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How software gets built when AI runs the cycle

AI software development lifecycle

With our proven AI-native SDLC, we reimagined the software development process to combine the old control objectives with new enforcement.

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6steps in every project
10+AI agents doing the work

The basics

Software delivery happens in the same steps

SDLC THE CYCLE
  1. 01Define — agree what the system has to do
  2. 02Design — decide how it will be built
  3. 03Build — write the code
  4. 04Test — prove it works
  5. 05Release — put it in front of users
  6. 06Improve — fix, change, repeat

Every software project runs on the same Software Development Life Cycle, or SDLC, whether or not anyone names it. The steps are fixed, but the people and the timing are not. Two projects can follow the same SDLC and still differ in who handles each step and how long it waits before the next one starts.

Why does waiting take the longest?

Traditional SDLC

One approved feature, from decision to live:

waiting for a
free developer
building
waiting for
review
review
waiting for
testing
testing
waiting for
a release slot
  • work actually happening
  • queueing, waiting for a person to be free
  • Illustrative shape, not measured data

Usually, the work itself is quick. The delay comes from queues between steps that run up the clock and the bill.

The cause

Software team has a fixed bandwidth

THE WHOLE TEAM BA DEV DEV QA DEVOPS PM

Six people, five roles — two of them developers — and a task sits in one pair of hands at a time.

  1. 01BA

    writes the requirement

  2. 02 · YOUR SIDEClient

    approves it

  3. 03Dev

    writes the code — two at a time

  4. 04Code review

    a second dev checks it

  5. 05QA

    tests it

  6. 06DevOps

    deploys it

2 DEVS MAX

WAITING Change request

Only two tasks can be in development at once; the rest queue outside. That waiting is dead time, because the work is ready and the people aren't available.

A bigger team isn't more bandwidth

Six people does not mean six things happening at once. One task moves through them in sequence before every hand-off.

More people ≠ more speed

Each hire adds coordination, onboarding and handovers as well as capacity.

Fixes compete with features

Testing, review and bug fixing draw on exactly the same people.

The change

AI-driven SDLC makes a difference

Same cycle

STEPS 1–2 · UNCHANGED

People decide what to build, and how

Requirements and architecture undergo mutual sign-off. Nothing starts until both are approved.

Human oversight
STEPS 3–6 · NO LONGER A QUEUE

A team of AI agents does the building

AI-generated code, review, testing, and release happen in parallel, immediately, without waiting for anyone to be free.

10+ AI agents AI DLC

How AI-driven development works

AI SDLC framework

AI-DLC replaces traditional sprints with shorter 'bolts' for faster delivery. Each agent does one job. Tasks arrive at the coordinator, which decides who does what and in which order.

Coordinator ASSIGNS ALL WORK

Checks the
requirements

Sets the
architecture

Checks design,
releases

2 AGENTS

Writes the code

3 AGENTS

Reviews the code

2 AGENTS

Writes & runs tests

2 AGENTS

The builder never approves its own work

The agent that writes the code is never the agent that reviews or tests it. The same separation of duties you would expect from a human team.

Agents work at the same time

While one part of the system is being built, another is being tested, and a third is being released.

Development process

Is AI-generated code any good?

Every AI-assisted development undergoes six comprehensive checks. Each one can send the work back.

  1. 01Requirements

    checked for gaps and collisions

  2. 02Code

    written by an agent

  3. 03Code review

    a different agent checks it

  4. 04Tests

    unit, integration, end-to-end

  5. 05Design

    compared pixel by pixel

  6. 06Release

    deployed and monitored

A failed check returns the feature to be fixed, and then it has to pass the checks again.

In a human team that much checking would be unaffordable, here each pass costs minutes.

In the AI SDLC, every check is run by a different review agents than the one who did the work. Nothing approves itself.

Real projects, live today

The result: AI autonomous development process

A REBUILD — THE TRADITIONAL WAY 11 months, still not delivered
11 months
THE SAME REBUILD — WITH AI SDLC 3 months, in production
3 months
START12 MONTHS
1.2 people part-time instead of 5 full-time
Six months of delivery by half an analyst, half a tester and a little oversight.
No developers at all, high software quality
Products are in production.
Clients accept the work, ask for changes, and we keep shipping.

Client names held under NDA.

The decisions stay with people

What does not change in AI DLC?

  1. 01

    Requirements

    You and our analyst agree what to build, and what "finished" means.

  2. 02

    Architecture

    Our architect decides how it must be built, and approves it before anything starts.

  3. 03

    Acceptance

    Humans review the result and accept it. Nothing is finished because an agent said so.

  4. 04

    Accountability

    Named people are answerable for the work. "The agent did it" is not an answer we will give you.

Bad requirements now produce bad software faster. That is exactly why the first two steps are still human, still slow, and still approved by name.

Match today's reality

Software engineering with AI

You approve what to build

Requirements and architecture, signed off the same way as always.

We build, check and release it

Six automated checks on every change, epic by epic.

You accept it, or ask for changes

Changes go through the same pipeline. There is no "later sprint".

The pace is set by how quickly we agree on what to build instead of how many developers are available.

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