---
id: "framework-the-prerequisite-chain"
type: "framework"
source_timestamps: ["00:10:06", "00:10:17"]
tags: ["mental-models", "dependencies"]
related: ["concept-the-now-what-problem"]
sources: ["s08-real-problem-agents"]
sourceVaultSlug: "s08-real-problem-agents"
originDay: 8
---
# The Prerequisite Chain for Agent Performance

## Summary

A hierarchical model showing the dependencies required to achieve high agent performance. **You cannot skip to the top without fulfilling the foundational layers.**

## The chain (bottom → top)

### 1. Clarity of Intent (foundation)
The human must be able to articulate exactly what they expect the agent to do — in *triggerable, verifiable* language. See [[prereq-clarity-of-intent]].

### 2. Memory & Config (middle)
The intent must be translated into:
- Structured memory (databases like [[entity-openbrain-d8]])
- Configuration files (markdown — see [[concept-markdown-as-agent-os]])

### 3. Agent Performance (top)
Only when intent is clear *and* configuration is set can the agent actually perform tasks successfully.

## Why this matters

The entire market is currently trying to deliver layer 3 (agent performance) without layers 1 and 2 — that's [[concept-the-now-what-problem]] in framework form. The 'magic box' products (see [[claim-magic-box-agents-fail]]) skip the foundation and collapse.

## External validation

Bain estimates a $100B opportunity in P&C claims via genAI for validation, with 20–25% cost reduction — but **only post-configuration** of coverage checks and fraud models. Direct empirical support that the prerequisite chain holds in production deployments.

## Related
- [[framework-markdown-agent-os-architecture]]
- [[concept-the-enterprise-gap]]