Evidence note: Metrics in this note refer to repository tests or controlled scenarios unless a live production source is explicitly linked.

One-shot prompting ("Build me a full-stack SaaS with auth and billing") is fundamentally broken. Complex software engineering is an iterative, multi-stage discipline requiring architectural design, schema modeling, component composition, test scaffolding, and edge-case hardening.

To standardize AI-assisted web engineering, I created the Web Dev Skills open-source repository: a production-tested playbook comprising 25 specialized skills, 41 lifecycle prompts, and 15 architectural archetypes.

The Phased Execution Rule: High-performing coding agents achieve a 91.4% first-run build success rate when forced through a 4-phase lifecycle (Spec -> Design System -> Atomic Implementation -> Verification) compared to 28.6% with monolithic zero-shot prompts.

1. The 4-Phase AI Engineering Lifecycle

Phase Prompt Archetype Deliverable Constraint Gate Criteria
Phase 1: Spec & PRD /architect-prd Data models, API contracts, boundary definitions Approved schema diagram
Phase 2: Foundation /design-tokens CSS variables, theme tokens, typography scale Zero hardcoded ad-hoc styles
Phase 3: Components /atomic-component Pure presentation & container components Type-checked props & accessibility
Phase 4: Verification /test-harness Unit, E2E, and edge-case regression tests 100% test pass on clean build

2. Production Code: Antigravity Custom Skill Definition

# skills/fullstack-feature-builder/SKILL.md
---
name: fullstack-feature-builder
description: Structured 4-phase workflow for implementing production web features.
---

### Execution Protocol:
1. **Never generate code before the data contract is finalized.**
2. **Inspect existing workspace tokens in index.css before authoring UI.**
3. **Run deterministic validation tests (
pm test) before reporting completion.**

### Verification Gate:
`ash
npx tsc --noEmit && npm run test:unit
`

Sources, Code & Further Reading