Inside the AI Factory
Where AI writes the code and humans run the plant.
Traditional agencies still treat AI like a sidekick. With AI Agency, the AI Factory is the main engine. We use AI to design, generate, refactor and test entire systems, while senior architects control the blueprint, guardrails, and final sign-off.
You don't get “experiments”. You get production software built by an autonomous pipeline instead of a room full of coders.
100% AI Code
Every line is generated by AI. Humans only architect, review, and sign off.
Your Repo
Code lives in your Git repo. No black boxes or proprietary lock-in.
No Hourly Billing
We align on outcomes, not typing time. Fixed scope, factory delivery.
INTAKE
Founder / CTO brief
ARCHITECTURE
Senior humans design
AI CODE
Factory generates code
CHECKS
Tests & security
LAUNCH / ITERATE
Deploy & regenerate
Not a Tool. A Production Line.
The AI Factory is our end-to-end software production line.
Instead of hiring a team of developers to manually type code, we:
- Encode your requirements and constraints as system prompts, guardrails, and tests.
- Orchestrate multiple AI models and dev environments in a single pipeline.
- Generate, review, and ship code in repeatable cycles, not one-off heroics.
Think of it as DevOps for AI code generation:
- InputsProduct vision, constraints, tech stack preferences.
- The LinePrompts, agents, refactoring loops, test suites, CI/CD.
- OutputsWorking applications, APIs, agents, and dashboards you can deploy and maintain.
How the Factory Is Wired.
We run the AI Factory like a plant with clear layers. No black box, no “prompt and pray”.
Layer 1
Human Governance
Senior architects and product owners
- Define system architecture, data models, and integration points.
- Approve tech stack (frameworks, databases, hosting).
- Set non-negotiables: security, performance, and compliance constraints.
Layer 2
AI Factory Engine
Models, agents, and dev environments
- AI generates frontend, backend, infra-as-code, and tests.
- Agents refactor, document, and optimize existing code.
- Automated checks catch obvious bugs before humans even look at it.
Layer 3
Infrastructure & Integrations
Cloud, databases, APIs
- We plug the generated code into real infra: cloud platforms, DBs, auth providers, payment gateways, CRM/ERP systems.
- Everything is managed in version control so you can see every change and roll back when needed.
Code is written by AI, but the architecture, constraints, and final deployment are owned by humans.
How the Factory Turns Ideas Into Running Systems.
Here's what actually happens after you say “let's build”.
Discovery & Constraints
We map your product, edge cases, and business rules. Deliverable: a short Product Blueprint and constraint list (must-have stack, integrations, non-negotiables).
Architecture Blueprint
Senior architects design the system diagram: services, data flows, entities, and integration points. Deliverable: architecture map and tech stack recommendation.
Factory Configuration
We convert the blueprint into structured prompts, guardrails for naming/patterns/security/performance, and test cases with sample data. This is where we remove the randomness from AI.
AI Generation & Review
The AI Factory generates frontend, backend, infra, and tests. Architects review at a system level: does it match the blueprint, are there smells or security issues, and we adjust prompts and regenerate where needed.
Deployment & Iteration
We plug into CI/CD, deploy, and monitor. New requirements? We update the blueprint and prompts and let the Factory regenerate impacted parts instead of manually rewriting everything.
What Comes Off the Line.
Anything you'd normally throw at a dev team, the AI Factory can produce faster and with cleaner architecture.
SaaS & Web Platforms
- Multi-tenant apps
- Admin dashboards
- Billing & onboarding
- Complex workflows
View example
Native & Cross-Platform Mobile Apps
- iOS and Android apps
- Backend integration
- Auth & payments
- Analytics wiring
View example
AI Agents & Internal Automation
- CRM & helpdesk plugins
- Inbox & internal tools
- Support & outreach
- Routing & data cleanup
View example
Legacy Code Rescue
- Stabilizing messy codebases
- Refactoring to modern patterns
- Adding test coverage
- Future AI-driven maintenance prep
View example
Who Owns the Code? How Safe Is It?
You should be suspicious of anyone saying “AI wrote it, trust us”. Here's how we de-risk that.
Human review as a rule, not a favor
- Every project has a named architect accountable for quality.
- AI output is reviewed against the architecture, not just “does it run”.
- We use static analysis, tests, and monitoring — not vibes.
Your repo, your IP
- Code lives in your Git repository, not our private black box.
- You keep full IP rights and can bring your own team in at any time.
- No hidden platforms or proprietary lock-in.
We don't train on your private code
- Your code and data are not used to train public models.
- We use models and configurations that respect isolation and privacy settings.
Stack choice, not stack religion
- We recommend modern, maintainable stacks, but we don't force exotic tools only we understand.
- Your future hires and partners should be able to work on this codebase without needing us in the room.
We rely on industry-standard tools for testing, security scanning, and code quality.
Why This Model Wins Against Classic Agencies.
No hourly drag
We’re not paid to type slowly; we’re paid to ship working systems.
Same architects, more output
A small senior team driving a huge AI coding surface beats a large junior team any day.
Regeneration over refactoring
Instead of manually untangling code, we regenerate components with new constraints.
Cleaner architecture by default
Because the blueprint comes first, not “we’ll figure it out in sprint 7”.
You’re not buying “AI experiments”. You’re buying a repeatable production system for building software.
How We Work With You.
We keep it simple. Three typical ways to run the Factory:
Greenfield Build
New Product / MVP
You bring the idea and constraints. We design the architecture and run the Factory from zero to launch.
Platform Upgrade
Existing Product
We analyze your current system. The Factory refactors, replaces, or extends modules while keeping critical pieces running.
Experiment Line
R&D / Prototypes
Rapid, AI-generated prototypes to test new ideas, features, and business models without burning months of dev time.
Most serious builds move from Blueprint → First Running Version in weeks, not quarters, depending on scope.
Questions You Should Be Asking.
Is this experimental, or can I run a real business on this?
We use production-grade stacks, version control, tests, and CI/CD. The only difference is who writes the code. The software is built to be maintainable by any competent team, not just us.
What happens when I need changes?
You don’t start a new 6-month project. We adjust the blueprint and constraints, then let the Factory regenerate the affected parts. This makes change cheaper and faster than manual refactors.
Can my internal devs work on this later?
Yes. They work with normal frameworks, repos, and pipelines. We can even onboard them to the Factory model so they can use AI generation safely in-house.
Which models and tools do you use?
We combine frontier models and AI dev environments (Cursor, Claude, v0, Replit, Lovable, and others) in one pipeline. The exact stack depends on your requirements and data sensitivity.
How do you price this?
We don’t bill for typing time. We scope the architecture and complexity, then give you a fixed or milestone-based price tied to outcomes — not hours.