Our offerings
Getting started with AI-assisted engineering
A two-hour session, open to anyone
The state of the tooling, and then the part that matters: telling sound agent output from the kind that passes review and should not have.
- 2 hours, five chapters
- Recording coming soon, live on request
- Nothing to install
Modular training for your team
Three one-day modules, each sold on its own
Foundations, Verification, and Platform. Each is a full day with its own job, so a team can buy the one where it needs the step up.
- One day per module
- On site
- Your codebase
The free session in detail
Getting started with AI-assisted engineering
Where we got to, what the tools are, and what good looks like.
Most teams are now using coding agents, but have no agreed way of working with them. Closing that gap is the purpose of this session. We will cover what the tools have turned into, and then spend the bulk of the time on how to judge what an agent hands back to you. When most people think of generative AI failures, they still picture a hallucinated API call, which a compiler can now catch in seconds. The costly failures are now the ones which pass review, and are written with no more hesitation than correct implementations. For cloud native teams, these failures land in YAML and templates, where a mistake will show up as silence rather than an error. A talk-through with worked examples on screen, not a lab. No prep or prior experience is assumed.
You will be able to
Place the tool your team uses on a ladder that runs from a web chat window to a harness working unattended
Explain why an agent missed something you were sure it knew
Recognise the kind of failure a normal code review waves straight through
Take away a handful of checks you can apply to agent-written work the same afternoon
Setting it up
Nothing at all, not even an install
- Length
- 2 hours
- Format
- Recording coming soon, live on request
- Level
- Beginner to intermediate
- Your code
- No
- Price
- Free
The free two-hour session, coming soon
Tell us where to send it and we will email it to you as soon as it is ready. If you would rather have the session given live, to your team or at your event, then let us know and we will arrange a date.
The modules in detail
| Module | Length | Where | Your code | Who it is for | Price |
|---|---|---|---|---|---|
Foundations AI Coding Agents for Engineering Teams | 1 day | On site / remote | No | Engineers using an agent most days | On request |
Verification Reviewing and Testing AI-Generated Code | 1 day | On site | Yes | A delivery team | On request |
Platform AI for Platform Engineering | 1 day | On site | Yes | Platform or infrastructure teams | On request |
The free session is the starting point, and assumes no experience with an agent at all. The modules pick up from there, and are built for teams already working with agents day to day. Foundations and Verification are the pair most engineering teams will want.
AI Coding Agents for Engineering Teams
Context, cost, and control.
Most engineers using an agent are using it as a chat window that happens to edit files. They cannot say what is in its context, they have no idea what a run costs, they use the same model for renaming a variable and for designing an interface, and when it does something stupid they conclude the tool is stupid. Every one of those is an operating error, and every one of them is fixable. This is also the only module that needs nothing from you: no repository, no cluster, no credentials, and no security review, so it can be booked without a procurement conversation.
You will be able to
Be held to account for what your agent knows at any given moment
Work out why a run went wrong
Bring down agent usage costs by restructuring the work and matching each task to the right model
Say where your models are allowed to run, from a laptop to your own cloud account
Document and capture your team's current practice
Setting it up
Everything runs on our sandbox
- Length
- 1 day
- Format
- On site / remote
- Hands-on
- 4 hrs
- Level
- Intermediate
- Your code
- No
- Price
- On request
Reviewing and Testing AI-Generated Code
Guardrails, the delivery loop, and wiring agents into systems that are not AI.
The bottleneck in AI-assisted engineering is trusting the output, rather than the workflows generating output. If a team cannot review agent output quickly, it either merges work nobody understands, or slows down to the point where the agent was pointless. Both of these outcomes are common. The day covers the security side of that too, in the language your security function already uses, so what you take back to them needs no translation.
You will be able to
Put limits around an agent that automatically hold
Agree on and provide justification for what your team will not hand to an agent
Perform high quality verification and reviews of agent-produced work
Spot instructions that have erroneously reached your agent, and decide what is allowed to reach it
Give an agent permissions to systems it needs which don't have damaging over-reach
Move a change from backlog to merge-ready using safe and repeatable processes
Setting it up
We will work in the branch of a non-production repository
One system you already run, with read-only permissions
- Length
- 1 day
- Format
- On site
- Hands-on
- 5 hrs
- Level
- Intermediate
- Your code
- Yes
- Price
- On request
AI for Platform Engineering
Kubernetes, operators, and access control.
This day is for the team that has agents working well on application code and has found that almost none of it carries over to the platform. The scaffolding for running AI which assists in managing platforms is materially different: correctness in infrastructure is proved by a cluster reconciling rather than by a test run. An agent holding cluster credentials has a blast radius that an agent editing a Go file does not.
You will be able to
Catch infrastructure mistakes which an agent can make silently before reaching a cluster
Let an agent investigate a live workload
Decide what the agent process itself runs inside, instead of trusting the harness to bound it
Judge if an infrastructure change is correct
Know what your teams spend on models, who spent it, and what data left the network
Set the terms before an agent touches a service owned by another team
Setting it up
We will work in a non-production cluster or a namespace
- Length
- 1 day
- Format
- On site
- Hands-on
- 4 hrs
- Level
- Advanced
- Your code
- Yes
- Price
- On request
Approach
Does this sound like your team?
Teams already given AI tooling
Individual wins and processes which never coalesce into a shared way of working
Teams that tried it and stopped
Worth understanding what went wrong before spending more on licences and tokens
Platform teams holding the line
Happy to review agent work in a repository, but not sure how agents may work in a cluster
Engineering leads who need a standard
A worked example the team can point at
How the modules run
- Six to ten engineers per module, so everybody works at their own keyboard
- Your own laptop and agent, with access to your model provider
- The modules are designed for teams already using an agent day to day. Start with the free session if you're not quite there yet
Talk to a specialist
Interested in running AI-Assisted Engineering with your team? Book a quick chat with one of our team to find out more.
Talk to a specialist