Tools don't transform companies. People who use them well do.
A hands-on program that takes your team from AI-curious to AI-fluent — using your codebase, your workflows, and your real problems as the curriculum.
Most AI training is a lecture about the future. Ours is a working program: your people leave having already automated something real, in your environment, with skills they can repeat without us in the room. Developers learn to direct AI agents through real tasks in your codebase. Operators learn to build and supervise AI workflows in their actual daily tools.
The program is delivered in short practical sessions over several weeks — because one-off workshops produce enthusiasm that evaporates by Monday. Each cohort ends with shipped automations, written playbooks, and a measurement of what changed.
What you get
Practical curriculum
Tailored to your stack, your tools, and your team's actual daily work — not generic examples.
Shipped automations
Each participant leaves with something real they built and deployed during the program.
Written playbooks
Reference guides your team keeps: when to use AI, how to prompt, how to review, when not to trust it.
Progress metrics
Before/after measurement of adoption, confidence, and time saved on real tasks.
How it works
Assess
We survey skills, tools, and attitudes to design the right starting point.
Train
Weekly hands-on sessions with homework on real work — not toy exercises.
Build
Participants ship a real automation each, supervised by our engineers.
Embed
Playbooks, office hours, and a measurement of what changed in the first 90 days.
Questions we get asked
Who is this for — engineers or non-engineers?
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Both tracks exist. The engineering track covers AI-assisted development, agent direction, and AI-aware code review. The operations track covers workflow automation, prompt design, and supervising AI in daily tools. Mixed cohorts work well too.
How long is the program?
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The core program runs 4–6 weeks with one session per week plus practical assignments. Intensive 2-week versions are available for teams under deadline pressure.
What tools do you teach?
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The ones your team will actually use. We are tool-agnostic in principle and pragmatic in practice: the curriculum is built around your existing stack, with the best current AI tooling for each job.
How do we know it worked?
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We measure before and after: adoption rates, time saved on benchmark tasks, and the number of automations still running 90 days later. Enthusiasm is nice; numbers are better.
Other ways we work
Engagements combine more often than you would think — an automation project surfaces security questions, a build needs an upskilled team to own it. The other three services, in one place:
Production-ready software, built the third way.
Senior engineers directing specialized AI agents: the speed of automation on the repetitive work, human judgment on every decision that matters.
Explore Software Development →AI WorkflowsYour team is doing work a machine should be doing.
We find the repetitive, rule-heavy workflows draining your team's hours and automate them with AI agents — with humans in the loop wherever judgment is required.
Explore AI Workflows →AI Risk & SecurityYour people are already using AI. The question is whether it's safe.
A structured assessment that maps every AI touchpoint in your organization — the official ones and the shadow ones — and turns the risks into a prioritized remediation plan.
Explore AI Risk & Security →Sound like what you need?
A 30-minute call is the fastest way to find out.