---
title: "AI Coding Taxonomy & Agent Experience"
description: "Core vocabulary and operational taxonomy for AI coding agents, attention dynamics, developer/agent experience (DX/AX), and execution modes."
section: "concepts"
type: "concept"
created: "2026-08-27"
updated: "2026-08-27"
confidence: "high"
tags: ["agents", "context-engineering", "coding-guidelines", "workflow", "principle"]
canonical: "https://pyweb.dev/wiki/ai-coding-taxonomy"
---
# AI Coding Taxonomy & Agent Experience

A rigorous, standardized vocabulary for reasoning about AI models, harnesses, attention dynamics, collaboration modes, and developer/agent experience, compiled from [matt pocock](/wiki/matt-pocock)'s AI Hero curriculum.

```mermaid
flowchart TD
    subgraph ModelLayer [1. Model & Inference Layer]
        M[Model / Parameters] -->|Inference| P[Next-token prediction]
        P --> TOK[Input / Output / Cache Tokens]
        P --> PR[Prefix Cache]
    end

    subgraph AttentionLayer [2. Attention Dynamics]
        TOK --> AR[Attention Relationship: ~N² pairs]
        AR --> AB[Attention Budget per Token]
        AB -->|Context Accumulation| AD[Attention Degradation]
        AD --> SZ[Smart Zone vs Dumb Zone]
    end

    subgraph HarnessLayer [3. Harness & Environment]
        H[Harness / System Prompt] -->|Manages| C[Context Window]
        H -->|Tool Call| ENV[Environment / Filesystem]
        ENV -->|Tool Result| H
        H -->|Permissions / Modes| SB[Sandbox]
    end

    subgraph LifecycleLayer [4. Context Lifecycle & State]
        C --> CL[Clearing]
        C --> HA[Handoff Artifacts: Spec & Ticket]
        C --> CP[Compaction / Autocompact]
        C --> MS[Memory System]
    end

    subgraph ExperienceLayer [5. Experience & Interaction Modes]
        DX[DX: Developer Experience] <--> AX[AX: Agent Experience]
        HITL[Human-in-the-loop] <--> AFK[AFK Unattended]
        VC[Vibe Coding] <--> HR[Human Review / Diffs]
    end
```

## 1. Model, Inference, and Attention Dynamics

- **Model vs Harness:** A model represents the frozen parameters (weights) tuned during training that performs stateless next-token prediction. It cannot act agentically alone. The [harness](/wiki/agent-harness-engineering) surrounds the model with tools, system prompts, context-window management, permissions, and hooks.
- **Inference & Token Accounting:** Running a model generates output tokens from input tokens. Consecutive requests sharing prefixes leverage provider-side **prefix caches**, billing those tokens as discounted cache tokens.
- **Attention Relationships:** In a context of $N$ tokens, approximately $N^2$ attention relationships exist between token pairs. Because each token has a finite **attention budget** to distribute across the context, adding tokens dilutes attention.
- **Attention Degradation & Smart Zone:** As context accumulates, each token's attention budget spreads across competing tokens, causing signal on critical relationships to shrink (**attention degradation**). This defines the [smart zone](/wiki/smart-zone) early in a session versus the sloppier "dumb zone" later in extended sessions.
- **Parametric vs Contextual Knowledge:** Parametric knowledge is frozen in weights at the **knowledge cutoff** date; contextual knowledge consists of facts loaded directly into the context window.
- **Sycophancy vs Hallucination:** Sycophancy is confidently agreeable output shaped by RLHF preferences; hallucination represents confidently-wrong output divided into factuality (invented facts) and faithfulness (drift from loaded context).

## 2. Interaction Modes & Experience (DX vs AX)

- **DX (Developer Experience):** How easy a codebase and toolchain make it for humans to do good work (documentation, feedback speed, error clarity).
- **AX (Agent Experience):** How well the environment is configured for an AI agent to do good work—deterministic checks, deep module architecture, and easily retrieved context without prompt bloat.
- **Human-in-the-Loop vs AFK:**
  - **Human-in-the-loop:** Pairing with an agent in real time, reviewing diffs, and redirecting.
  - **AFK (Away From Keyboard):** Unattended execution where an agent works autonomously against automated validation suites.
- **Human Review vs Vibe Coding:**
  - **Human Review:** Reading and judging the actual code diff produced by the agent.
  - **Vibe Coding:** Accepting code without inspecting diffs, treating generated output as opaque.
- **Automated Check vs Automated Review:**
  - **Automated Check:** Deterministic pass/fail verification in the environment (tests, lints, typechecks, build).
  - **Automated Review:** Non-deterministic evaluation where another agent inspects code and exercises judgment.

## 3. Context Lifecycle and Handoff Mechanics

- **Stateless vs Stateful:** Models are stateless across requests; agents are stateless across sessions by default unless persistence mechanisms are added.
- **Progressive Disclosure & Context Pointers:** Loading only necessary context upfront while leaving **context pointers** (mentions pointing to external documents or skills) for on-demand loading.
- **Clearing vs Compaction:**
  - **Clearing:** Ending a session to restart with an empty context window (`/clear`).
  - **Compaction:** In-memory summarization of past history seeding a fresh session, trading fidelity for headroom.
- **Handoff Artifacts (Specs & Tickets):** Structured documents bridging work across session boundaries. A **spec** scopes multi-session architecture; a **ticket** scopes one bounded session.

## Related Concepts

- [context engineering](/wiki/context-engineering)
- [smart zone](/wiki/smart-zone)
- [context rot](/wiki/context-rot)
- [agent harness engineering](/wiki/agent-harness-engineering)
- [agents md spec](/wiki/agents-md-spec)
- [handoff artifacts](/wiki/handoff-artifacts)
- [progressive disclosure](/wiki/progressive-disclosure)
- [matt pocock](/wiki/matt-pocock)

---

## Agent Navigation

cluster: person (170 pages) | betweenness: 126.7

### References (outbound)
- [Matt Pocock](https://pyweb.dev/wiki/matt-pocock.md)
- [Agent Harness Engineering](https://pyweb.dev/wiki/agent-harness-engineering.md)
- [Smart Zone](https://pyweb.dev/wiki/smart-zone.md)
- [Context Engineering](https://pyweb.dev/wiki/context-engineering.md)
- [Context Rot](https://pyweb.dev/wiki/context-rot.md)
- [AGENTS.md Specification](https://pyweb.dev/wiki/agents-md-spec.md)
- [Handoff Artifacts](https://pyweb.dev/wiki/handoff-artifacts.md)
- [Progressive Disclosure](https://pyweb.dev/wiki/progressive-disclosure.md)

### Evidence (verified primary sources)
- [aihero-ai-coding-dictionary-2026](https://pyweb.dev/wiki/raw/articles/aihero-ai-coding-dictionary-2026.md) | origin: https://www.aihero.dev/ai-coding-dictionary | ingested: 2026-08-27 | sha256: 52b0a5da7c9f6dd60dfdbf29031bcf6107c2765b6ef5b3a7f96cc607f42b06c7

### Machine endpoints
- Knowledge graph: https://pyweb.dev/api/graph.json
- Graph analysis: https://pyweb.dev/api/graph-analysis.json
- Context index: https://pyweb.dev/llms.txt