The Hidden Cost of Cheap Intelligence Is Review Debt
Review Debt is the accumulated cost of cheap model outputs requiring expensive review. The fix is boundary contracts upstream, not validators downstream.
Topic
ai-architecture
A collection of 39 issues
Code as Specification: Why the Schema Comes Before the Prompt
The central mistake in prompt engineering is treating prose as the primary specification. In production systems, the prompt should be downstream of the contract, not the other way around.
Red Teaming: Breaking Your Own Agent Before the Internet Does
Most teams call something a red team when they ask an LLM to be mischievous for ten minutes. Real red teaming is not prompt theater. It is a disciplined loop for breaking the runtime before production does it for you.
Human-in-the-Loop Is an Operating Model, Not a Safety Checkbox
Human-in-the-loop is an operating model: someone must own the policy, escalation thresholds, reviewer capacity, appeals, and the path to greater autonomy.
Judgment Compression: Who Owns the Expert Decisions Encoded in AI?
When AI ranks several valid options, it executes an organizational policy. Judgment compression works only when its decision rights and accountability are explicit.
The Agent Failure Bestiary: Sycophancy, Drift, and Recursion Loops
Most agent failures look novel when they happen. They are usually not. They belong to a small recurring bestiary of failure patterns that appear whenever stochastic systems are given too much authority and too little structure.
The Cognitive Firewall: PII Scrubbing Is Not a Feature. It's Part of the Runtime.
PII scrubbing is not a safety feature you bolt on later. If an LLM can see private data and untrusted instructions in the same token stream, your runtime boundary is already broken.
The Death of the Dashboard
Dashboards are a SaaS mental model. Professional services are push-based. The Acknowledgment Loop replaces dashboard analytics.
The Utilization Paradox: Why a 70B Model Can Be Cheaper Than an 8B Model
Most teams assume smaller models are cheaper by default. In production inference, that is often false. The real cost driver is utilization: how much useful work each GPU hour actually carries.
Why More Context Can Make an LLM Worse
The default response to agent failure is to stuff more context into the prompt. That often makes the system worse. A context window is working memory, not a hard drive.