AI in Software Engineering

01What you'll walk away with

Six things you'll own
by the final week

Not topics you sat through: artefacts and habits you can show a hiring manager or apply to Monday's sprint.

01

A prompting system for engineers

Role, context, constraints, output contract. Repeatable structure that gets usable code instead of plausible-looking code.

02

A code review checklist for AI output

What to check before you commit anything a model wrote: readability, hidden coupling, performance, and the security holes it won't mention.

03

A working capstone you deployed

A real service with a test suite you understand and an architecture decision record explaining why it looks the way it does.

04

A personal AI safety policy

What you will and won't put into a model, how to handle client code, and how to stay inside your employer's policy without stalling.

05

A model-selection instinct

Which model for which job, when a cheaper one is enough, and when to stop prompting and write it yourself.

06

A 30-day post-programme plan

The habits that survive contact with a real backlog, written for your actual stack and team.

02Curriculum · 8 classes over 4 weeks

Four weeks.
One lifecycle.

Each week closes a loop. You finish with something that runs, not notes you'll never reopen.

Week 01

01

Classes 1–2

Foundations, environment and the prompt as a spec

Where the models actually differ, how to set up an IDE that helps rather than autocompletes noise, and how to write a prompt that reads like a specification instead of a wish.

AI-native vs AI-assisted vs AI-aware
Model comparison for real coding work
IDE, Copilot, Cursor and local models
Turning vague briefs into technical specs
Documentation at scale: ADRs, OpenAPI, READMEs
Reading a legacy codebase with AI

Week 02

02

Classes 3–4

Generation, review and refactoring you can defend

The week most engineers change how they work. You stop accepting output and start interrogating it, reviewing generated diffs the way you'd review a colleague's.

Production functions, APIs and modules
Validating before you commit
AI-assisted refactoring and design patterns
Breaking down monoliths
AI as a structured first-pass reviewer
What stays with the engineer, always

Week 03

03

Classes 5–6

Testing, security and shipping responsibly

AI fails quietly and confidently. This week is about catching it before production does, and about the judgement calls no model will make for you.

Test suites you actually understand
Hypothesis-first debugging workflows
Security review of generated code
Secrets, licensing and data leakage
Employer AI policy in practice
CI/CD with AI in the loop

Week 04

04

Classes 7–8

Capstone build and live defence

You ship something real and then explain every decision to a practitioner and your peers. The defence is the point. Anyone can generate code, few can justify it.

Choose your track: CRUD, REST + auth, or multi-service
Build with a full prompt log
Architecture decision record
Live defence to your cohort
Practitioner feedback round
Your 30-day roadmap

03How it works

Live, small,
and hands on the keyboard

No pre-recorded playlist. You show up, you build, and someone who has done it reviews what you made.

STEP 01

Live sessions with a practitioner

Small cohorts, taught live by an engineer who has shipped AI-assisted code in production. You can interrupt, argue, and ask the awkward question. That's the point of it being live.

Practitioner leading a live Brixgate session

STEP 02

Build every week, not just at the end

Each class ends with something to make before the next one. By week four the capstone isn't a scramble. It's the accumulation of what you already built.

STEP 03

Get reviewed by peers and a practitioner

Your work gets read by people solving the same problems. Reviewing someone else's prompt log teaches as much as writing your own.

STEP 04

Defend it, then take the certificate

A live capstone defence in front of your cohort, then a field-verified Expert Practitioner Certificate any employer can check.

04Tools & platforms

The stack you'll actually work in

Model-agnostic by design. You learn to choose, not to depend.

Your own
stack

Tools our practitioners build with. Brixgate is not affiliated with these companies.

05Fit check

Worth being honest
about who this suits

We'd rather you self-select out now than sit through four weeks that weren't built for you.

This is for you if…

You write code professionally and have at least a year of doing it for real.
You already use AI tools but suspect you're using them shallowly.
You want to ship faster without losing ownership of what you ship.
You can commit to live sessions and building between them.
You're comfortable having your work reviewed in front of peers.

This isn't for you if…

You're learning to code from scratch. Start with fundamentals first.
You want a passive, watch-at-2x course. Nothing here is pre-recorded.
You're looking for a certificate without the build. The capstone is mandatory.
You already train models or run ML pipelines. This will be too foundational.
You can't spare a few hours a week for four weeks. Wait for a better window.

Not sure where you land? Take the 90-second check

What You Will Master

The Three AI Skills That Define
an AI-Native Software Engineer

Structured Prompt Engineering

Write prompts that produce accurate, maintainable, production-ready code, not one-shot outputs that need rewriting.

Critical AI Code Review

Review AI-generated code for security vulnerabilities, hidden coupling, and false coverage, before it reaches production.

Personal AI Workflow Design

Build repeatable, high-leverage AI workflows, across your IDE, CI/CD, and documentation pipeline. That compound over time.

07Upcoming start dates

Pick a cohort

Groups stay small on purpose. When a cohort fills, it closes.

Loading…Fetching cohorts

08Alumni

What changed
for them

Specific outcomes from engineers who finished the sprint.

I used to spend hours on boilerplate and hunting obscure bugs. After week two I had a structured review process for every piece of AI-generated code I ship. My PRs are tighter and reviews go faster.

BD

Backend Developer

Brixgate alumnus · Cohort 01

The security class changed how I look at generated code entirely. I found three injection vulnerabilities in our codebase within a week of applying the checklist. We had shipped that code six months earlier.

FS

Full-Stack Developer

Brixgate alumnus · Cohort 01

I finished with a working REST API, a test suite I actually understand, and a prompt log showing exactly how I built it. That artefact alone got me noticed in my next interview.

SE

Software Engineer

Brixgate alumnus · Cohort 01

09Why it pays off

What the fee
actually buys

AI-native engineers ship faster, review smarter and negotiate better. You leave with the workflows, the judgement and an artefact that proves both.

0%

of developers using AI tools report measurable gains in personal productivity

GitHub Developer Survey, 2024

3×

faster delivery for teams with structured AI-assisted development workflows

McKinsey Global Institute

4 wks

from where you are now to a defended capstone and a verifiable certificate

Brixgate programme length

This programme

Live sessions with a working practitioner
Small cohort: your work actually gets reviewed
A deployed capstone you can show in interviews
Field-verified certificate, checkable by employers
Peers you keep after the four weeks end

A self-paced video course

Pre-recorded, filmed before the last model shipped
Nobody reads your code or tells you it's wrong
A completion badge, not evidence of judgement
Most people stop around lesson four
No one to ask when you're stuck at 11pm

11FAQ

Questions people
actually ask

Still unsure? Message us on WhatsApp and a human will answer.

Do I need to be a senior engineer?

Which programming languages are covered?

Is AI-generated code actually safe to ship?

Can I use real work from my job as the capstone?

How much time does it take each week?

What if I miss a live session?

Is the certificate worth anything to employers?

AI in
Software Engineering

Six things you'll own
by the final week

Four weeks.
One lifecycle.

Foundations, environment and the prompt as a spec

Generation, review and refactoring you can defend