The one-day, on-site bootcamp that turns engineering teams into AI-native shippers.

Most companies that buy AI coding tools capture a fraction of the value they paid for. The CodieDev Bootcamp is the single, in-person day that closes the gap, turning a team of license-holders into engineers who write the majority of their daily code with AI, and giving leadership the visibility to prove it.

Multi-day cohorts available for larger teams.

Adoption is not a procurement problem. It is a training problem.

15–20%Untrained adoption ceiling

What most teams actually capture from their AI tools. The CodieDev bootcamp + platform system aims for 100% adoption.1

60%Lower productivity gains

The penalty teams pay when they roll out AI coding tools without structured training.

3xBetter adoption rates

What organizations achieve when they treat AI coding as a process challenge, not a tooling challenge.

The pattern across every credible study is the same: tools alone deliver a fraction of the value. Structured training is the multiplier. The bootcamp is that multiplier, delivered in a single day.

What the day is worth.

The bootcamp moves each engineer from ~15% to ~40% productivity gain, a delta of roughly $50,000 per engineer, per year, at a $200K fully-loaded cost.1

It compounds every year the team keeps using what they learned. A one-day bootcamp pays for itself in a matter of days. Everything after that is pure return.

A program designed to make the new way of working stick.

Morning / I

The state of AI coding, circa now

A presentation on the latest developments, the patterns that are actually working at companies shipping with Claude Code, and the misconceptions worth letting go of. We address the fears engineers bring into the room: their craft, their judgment, their jobs. Directly and honestly.

Morning / II

Setup & first contact

Every engineer installs Claude Code and the CodieDev CLI. We get every laptop talking to the platform, every account configured, every keybinding sane. Nobody leaves the morning blocked on setup.

Midday

Real ticket. Real team. Real support.

Engineers bring an actual ticket from their backlog and work it with AI, with us in the room. We pair, we coach. We show how to use plan mode to research thoroughly and weigh multiple approaches before a single line is written. We answer the questions that only come up when the work is real.

Afternoon / I

The CodieDev practice

How to write tickets the AI can actually execute on. How to push reverse tickets back to the platform after a session so the work is captured. How to publish skills and specs. How to use the social layer (questions, threads, shared learnings) so the team levels up together rather than each engineer rediscovering the same lessons in isolation.

Afternoon / II

The hackathon: build something audacious

A judged, competitive hackathon to close the day. Engineers build something that helps them in their job or moves the company forward. It's where everything from the day clicks into place, and it's where teams discover what they're suddenly capable of.

Not just faster. Better.

Speed

The majority of daily code, written with AI

By the end of the day, every participant has the working practice, not just the theory, to delegate the bulk of their day-to-day implementation to AI, with the judgment to know when not to.

Quality

Plan mode as thinking partner

We teach engineers to use plan mode to do real research, surface assumptions, weigh multiple approaches, and stress-test designs before committing to code. The result is more accurate work, fewer rewrites, and stronger architecture.

Collaboration

A team that learns from itself

CodieDev's social and artifact features turn individual breakthroughs into team-wide gains. Skills, specs, and patterns get published, refined, and engineers ask each other questions in the open. Knowledge compounds, and that is how the ROI line bends upward instead of staying flat.

Observability

Executive visibility, finally

Tickets in, reverse tickets out, artifacts published, sessions logged. Leadership ends up with a clearer picture of what's being built and how than they had in the pre-AI era. Exactly the answer to the boardroom question of “what is the AI actually doing for us?”

A team that has been through the bootcamp doesn't just use AI. They have a shared vocabulary, a shared workflow, and a shared place to keep getting better. That is the difference between a tool you bought and a capability you own.
The CodieDev thesis

Small enough to be personal. Structured enough to be transformational.

Duration: One full day, on site

Multiple days available for larger teams or deeper enablement.

Cohort size: 10–12 engineers, maximum

Small enough that we work one-on-one with every participant during the hands-on portions.

Format: Hands-on, not lecture

Roughly a third presentation, two-thirds engineers writing real code with us in the room.

Inputs we need: A room, laptops, real tickets

Each engineer brings an actual backlog item to work on. We bring the rest.

What every team leaves the day holding.

  1. A working installation, on every laptop

    Claude Code and CodieDev CLI configured and connected. No “I'll set it up next week.”

  2. At least one real ticket, shipped or near-shipped

    Closed by AI under coaching. Proof of concept that lives in the actual codebase.

  3. A team-wide vocabulary and workflow

    Plan mode, reverse tickets, skills, specs. The language that turns AI work into a coordinated practice.

  4. An active workspace on CodieDev

    Skills, specs, and questions already populated by the team during the day. Ready to grow.

  5. A hackathon project and a winner

    Something built in hours that would have taken weeks. Often something the company actually keeps using.

  6. Executive-grade observability

    Leadership can see what's being built, how it's progressing, and where AI is generating leverage, from day one.

Your tools shouldn't be the only thing getting smarter. Your team should be too.

The bootcamp is the highest-leverage investment in your AI coding stack. It is the difference between a team that holds licenses and a team that has actually become an AI-native engineering org with the productivity, the quality, and the executive visibility to prove it.

1Productivity figures reference DX's 2025 AI Measurement Framework, Google's 2025 DORA Report, and Faros AI's telemetry across 100,000+ developers and 1,255 teams. The $50K/engineer/year delta assumes a $200K fully-loaded engineer cost and the difference between typical untrained (~15%) and trained (~40%) productivity gains as measured by DORA delivery metrics and PR throughput. We recommend instrumenting your team using these same frameworks so the bootcamp's impact is measured in your numbers, not ours.