Advanced Agents From First Principles
Go beyond basic agent loops into orchestration, evaluation, reliability, multi-step reasoning, memory, and production-grade agent systems.
Apply this book: open the related solution paths →
Extend the first-principles agent model into the harder engineering problems that appear once agents become long-running, stateful, and operational.
Chapters
Advanced Agents From First Principles 24: How Do You Release Agent Behavior Safely? Add Behavioral Contracts, Compatibility Checks and Promotion Gates
Treat agent behavior like a production interface: define behavioral contracts, test compatibility across models, prompts, tools, memory, routers and verifiers, then promote changes through explicit release gates.
Advanced Agents From First Principles 23: Your Infrastructure Is Healthy. Why Is the Agent Getting Worse? Detect Behavioral Drift and Roll Back Safely
Learn how to detect silent behavioral regressions in agent systems caused by model, prompt, router, verifier, retrieval, policy and data-distribution drift, then roll back safely using evidence rather than intuition.
Advanced Agents From First Principles 22: What Happens When One Dependency Starts Failing? Add Circuit Breakers, Bulkheads and Graceful Degradation
Learn how to contain failing model, browser, retrieval, verifier, database and API dependencies with circuit breakers, bulkheads, bounded retries and graceful degradation.
Advanced Agents From First Principles 21: What Happens When Too Many Agents Compete for the Same Resources? Add Admission Control, Quotas and Backpressure
Learn how to schedule many concurrent AI agent runs across shared models, GPUs, browsers, tools and external APIs using admission control, quotas, fairness, priorities, reservations and backpressure.
Advanced Agents From First Principles 18: What Should Your Agent Observe Next? Use Expected Value of Information
Learn how to choose the next observation, diagnostic, retrieval, experiment, tool call, or verifier check by estimating how much it could change the agent's decision relative to its cost.
Advanced Agents From First Principles 17: What Is Your Agent Actually Uncertain About?
Stop treating agent confidence as one scalar. Decompose uncertainty into interpretation, evidence, routing, state, candidate, and verification uncertainty so the runtime can buy the right next action.
Advanced Agents From First Principles 16: Where Should an Agent Spend Its Compute? Build a Dynamic Budget Scheduler
Learn how to allocate model calls, search nodes, tool executions, verifier work, latency and money dynamically instead of relying on fixed agent budgets.
Advanced Agents From First Principles 15: How Do You Optimize an Agent Policy Without Turning It Into Another Black Box?
Learn how to optimize routing, search depth, escalation, model selection and stopping policies from verified trajectories while keeping the control layer small, interpretable and reversible.
Advanced Agents From First Principles 14: Can Your Agent Learn From Its Own Trajectories Without Learning the Wrong Lessons?
Learn how to turn verified agent trajectories into safer routing, search and budget policies without reinforcing the system's own mistakes.
Advanced Agents From First Principles 13: How Do You Debug an Agent That Made the Wrong Decision? Add Trajectory Observability
Learn how to debug advanced agent systems with decision lineage, trajectory traces, routing and pruning reasons, cost attribution, verifier evidence, replay, and failure localization.
Advanced Agents From First Principles 12: Is Your Advanced Agent Actually Better? Benchmark It Under Equal Budgets
Learn how to benchmark MCTS, Tree of Thoughts, self-consistency, debate, routing and adaptive agent systems without confusing extra compute with better architecture.
Advanced Agents From First Principles 11: Which Advanced Agent Architecture Should You Use? A Practical Selection Guide
A practical framework for choosing between self-consistency, Tree of Thoughts, beam search, MCTS, evolutionary search, specialist routing, debate, planner-executor-critic systems, adaptive agents and mixtures of agents.
You Probably Don't Need All of This: Build the Minimum Production Agent Architecture
The final lesson in Advanced Agents From First Principles: start with the smallest production agent that preserves authority, authoritative state, verification and traceability, then add complexity only when measured failures justify it.
Advanced Agents From First Principles 09: Can Your Agent Actually Learn From Previous Runs?
Learn how to turn verified agent trajectories into safer future policies without confusing memory with learning or poisoning the system with bad experience.