Llm - AIBussin — AI applications, systems and books

What Context Means
Beyond the Chat Box
The Action Boundary
If There's Any Doubt, It's Deterministic
Advanced Agents From First Principles 24: How Do You Release Agent Behavior Safely? Add Behavioral Contracts, Compatibility Checks and Promotion Gates
Advanced Agents From First Principles 23: Your Infrastructure Is Healthy. Why Is the Agent Getting Worse? Detect Behavioral Drift and Roll Back Safely
Advanced Agents From First Principles 22: What Happens When One Dependency Starts Failing? Add Circuit Breakers, Bulkheads 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
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
Advanced Agents From First Principles 17: What Is Your Agent Actually Uncertain About?
Advanced Agents From First Principles 16: Where Should an Agent Spend Its Compute? Build a Dynamic Budget Scheduler
Advanced Agents From First Principles 15: How Do You Optimize an Agent Policy Without Turning It Into Another Black Box?
Advanced Agents From First Principles 14: Can Your Agent Learn From Its Own Trajectories Without Learning the Wrong Lessons?
Advanced Agents From First Principles 13: How Do You Debug an Agent That Made the Wrong Decision? Add Trajectory Observability
Advanced Agents From First Principles 12: Is Your Advanced Agent Actually Better? Benchmark It Under Equal Budgets
Advanced Agents From First Principles 11: Which Advanced Agent Architecture Should You Use? A Practical Selection Guide
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
You Probably Don't Need All of This: Build the Minimum Production Agent Architecture
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?
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?
Agents From First Principles 09: AI Agent Says It Worked When It Didn’t? Verify the Result Outside the LLM
Agents From First Principles 06: AI Agent Chooses the Wrong Tool? Design Better Tool Interfaces, Schemas and Routing
AI Agent Returning Invalid Tool Calls? How to Validate LLM Actions
Advanced Agents From First Principles 07: Do Your Agents Agree Too Easily? Use Adversarial Review and Multi-Agent Debate Without Confusing Debate With Truth
The “Negative Contrast Trap”: Why AI Writing Overuses “Not X, But Y”
From Photo Albums to Movies: Teaching AI to See Its Own Progress
A Novel Approach to Autonomous Research: Implementing NOVELSEEK with Modular AI Agents
Using Quantization to speed up and slim down your LLM