Hunter Brennick AI Systems & Advisory ↗
AI Systems Orchestration
Appendix/Further Reading

Further Reading

The shortest path from continuous improvement roots to AI native improvement loops. Read these in order. They are the spine behind Chapters 13 through 15.

9 annotated reads
01 AccelerateNicole Forsgren, Jez Humble, Gene Kim The measurement spine for modern software delivery: delivery performance, quality, and organizational capabilities. https://itrevolution.com/product/accelerate/ 02 Site Reliability Engineering or The Site Reliability WorkbookGoogle The operating model for production feedback loops: SLOs, error budgets, toil reduction, incident learning, and automation with guardrails. https://sre.google/books 03 "The Vision of Autonomic Computing"Jeffrey O. Kephart and David M. Chess The classic self-managing-systems paper. Read this for MAPE-K: monitor, analyze, plan, execute, knowledge. https://cir.nii.ac.jp/crid/1363951793518051840?lang=en 04 "Hidden Technical Debt in Machine Learning Systems"D. Sculley et al. The cautionary paper for AI-backed improvement loops. It explains why ML/AI systems accumulate hidden maintenance risk quickly. https://papers.nips.cc/paper/5656-hidden-technical-debt-in-machine-learning-systems 05 "MLOps: Continuous Delivery and Automation Pipelines in Machine Learning"Google Cloud The CI/CD/CT bridge: continuous integration, continuous delivery, continuous training, monitoring, and metadata. https://docs.cloud.google.com/architecture/mlops-continuous-delivery-and-automation-pipelines-in-machine-learning 06 "Building Effective Agents"Anthropic The modern agent engineering read. The useful takeaway: prefer simple workflows first, then add autonomy only where it earns its complexity. https://www.anthropic.com/research/building-effective-agents 07 OpenAI Evals / Agent Evals guides Evals are the proof layer for AI systems. Read these before trusting agents to modify prompts, workflows, tools, or platform behavior. https://platform.openai.com/docs/guides/evalshttps://platform.openai.com/docs/guides/agent-evals 08 Toyota Production SystemTaiichi Ohno The lean root: waste removal, flow, standard work, and improvement at the source. https://www.routledge.com/Toyota-Production-System-Beyond-Large-Scale-Production/Ohno/p/book/9780915299140 09 Out of the CrisisW. Edwards Deming The deeper quality-management root: improvement as a property of the system, not individual heroics. https://mitpress.mit.edu/9780262535946/out-of-the-crisis/

Continuous improvement is not autonomous mutation. It is a measured feedback loop that observes, diagnoses, proposes, sandboxes, verifies, and only then applies changes through a gate.

Pairs withChapter 13 · Learning Loops And Continuous Improvement How an AI system gets better after each run without pretending the agent should blindly rewrite itself.