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AI-First Development

How products get built in the age of AI.

The Core Insight

Products are conversations, not artifacts.

A product is an ongoing dialogue between creators and users, continuously shaped by signals, never finished. The specification is a living model of intent that evolves as understanding deepens.

Code is derived. The specification is the source of truth. When understanding changes, implementation follows.

The Self-Improving Loop

Vision → Specification → Implementation → Usage → Signals
      ↑                                          ↓
      ←←←←← AI Product Intelligence ←←←←←

Traditional products iterate over months. User research, planning, development, launch, feedback collection, analysis, more planning. The loop takes quarters.

AI-first products compress this to hours:

  1. AI agents test the product continuously, generating usage signals
  2. AI Product Manager synthesizes signals into specification updates
  3. AI implements approved changes
  4. Loop repeats

The product improves while you sleep. Feedback flows directly into improvement. The structural advantage compounds.

What Remains Human

Taste. Knowing what is worth building. The difference between a product that technically works and one people love. AI generates variations. Someone chooses.

Accountability. When the system fails and there are consequences, someone owns the decision to ship. AI optimizes. It cannot be responsible.

Novel insight. AI works from patterns in training data. When doing something genuinely unprecedented, human creativity leads. AI accelerates execution of human insight.

Trust and relationships. People hire people. Your network, reputation, ability to understand what someone really needs. This is durable.

The 2027 View

Products become organisms, not artifacts.

The team is:

  • Human(s) with vision and taste
  • AI PM processing all signals
  • AI engineers implementing changes
  • AI testers validating continuously

The specification is not a markdown file. It is a living model of intent, maintained by the system, viewable as documents but not limited to them.

Human creative capacity to imagine what is worth building becomes the constraint. The translation to running software is nearly instantaneous. The product converges toward user needs automatically.

Carmenta Is Built This Way

This isn't theory—we practice what we teach. Carmenta is built using AI-First Development. The specification lives in version control. Code is generated from it. The specification is the IP.

We're building in public so you can watch the methodology in action. The flywheel—agents test, AI PM synthesizes, AI builds—is how we improve Carmenta together.

The methodology and the product are the same thing.

Want to see this in practice?