What is a coding workflow?

A coding workflow is the repeatable process you use to move from idea to shipped software, including research, requirements, technical planning, implementation, and validation.

Why does an AI coding workflow need documentation?

AI coding workflows need documentation because the PRD, technical design, and agent instructions preserve intent across sessions and make the generated code more consistent.

What should happen before building with AI?

Before building with AI, you should validate the idea, define the product requirements, make key technical decisions, and prepare an instruction file such as AGENTS.md.

Coding Workflow for AI Projects: A 5-Step Process That Ships

?Why Most AI Coding Fails

Most developers using AI assistants jump straight into coding. They prompt, get code, fix bugs, prompt again, and repeat. Hours later, they have a mess of disconnected features that don't work together.

The Problem ↔ Solution

✗Start coding immediately, figure it out as you go

✓Research → Define → Plan → Build systematically

✗AI generates random code, you fix it repeatedly

✓AI follows structured plan, builds coherently

✗Scope creep, endless features, never launch

✓MVP-focused, clear boundaries, ship fast

✗Context lost between AI sessions

✓Persistent context via AGENTS.md

The 5-Step Coding Workflow for AI Projects

Each step builds on the previous, creating a chain of context that AI can follow. Total time: ~4 hours for a complete MVP.

Research & Validation

~20 min

Validate your idea before writing code. AI helps with market research, competitor analysis, and technical feasibility.

Market AnalysisCompetitor ResearchTechnical Feasibility Report

Product Requirements

~15 min

Define WHAT to build with a structured PRD. User stories, feature priorities, and success metrics.

PRD DocumentUser StoriesFeature Prioritization

Technical Design

~15 min

Plan HOW to build it. Architecture decisions, tech stack selection, and database schema.

Tech Design DocArchitecture DiagramDatabase Schema

Agent Configuration

~10 min

Generate instruction files for AI coding assistants. AGENTS.md, .cursorrules, CLAUDE.md.

AGENTS.md.cursorrulesTool-specific Configs

Build with AI

~1-3 hrs

Execute the plan with AI assistance. Build incrementally, test after each feature, iterate.

Working MVPDeployed AppDocumentation

The Key Insight

"Each step creates a document that becomes context for the next step. By the time you start coding, your AI assistant has complete understanding of WHAT to build, WHO it's for, and HOW to build it."

This is why random prompting fails—AI has no context. With the workflow, you're giving AI a complete blueprint. The AGENTS.md file becomes the "brain" that persists across sessions. If you want to see how this educational workflow maps onto the actual product, open the Vibe Workflow product overview.

How AI Fits Into Each Step

Research→Gemini/GPT for web research, Claude for analysis

PRD→Claude for structured documents, templates from our generator

Tech Design→Claude for architecture, GPT for comparisons

Agent Config→Generated from PRD + Tech Design automatically

Build→Cursor, Claude Code, or Windsurf with AGENTS.md context

The Context Chain

Idea→research.txt→PRD.md→TechDesign.md→AGENTS.md→MVP

Each document references the previous. When building, AI can trace decisions back to research findings.

Want the underlying assets? Browse the prompt templates for the raw documents, inspect the visual workflow diagram for the stage map, or start with the definition of vibe coding if you are still framing the methodology.

Coding Workflow
for AI Projects