The Agentic Development Lifecycle (ADLC) — Vixera Labs

Training

The Agentic Development Lifecycle.

Most teams still run the traditional software development lifecycle at human pace. The Agentic Development Lifecycle (ADLC) puts agents at every stage — so the same work ships in a fraction of the time. This is how I build, and what I teach.

$227M+
Combined client valuation
$45M+
Raised by founders we built for
100+
Products shipped
7
Products acquired

The proof

This isn’t theory. Products built this way have raised $45M+ and reached $227M+ in combined valuation, with seven acquired and two on Shark Tank. One full Shark Tank build shipped in two weeks — founders walked on stage with a finished product and raised $4M. The same approach has powered US government technology engagements, including civic technology for a major US city government office.

The core idea

Two life cycles — same stages, different speed

Specs / PRD
Traditional SDLCEvery spec & edge case up front · 3–6 months
Agentic Development LifecycleOne main artifact, AI-assisted~10–15% of the time
Break down
Traditional SDLCPM maps tickets + FE / BE / deploy deps · weeks
Agentic Development LifecycleTickets drawn from the PRD1–2 days · 90% AI / 10% human
Build + test
Traditional SDLCHand-coded, then manual QA · the long pole
Agentic Development LifecycleTDD loops itself to greenauto-verified per ticket
Ship + review
Traditional SDLCManual review cycles
Agentic Development LifecycleHuman review + unit + Playwright
What that adds up to

The same product — a fraction of the time

Traditional

6 – 9 months

Agentic Development Lifecycle

4 – 8 weeks

Roughly 6–10× faster — not by cutting corners, but by collapsing the planning and hand-off overhead and letting agents do the building under test.

Same scope. Same quality bar. The engineering moves from typing to directing and verifying.

How it works

One loop, run at every stage

Under the hood, every stage runs the same engine: you set the direction, agents build under test, and the results loop straight back to you. You stay in control — the typing just moves to the agents.

You direct

Set the plan, spec & intent

agents pick it up
Agents build

Code written to the spec

under test
Tests verify

Red → green, every change

results surface
You review

Approve, correct, refine

…and back to the top — every stage runs this loop

The ADLC, step by step

Seven stages, start to finish — the way real software gets built with AI in the loop. Tap any step to see what you do inside it, and what you walk away with.

  1. What you'll do

    • Pressure-test the idea with AI
    • Define scope and constraints
    • Choose the architecture direction

    What you'll have

    • Agreed goals & scope
    • Architecture direction
    • Milestone plan
How do I know this works?

It’s not hype — it’s decades-old engineering

Every skill in this course traces back to the books serious engineers have trusted for years. New tools, proven principles.

Tracer bullets

Build a thin, working slice end-to-end to prove the architecture before fleshing it out.

The Pragmatic Programmer · Hunt & Thomas

Deep modules

Clean, self-contained pieces with simple edges — a codebase you can navigate.

A Philosophy of Software Design · John Ousterhout

Red · green · refactor

Write the test, make it pass, then improve — the loop the agent runs.

Test-Driven Development · Kent Beck

Who it’s for

Founders and engineers who want to build real products with AI at speed — and want the lifecycle, not just the tools.