[ Blog_Posts ]

Your AI Bill Is a Distributed Systems Problem, Not a Model-Pricing Problem

When the monthly LLM bill jumps several times over, the first instinct is that the model got more expensive or usage simply grew. It is almost always something else: a distributed systems failure mode, retry storms, fanout amplification, cache misses, unbounded conversation growth, that happens to be denominated in tokens instead of network calls. Debug the call graph, not the model price.

2026-08-04 Harrison Guo 9 min read generative-ai cost distributed-systems observability reliability system-design ai-agent first-principles

Validation Is a Loop, Not an Assertion: Why Your AI Agent Reports Success It Never Achieved

The most common production AI agent failure is treating validation as an assertion, a one-shot pass/fail check, instead of a loop that validates, scores, and decides whether to accept, retry, or escalate. Deterministic code can assert. Non-deterministic model output needs a closed loop, or your agent will report success while doing the wrong thing.

2026-07-28 Harrison Guo 10 min read generative-ai ai-agent validation system-design reliability closed-loop llm-as-judge first-principles eventual-consistency

A Wrong Ruler Is Worse Than No Ruler: Verifying the Checks You Trust

In a rules-first AI system, the deterministic checks get authority. They gate output and overrule the model judge. But a wrong check with authority is worse than no check at all. A first-principles standard for verifying the ruler before you trust it.

2026-07-17 Harrison Guo 11 min read generative-ai system-design reliability evaluation llm-as-judge rules-engine calibration metrics verification first-principles neuro-symbolic

Determinism Where You Can, Judgement Where You Must: The Technique Boundary for AI Systems

Every part of an AI system has exactly one right home: a rule, a state machine, or a bounded judge. Control belongs to the orchestrator, not to an autonomous loop. A first-principles boundary for deciding which technique owns which part.

2026-07-09 Harrison Guo 18 min read generative-ai system-design reliability llm-as-judge rules-engine state-machine ai-agents neuro-symbolic first-principles verification evaluation

Shrink the Stochastic Surface: A Design Standard for Probabilistic Systems

The reliability of a probabilistic system is set by how much of it you let the model decide. A first-principles standard for shrinking the stochastic surface, on the generation side and the evaluation side.

2026-06-24 Harrison Guo 13 min read generative-ai system-design reliability retrieval-augmented-generation fine-tuning evaluation llm-as-judge rules-engine neuro-symbolic first-principles verification

Generative AI Builds Shapes, Not Games: The Constraint Gap and the Architecture That Closes It

Generative AI nails plausible shapes but misses constraints, composition, and verification. A first-principles read of the gap, and the architecture that closes it.

2026-06-20 Harrison Guo 12 min read generative-ai text-to-3d game-development procedural-generation neuro-symbolic constraint-satisfaction minecraft higgsfield ai-limitations first-principles verification

I Tested Higgsfield's Minecraft 'Prompt-to-Build.' It Generates Shapes, Not Scenes.

I ran eight building prompts through Higgsfield's Minecraft prompt-to-build. It nails single shapes in a minute but drops exact sizes, materials, doors, and whole scenes.

2026-06-18 Harrison Guo 11 min read higgsfield minecraft ai-tool-evaluation generative-3d text-to-3d voxel prompt-to-build ai-benchmark hands-on-review

Agent Architecture Is a Compute Allocation Problem: The Advisor Strategy, Cost-Curve Frame Recursed

Anthropic named the advisor strategy in April. Tobi Lutke made it viral in May with Qwen plus GPT-5.5. Stanford's HazyResearch formalized the same shape earlier. One cost-curve frame unifies all three: a cheap executor runs the loop, an expensive advisor weighs in only at hard decisions. The third recursion.

2026-06-15 Harrison Guo 21 min read claude-code ai-agent advisor-strategy anthropic tobi-lutke qwen cost-curve model-orchestration first-principles distributed-systems agent-architecture

Agent Retrieval Above the Crossover: A First-Principles Read of CodeGraph

CodeGraph is the LLM-symbol-graph my prior retrieval post argued should exist. Read against its own SQLite index: why its architectural choices are right, and where the abstraction leaks.

2026-06-08 Harrison Guo 25 min read claude-code codegraph ai-agent retrieval symbol-graph tree-sitter mcp sqlite fts5 first-principles distributed-systems abstraction-leaks

I Tested CodeGraph on Hono. The Tool-Call Savings Reproduce — the Cost Savings Don't.

Independent CodeGraph benchmark on Hono (~280 TS files): -55% tool calls reproduces the published claim, but cost is a wash (+7%), not -35%. Raw CSV included.

2026-06-01 Harrison Guo 19 min read claude-code codegraph ai-agent retrieval benchmark hono mcp tree-sitter claude-code-cost ai-tool-evaluation cost-curve

[ Blog_Posts ]

[ Connect_With_Me ]