Agentic Engineering Bootcamp

Ship real ticketswith coding agents.

A hands-on bootcamp in your own codebase. Your engineers use Claude Code and Codex on real tickets, learn where agents fail, and keep the workflows, prompts and guardrails they build.

OpenAI Partner · 5 certified engineersMerged work / Workflows / Guardrails

Why it matters

Coding agents are fast. Your team needs to know where they fail.

Where
In your codebase, on tickets from your own backlog.
Tools
Claude Code and Codex by default, or the tools your team already has approved.
Access
The permissions and environments your security team approves.
Who
Engineers at any level. No AI experience needed.

Run by forward deployed engineers from an OpenAI partner, with 5 certified engineers.

How it works

Learn on real work, not toy examples.

Every session uses your codebase and your backlog, so what the team learns works on Monday.

  1. Set up

    Prepare the codebase

    Agree the repositories, tickets and access. Set up the agent tools with the permissions your security team approves.

  2. Ship

    Pair on real tickets

    Engineers work real tickets with coding agents, from planning to tests to review. We coach in the session, not from slides.

  3. Break

    See where agents fail

    Work through the failure cases on purpose: wrong assumptions, silent test gaps, unsafe changes and leaked secrets.

  4. Keep

    Make it the team's way of working

    Write the team's agent instructions, review checklist and guardrails into the repo. The bootcamp runs over two days for up to 12 engineers.

Scope

What the team practises.

The bootcamp covers the full loop, not only prompting.

  • Plan

    Scoping work for an agent

    Turning a ticket into a task an agent can do well, with clear checks for done.

  • Build

    Agent-driven implementation

    Using Claude Code and Codex to write, refactor and test code in a large, real codebase.

  • Review

    Reviewing agent-written code

    What to check, what to distrust and how to keep pull requests small enough to review.

  • Secure

    Safe agent use

    Permissions, secrets, sandboxing and the changes an agent must never make alone.

What you take away

Deliverables your team keeps.

Everything we produce belongs to your team and lives in your accounts and repositories.

  • Yours to keep

    Everything we make is yours.

    Every output stays in your accounts and repositories when we leave.

  • 01 / Shipped

    Real work merged

    Tickets from your own backlog, shipped and reviewed during the bootcamp.

  • 02 / Workflows

    Agent setup in your repo

    Instruction files, commands and checks the whole team uses after we leave.

  • 03 / Guardrails

    Rules for agent-written code

    A review checklist and security rules your team agreed and can enforce.

  • 04 / Baseline

    A before-and-after measure

    The measure the team chose, for example cycle time or review time, taken before and after.

Sample output

What stays in your repo.

The bootcamp ends with files in version control, not slides in a shared drive.

your-repository/Illustrative format
  • AGENTS.mdTeam instructions the agents read on every task
  • .claude/commands/Shared commands for planning, testing and review
  • docs/agent-review-checklist.mdWhat reviewers check in agent-written code
  • .github/workflows/agent-checks.ymlAutomated checks on every agent pull request
  • docs/bootcamp-baseline.mdThe before-and-after measure the team chose

Illustrative format. File names and contents depend on your repository, your tools and the rules your team agrees.

Useful answers

Before we start.

Discuss anything specific to your team or environment.

Which tools do you use?

Claude Code and Codex by default. We can work with the tools your team already has approved.

Do engineers need AI experience?

No. The bootcamp starts from your codebase, not from AI theory. Experienced users go deeper on review and safety.

Is our code safe?

We use the permissions and environments your security team approves. We agree the repositories and data in scope before we start.

How is this different from AI Training?

AI Training teaches teams to build AI features. This bootcamp teaches engineers to use coding agents to build any software faster and safely.

The next step

Put agents to work on your backlog.

Request a technical call

We’ll confirm fit and the scope in writing before any work begins.

Agentic Engineering Bootcamp — real tickets, your codebase
Request a technical call