---
title: AI-DLC vs Agile
description: How AI-DLC compares to traditional Agile methods
---

## Side-by-Side Comparison

| Aspect | Agile/Scrum | AI-DLC |
|--------|-------------|--------|
| **Iteration Duration** | Weeks (Sprints) | Hours/Days (Bolts) |
| **Who Drives** | Human-driven, AI assists | AI-driven, human-validated |
| **Design Techniques** | Out of scope | Integrated (DDD in construction bolts) |
| **Task Decomposition** | Manual | AI-powered |
| **Phases** | Repeating sprints | Rapid three-phase cycles |
| **Rituals** | Daily standups, retrospectives | Mob Elaboration, Mob Construction |
| **Documentation** | Often neglected | Built-in artifacts |
| **Context Engineering** | Lost between sprints | Specs + Memory Bank |

## Iteration: Sprints vs Bolts

**Agile Sprints**

- **Duration**: 1-4 weeks
- **Planning**: Sprint planning ceremony
- **Execution**: Daily standups, continuous work
- **Review**: Sprint review, retrospective
- **Output**: Potentially shippable increment

**AI-DLC Bolts**

- **Duration**: Hours to days
- **Planning**: AI-powered decomposition
- **Execution**: Stage-gated progression
- **Review**: Human validation at each checkpoint
- **Output**: Validated, tested feature

## Role Inversion

### Traditional Agile

```mermaid
flowchart LR
    H1(Human):::plan --> P(Plans):::plan --> H2(Human):::plan --> E(Executes):::plan --> AI(AI assists):::build
    classDef plan fill:#fff,stroke:#6366F1,color:#4338CA,stroke-width:1.5px,rx:8,ry:8
    classDef build fill:#fff,stroke:#0EA5E9,color:#0369A1,stroke-width:1.5px,rx:8,ry:8
```

Humans drive the entire process. AI tools (copilots, assistants) help with specific tasks but don't lead.

### AI-DLC

```mermaid
flowchart LR
    H1(Human):::plan --> I(Defines Intent):::plan --> AI1(AI Proposes):::done --> H2(Human Validates):::check --> AI2(AI Executes):::done
    classDef plan fill:#fff,stroke:#6366F1,color:#4338CA,stroke-width:1.5px,rx:8,ry:8
    classDef done fill:#fff,stroke:#10B981,color:#047857,stroke-width:1.5px,rx:8,ry:8
    classDef check fill:#fff,stroke:#EC4899,color:#BE185D,stroke-width:2px,rx:8,ry:8
```

AI leads the conversation. Humans provide intent and validation. AI handles decomposition, planning, and execution.

## Design Techniques

<CardGroup cols={2}>
  <Card title="Agile Approach" icon="circle-question-mark">
    Design techniques like DDD are optional. Many teams skip them due to time pressure, leading to technical debt.
  </Card>
  <Card title="AI-DLC Approach" icon="check">
    Domain-Driven Design is built into DDD construction bolts. You can't skip Domain Modeling - it's a required gate.
  </Card>
</CardGroup>

## Bolt Types with Built-in Design

| Bolt Type | Best For | Stages |
|-----------|----------|--------|
| **DDD Construction** | Complex domain logic, business rules | Model → Design → ADR → Implement → Test |
| **Simple Construction** | UI, integrations, utilities | Plan → Implement → Test |

## Context Engineering

:::warning
One of the biggest challenges in traditional Agile is context loss between sprints. Knowledge leaves with team members, decisions aren't documented, and the codebase becomes a mystery.
:::

### AI-DLC Solution: Specs + Memory Bank

Specs and Memory Bank provide structured context for AI agents:

- All project artifacts (requirements, designs, decisions)
- Traceability between artifacts
- Context that agents can reload in any session

```
memory-bank/
├── intents/           # What we're building
├── bolts/             # How we built it
├── standards/         # Project decisions
└── operations/        # Deployment context
```

## When to Use Each

**Use Agile When**

- Team is not using AI coding tools
- Organization has established Agile processes
- Regulatory requirements mandate specific ceremonies
- Team prefers human-led planning

**Use AI-DLC When**

- Building with AI coding assistants
- Need rapid iteration cycles
- Want integrated design practices
- Building complex systems
- Context persistence is critical

## Migration Path

AI-DLC retains familiar concepts to ease transition:

| Agile Concept | AI-DLC Equivalent |
|---------------|-------------------|
| Epic | Intent |
| User Story | Story (within Unit) |
| Sprint | Bolt |
| Backlog | Intent/Unit definitions |
| Definition of Done | Checkpoint validations |