Claude, Codex, Copilot and Cursor gave every developer an AI assistant. But no one taught your team how to actually work with it. So the output is inconsistent, the context resets every morning, and the productivity gain you were promised never showed up. The Intelligent Engineering Workshop trains your developers to run AI like an engineering system, hands-on, on your own stack.
You bought the tools. So why isn't your team shipping any faster? Because AI tools are only as good as the person driving them, and driving them well is a skill no one taught your team.
The AI doesn't know your architecture or conventions, so your developers burn a third of their AI time fixing output that doesn't match how your team actually builds.
Your team re-explains the same architecture, the same decisions, the same standards every session. The AI forgets it all overnight, and every day starts from zero.
Your developers babysit a single chat window when they could be directing several streams of work at once. All that parallel capacity sits unused.
The same prompts get retyped from scratch, every day, by every developer. There's no shared, repeatable way of working. Everyone just improvises alone.
This isn't a lecture or a slide deck. Your developers work hands-on, on real problems, and walk away able to:
Manage what the AI sees so it stops ignoring half the instructions and starts producing reliable, on-standard output the first time.
Set up context that carries across sessions and across developers, so no one (and no new hire) ever starts from zero again.
Direct multiple AI subagents at once instead of one prompt at a time. More shipped, from the same team, in the same week.
Turn repeated prompts into shared skills and commands the whole team can trigger in a single step. Consistency becomes automatic.
Work the way that gets the right answer in fewer passes. Less rework, fewer wasted tokens, and lower spend for the same output, or more output for the same spend.
Stop treating AI like a chat box and start running it like an engineering system. It's the durable way of thinking that keeps paying off long after the workshop ends.
Every session, we work real problems live, in front of your team. Your developers don't sit through a lecture about AI. They watch it work on problems like theirs, then do it themselves. The best proof that this changes how your team ships is watching your team ship.
A straightforward, hands-on engagement that respects your team's time. Remote, on your own stack, no disruption to delivery.
We learn your stack and your team, set up hands-on access, and frame the training the right way: this is leverage for your developers. It moves them up the stack, it doesn't replace them.
Two short remote sessions a week. We work real, representative problems on your own tools (never toy demos), so what your team learns transfers to Monday's work.
Between sessions, your developers take on a "build challenge": apply the new skill to their own work before the next session. It's how the operating model becomes a habit instead of a demo they watched.
Your team keeps the skills, the reusable commands and workflows they built, and a way of working that outlasts the engagement, and it can spread to the rest of engineering.
Software teams (especially .NET / C# shops) that already have AI tools but aren't getting the output they expected.
Engineering leaders who would rather level up the team they already have than wait months for a new hire to ramp.
Not for teams looking for someone to write the code for them. This makes your developers better; it doesn't replace them.
Priced per developer, with a cancel-anytime, hands-on platform license included so your team learns by doing, not by watching. From a small pod to a whole team. Tell us your team size and we'll size it on the call.
Before founding GlobalCove, our founder spent 30+ years architecting the systems Fortune 50 companies depended on daily, and a decade as a Microsoft MVP. That same obsession with doing it right now goes into training your developers to build with AI the right way.
Tell us how your team uses AI today. We'll show you exactly what they're missing, and how fast it changes.