Sources

Every empirical claim in this book traces to one of the sources below. Read the primary literature. It is better than any summary of it, including this one. Sources 1 to 21 support parts 1 to 13. Sources 22 to 27 were added for the operating parts in the second edition.

1. Xia, Deng, Dunn & Zhang. "Agentless: Demystifying LLM-based Software Engineering Agents." FSE 2025. arXiv:2407.01489 · github.com/OpenAutoCoder/Agentless
2. Kapoor, Stroebl, Siegel, Nadgir & Narayanan (Princeton). "AI Agents That Matter." TMLR 2025. arXiv:2407.01502
3. Anthropic Engineering. "How we built our multi-agent research system." June 2025. anthropic.com/engineering/multi-agent-research-system
4. Cognition (Walden Yan). "Don't Build Multi-Agents." June 2025. cognition.ai/blog/dont-build-multi-agents
5. Cemri et al. (UC Berkeley). "Why Do Multi-Agent LLM Systems Fail?" (MAST). NeurIPS 2025 Datasets & Benchmarks. arXiv:2503.13657
6. Liu, Lin, Hewitt, Paranjape, Bevilacqua, Petroni & Liang. "Lost in the Middle: How Language Models Use Long Contexts." TACL 2024. arXiv:2307.03172
7. Hong, Troynikov & Huber (Chroma). "Context Rot: How Increasing Input Tokens Impacts LLM Performance." July 2025. research.trychroma.com/context-rot
8. Modarressi et al. (LMU Munich & Adobe). "NoLiMa: Long-Context Evaluation Beyond Literal Matching." 2025. arXiv:2502.05167
9. Cuconasu et al.. "The Power of Noise: Redefining Retrieval for RAG Systems." SIGIR 2024. arXiv:2401.14887
10. Edge et al. (Microsoft Research). "From Local to Global: A Graph RAG Approach to Query-Focused Summarization." 2024. arXiv:2404.16130
11. Microsoft Research. "GraphRAG: New tool for complex data discovery." July 2024. microsoft.com/research blog
12. Aider (Paul Gauthier). "Building a better repository map with tree-sitter" & repo-map docs. 2023 onward. aider.chat/2023/10/22/repomap.html · aider.chat/docs/repomap.html
13. Zhang, Ruan, Fan & Roychoudhury (NUS). "AutoCodeRover: Autonomous Program Improvement." ISSTA 2024. arXiv:2404.05427
14. Yang, Jimenez et al. (Princeton). "SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineering." NeurIPS 2024. arXiv:2405.15793
15. Jimenez et al.. "SWE-bench: Can Language Models Resolve Real-World GitHub Issues?" ICLR 2024. arXiv:2310.06770
16. Anthropic. "Prompt caching with Claude" (up to 90% cost and 85% latency reduction, and a cache read costs about 0.1 times the input price). 2024. anthropic.com/news/prompt-caching
17. Packer et al. (UC Berkeley). "MemGPT: Towards LLMs as Operating Systems." 2023. arXiv:2310.08560
18. Shannon, C.E. "A Mathematical Theory of Communication." Bell System Technical Journal, 1948. The original framework for signal and noise
19. Anthropic Engineering. "Effective context engineering for AI agents." 2025. anthropic.com/engineering
20. Anthropic Engineering. "Writing effective tools for agents." 2025. anthropic.com/engineering
21. Zhu et al.. "When to use Graphs in RAG: A Comprehensive Analysis for Graph Retrieval-Augmented Generation." 2025. arXiv:2506.05690
22. Rose, Borchert, Mitchell and Connelly (NIST). "Zero Trust Architecture." NIST Special Publication 800-207, 2020. doi.org/10.6028/NIST.SP.800-207
23. OWASP. "Top 10 for LLM Applications 2025," LLM06: Excessive Agency. genai.owasp.org
24. FinOps Foundation. "FinOps Framework," the Allocation capability. finops.org/framework
25. Model Context Protocol. Specification: servers, tools, and schemas. modelcontextprotocol.io/specification
26. Rundgren, Jordan and Erdtman. "JSON Canonicalization Scheme (JCS)." RFC 8785, 2020. rfc-editor.org/rfc/rfc8785
27. Beyer, Jones, Petoff and Murphy (eds.). "Site Reliability Engineering," chapter 15: Postmortem culture, learning from failure. O'Reilly, 2016. sre.google/sre-book