ml/WIP Model Context Protocol

• ml/WIP Retrieval-Augmented Generation (RAG)

• refs/coding-assistants/CLAUDE_CODE

• refs/coding-assistants/CURSOR

• refs/coding-assistants/GENERAL

• refs/coding-assistants/HARNESS_ENGINEERING

• refs/coding-assistants/OPENAI_CODEX

• refs/coding-assistants/SKILLS

• refs/coding-assistants/SPEC_DRIVEN_DEV

• refs/coding-assistants/USEFUL_PROMPTS

• study/LLM Study

• study/interactive-theorem-proving/INTRO

• study/interactive-theorem-proving/LEAN_RESOURCES

• study/interactive-theorem-proving/dr/intro/dr-lean4-intro-gemini-flash

• study/interactive-theorem-proving/dr/intro/dr-lean4-intro-gpt5.5

• study/interactive-theorem-proving/dr/intro/dr-lean4-intro-opus4.8

• study/interactive-theorem-proving/dr/intro/prompts/deepresearch

• summaries/202605/math-gowers.wordpress.com-2026-05-08-a-recent-experience-with-chatgpt-5-5-pro