How the Factory Works

From first call to first deploy, without the drama.

Most agencies sell “sprints” and “resources”. We sell a pipeline.

This page shows exactly what happens after you click Start the Factory — what you see, what we do, and where AI and humans each sit in the loop.

No vague roadmaps. You’ll know what’s happening in every phase — and what you’re paying for.

1

Blueprint

Design & Architecture

2

Factory Run

AI Generation & Refinement

Processing...
3

Launch & Scale

Deploy, Monitor, Iterate

AT A GLANCE

Three Phases. Zero Guesswork.

Every project runs through the same three macro-phases. Scope changes, the pipeline doesn’t.

1

Phase 1 – Blueprint

We capture your product, constraints, and risks — then design the architecture and delivery plan.

2

Phase 2 – Factory Run

We configure prompts, guardrails, and tests, then let the AI Factory generate and refine the system.

3

Phase 3 – Launch & Scale

We deploy, monitor, and iterate using the same pipeline instead of starting from scratch.

END-TO-END FLOW

What Happens After You Click “Start the Factory”.

Below is the default flow for a new build. Timelines are typical, not marketing fantasy.

Step 1

Discovery Call

Day 0–2

We run a 20–30 minute call to understand:
• What you want to build or rescue
• Constraints (budget, timeline, stack, compliance)
• Existing systems we need to plug into

Your deliverables:
  • Clear recap message
  • Requested documents
Our work:
  • Assess if Factory is a fit
  • Outline rough path
Step 2

Product & Constraints Workshop

Week 1

A focused working session (1–2 hours) on Zoom/Meet.

Your side:

Walk through user journeys, edge cases, and “must-never-happen” risks.

Our side:

Map entities, flows, integration points. Define hard constraints (regions, compliance, stack).

Output:Product Blueprint + Constraint Sheet
Step 3

Architecture Blueprint

Week 1–2

Senior architects design the system. AI does not touch this part.

What we produce:
  • System diagram (services, queues)
  • Data model / entity diagram
  • Proposed tech stack & Risk notes
What you do:

Review, ask questions, approve. This is a formal go / no-go gate.

Step 4

Factory Configuration

Week 2

We turn the blueprint into something AI can actually follow.

Under the hood:
  • Structured prompts for modules
  • Guardrails for naming & security
  • Test cases & sample data
Your visibility:

You see the config at a human level: modules, flows, tests — not raw prompts.

Step 5

AI Generation & Review

Week 2–3

This is where the Factory runs.

AI does:

Generate frontend, backend, IaC, and tests. Refactor in loops until constraints pass.

Humans do:

Review system level (arch, security). Decide regeneration vs patching.

Your Deliverables:Running preview env, Repo access, Walkthrough video.
Step 6

Launch & Iteration

Week 3+

We plug in CI/CD, prepare production, and agree launch criteria.

On launch:

Deploy to your infra or ours. Set up monitoring.

Post-launch:

Change requests go back through the blueprint → config → generation loop.

TRANSPARENCY

Your Experience vs Our Internal Machine.

You shouldn’t have to care which model or tool we used yesterday. You should care what you see and when.

Before Build
You See
  • A simple intake form
  • A recorded workshop and summary doc
  • A visual architecture map
We Do Behind The Scenes
  • Tech feasibility checks
  • Risk analysis
  • Pre-config of prompts, test suites, and repos
During Factory Run
You See
  • A preview URL
  • Short loom-style walkthroughs
  • Milestone check-ins
We Do Behind The Scenes
  • Multiple AI generation cycles
  • Static analysis, security checks
  • Regeneration where code fails constraints
After Launch
You See
  • Clear change requests and impact estimation
  • Release notes and version tags
We Do Behind The Scenes
  • Iteration through AI with updated constraints
  • Regression tests and rollback safety
COLLABORATION

How We Work Day-to-Day.

No ticket bingo, no “we’ll get back to you next sprint”. We keep collaboration simple and predictable.

Single Source of Truth

We keep the project plan and decisions in one workspace (Notion / Linear / Jira – picked with you). No scattered docs.

Async First, Calls When Needed

Loom/videos + concise updates. Calls for workshops, approvals, and big decisions — not for status theatre.

Direct Access to an Architect

You always know who is accountable. No playing telephone through layers of PMs and junior devs.

QUALITY & RISK

Where QA, Security and Code Review Fit In.

The pipeline is fast because AI does the typing — not because we skip checks.

  • Automated checks in the loop

    Static analysis, tests and basic security scanning run as part of each Factory cycle, not at the end.

  • Human review at architecture level

    Architects review flows, data access, and edge cases — not just “does it compile”.

  • Industry tools, not home-grown magic

    We rely on standard tools for CI, code quality and security (e.g. GitHub Actions, SonarQube, Snyk), not mysterious internal dashboards.

Want the full architecture? See the AI Factory page

Quality & Security Stack

GitHub
Sonar
Snyk
OWASP
INPUTS

What We Need From You to Make This Work.

The Factory only runs smoothly if your inputs are sharp. Here’s what we ask for.

  • A clear owner on your side who can make decisions
  • Any existing diagrams, flows, or code repos
  • Access to tools we need to integrate (e.g. Stripe, CRM, auth)
  • Realistic constraints on budget and timeframe
  • A willingness to be honest about “nice-to-have” vs “must-have”

⚠️ This is what makes projects fail: ambiguous owners and hidden constraints.

Ready to Run Your First Line?

Whether you’re building new or rescuing a mess, we’ll walk you through your own Factory run — one phase at a time, no lock-in, no fluff.

• We map your case to the process
• We give you a realistic timeline
• You decide if you want to run the Factory