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The DreamerOS Reading Room

The papers, repos, and guides we cite when we build.

01

Papers

The papers we point teams to when they ask how the constellation actually works.

Building Effective AI Agents

Anthropic, 2024

The clearest writeup of when to reach for a workflow versus an agent. The whole DreamerOS engine-selection layer is downstream of this distinction.

Agents Companion

Google, 2024

The complement piece. Patterns for tool use, memory, and multi-agent coordination at production scale.

ReAct: Synergizing Reasoning and Acting in Language Models

Yao et al., 2022

The pattern most modern agents are still running. Reason about the next action, take it, observe, repeat.

Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

Wei et al., 2022

Why "think step by step" started showing up everywhere. The paper that made reasoning a first-class prompt structure.

Tree of Thoughts: Deliberate Problem Solving with LLMs

Yao et al., 2023

Branching beats linear when the problem has more than one promising path. The intellectual ancestor of Mind-Eye depth calibration.

Reflexion: Language Agents with Verbal Reinforcement Learning

Shinn et al., 2023

Agents that reflect on their own failures and update. The core idea inside IFP-Verify and the receipts log.

Retrieval-Augmented Generation Survey

Gao et al., 2023

The honest tour of RAG. What works, what does not, where most teams over-engineer it.

02

Repos

The code we read first when we want to learn how a piece of the stack actually behaves.

Anthropic Claude API examples

anthropics/anthropic-cookbook

Working code for tool use, prompt caching, batch, citations, and vision. Read before you build.

OpenAI Cookbook

openai/openai-cookbook

The reference patterns for function calling, embeddings, and assistants. Useful even if you do not ship on OpenAI.

LangChain

langchain-ai/langchain

The framework you should read to understand the abstractions, then decide whether you want them.

LlamaIndex

run-llama/llama_index

The retrieval-first cousin to LangChain. Strong on data connectors and indexing primitives.

MCP servers reference

modelcontextprotocol/servers

Reference implementations for Model Context Protocol servers. The plumbing that makes tool use portable across engines.

03

Guides

The long-form writeups we hand to teams who want one document to read this weekend.

Building Effective Agents

Anthropic engineering blog

The companion essay to the agents paper. The framing we keep coming back to.

Claude Code Best Practices

Anthropic

How to use Claude Code without wasting tokens on the wrong things. The CLAUDE.md and skills pattern starts here.

A Practical Guide to Building Agents

OpenAI

The other side of the same coin. Good on evaluation, less opinionated than Anthropic's piece.

Agent Whitepaper

Google

The most enterprise-shaped of the three. Strongest on planner-executor architectures and orchestration.

DreamerAI Methodology

DreamerAI, internal

The six lenses we put on every engagement. Reverse Math, Sideways Thinking, Triple-I, Anti-Slop Check, Triangulation, Fingerprint Portability.

04

Books

The longer reads. Worth a flight, worth a weekend.

Understanding Deep Learning

Simon J.D. Prince

The textbook to read if you want to stop nodding at words like transformer and start understanding them.

AI Engineering

Chip Huyen

The book on building production AI systems. Evaluation, deployment, monitoring, the boring parts that decide whether you ship.

Designing Machine Learning Systems

Chip Huyen

The predecessor. Same author, same discipline, more on data and training pipelines.

05

Videos and Talks

The talks worth the hour. Bring coffee.

Stanford CS25: Transformers and Agents

Stanford University lecture series

The graduate seminar that keeps inviting the people who built the systems to come explain them.

Anthropic interpretability talks

Anthropic research

The clearest public window into how a frontier lab thinks about what is going on inside the model.

Intro to Large Language Models

Andrej Karpathy

The one-hour talk we send to every new client. Still the best plain-English explainer of the stack.

We update this monthly.

Bookmark it. The list moves as the field moves.

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