From Prompts to Prototypes: How AI Changed Our Dev Workflow
Three weeks ago, we believed what most developers believe: that building production-ready apps required months of planning, coding, and coordination. Then, we changed one thing—how we started—and everything shifted.
The Catalyst Moment
We kicked off two ambitious projects:
- A review aggregation platform to analyze customer sentiment from multiple sources.
- A community platform for immigrant women in Colorado with local resources and events.
Instead of building from specs, we began with natural language vision statements using ChatGPT and Claude.
Our First Breakthrough: Vision-First Prompting
Instead of Figma wireframes or ERDs, we wrote:
- User stories
- Functional expectations
- Edge cases
AI-generated outputs:
- Structured requirement docs
- APIs
- Test suites
- Debugging explanations
“We weren’t abandoning coding—we were coding with intention, starting with AI-generated foundations.”
The Error Handling Challenge
Without detailed specs, interdependencies caused cascading issues. Our solution:
- Generated AI-authored error handling playbooks
- Ran continuous adversarial testing to break and improve our prototypes
- Shifted to terminal-first development with faster iteration
Result? Functional prototypes in six hours.
The Evolution: Schema-First Methodology
We needed architectural integrity—so we transitioned to:
Our Evolved Process
- Vision Definition
- AI-Prompted User Story Analysis
- AI-Generated Schema
- Iterative Schema Review
- Claude Code Build-out
“When schema comes first, structure and predictability follow.”
Why Schema-First Works
- Structural integrity
- Predictable debugging
- Minimized refactoring
- Higher AI output quality
A Broader AI Workflow Revolution
Our dev stack grew to include:
- n8n + Make.com: For automated backend workflows
- QMD: For documentation and AI-generated presentations
- Clipchamp: For AI-assisted video production
Each tool reinforced the others. This compounding momentum became exponential.
Future Outlook: UI-Powered Development
Claude Code’s new UI interface could:
- Onboard non-tech teammates
- Simplify schema-to-solution pipelines
- Further collapse dev timelines
What It Means for You
Whether you're a dev, PM, or founder:
This is your new dev flow:
- Write your vision
- Use AI for full user story mapping
- Generate/refine a schema
- Build with Claude
- Break + fix + repeat
You’ll deliver better, faster—and more intentionally.
Emerging Hybrid Roles
At Mile High AI Labs, we’re seeing new job archetypes emerge:
| Role | Description |
|---|---|
| Vision Architect | Translates abstract ideas into AI-executable prompts |
| AI Orchestrator | Connects systems, reviews AI code, optimizes workflows |
| Schema Strategist | Combines database architecture with prompt design |
| Iteration Master | Stress-tests AI outputs and drives continuous refinement |
The Ambiguity We're Navigating
- What is a “senior dev” when AI codes?
- How do we price faster builds?
- Which skills still matter in 2 years?
What Skills Now Matter Most
- Contextual storytelling
- Systems thinking
- Prompt engineering
- Schema design
- Critical evaluation of AI output
Final Thoughts: We’re Redefining Expertise
“The developers who thrive won’t resist AI—they’ll learn to dance with it.”
We’re not just building faster—we’re building with clarity, consistency, and confidence.
Your next idea can become a working product in hours. But more importantly—it could redefine your role in this new world.
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