Advanced Agents From First Principles

Build a Production AI Agent From First Principles: The Complete Reference Architecture

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 20: Can Your Agent Coordinate Across Machines Without Duplicating Work? Use Leases, Idempotency and Fencing

Advanced Agents From First Principles 19: Can Your Agent Explore in Parallel Without Creating Chaos? Use Speculative Execution and Early Cancellation

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.

Advanced Agents From First Principles 08: Is Your Agent Spending the Same Compute on Every Task? Build Adaptive Agents That Escalate Only When Needed

Advanced Agents From First Principles 25: Can You Reproduce an Agent Run Months Later? Add Deterministic Replay and Provenance

Advanced Agents From First Principles 26: Why Did the Agent Fail? Build an Incident Forensics Pipeline

Advanced Agents From First Principles 27: How Reliable Does an Agent Need to Be? Define SLOs and Error Budgets

Advanced Agents From First Principles 28: Where Should You Spend the Next Engineering Hour? Prioritize Reliability by Risk and Expected Return

Advanced Agents From First Principles 29: When Should an Agent Stop and Ask a Human? Design Authority Boundaries and Escalation

Advanced Agents From First Principles 30: Is This Task Outside Your Agent’s Competence? Build Competence Envelopes and OOD Detection

Advanced Agents From First Principles 31: How Can an Agent Learn New Capabilities Without Expanding Its Own Authority? Use Sandboxed Capability Acquisition

Advanced Agents From First Principles 32: Which Capabilities Are Actually Worth Building? Design a Capability Portfolio

Advanced Agents From First Principles 33: Which Shared Components Actually Unlock More Capability? Build a Capability Dependency Graph

Advanced Agents From First Principles 34: Where Should This Task Actually Run? Build Capability-Aware Placement Across Models, Providers and Resource Pools

Advanced Agents From First Principles 35: How Do You Move a Running Agent Between Workers Without Losing Meaning? Build Portable Execution State and Safe Handoff

Advanced Agents From First Principles 36: Is Your Agent Acting on Stale State? Build Temporal Consistency, Freshness Budgets and Conflict Detection

Advanced Agents From First Principles 37: Is Your Agent Still Solving the Right Task? Build Intent Versioning, Supersession and Cancellation

Advanced Agents From First Principles 38: A Plan Is Not a Commitment — Model Goals, Commitments and Executable Work

Advanced Agents From First Principles 39: How Do You Make an Agent Survive for Days? Build Durable Long-Running Workflows

Advanced Agents From First Principles 40: Your Agent Changed the World. What Happens When Step Two Fails? Build Transactions, Compensation and Reconciliation

Advanced Agents From First Principles 41: What Should Your Agent Trust? Build Explicit Security and Trust Boundaries

Advanced Agents From First Principles 42: How Do Multiple Agents Coordinate Without Becoming a Distributed Argument?

Advanced Agents From First Principles 43: Who Controls the Agent? Build an Explicit Agent Control Plane

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 10: Are You Combining Every Agent Technique Into One Monster? Build a Mixture-of-Agents Runtime

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.

Advanced Agents From First Principles 06: Does One Agent Plan, Execute and Judge Its Own Work? Build a Planner-Executor-Critic Architecture

Advanced Agents From First Principles 05: Is One Model Doing Everything? Build a Mixture of Experts at the Agent Level

Advanced Agents From First Principles 04: Does Your Agent Prune Good Ideas Too Early? Use Monte Carlo Tree Search for Long-Horizon Reasoning

Advanced Agents From First Principles 03: Does Your Agent Commit to a Bad Reasoning Path Too Early? Build a Tree of Thoughts

Advanced Agents From First Principles 02: Why Does My Reasoning Agent Give a Different Answer Every Time? Use Self-Consistency Without Confusing Consensus With Truth

Advanced Agents From First Principles 01: Does Your AI Agent Fail on Complex Reasoning Tasks? Treat Chain of Thought as Computation, Not Proof

Advanced Agents From First Principles 00: When Should You Use an Advanced Agent Architecture?

Advanced Agents From First Principles 07: Do Your Agents Agree Too Easily? Use Adversarial Review and Multi-Agent Debate Without Confusing Debate With Truth