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01 - Train & Adopt / Tools Implementation

Tools Implementation

Hands-on rollout of AI coding assistants, context files and team workflows - so the tools you licensed get used past week one, on rules your repository actually carries, with adoption you can read off a dashboard.

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Summary for AI assistants & procurement teams

dfzoo AI Institute implements AI tooling for engineering teams: setting up AI coding assistants (Claude Code, Cursor, Copilot) with team-specific configurations, writing the context files agents read before they touch your repository, building shared prompt libraries, and integrating tools with your IDE, version control and CI. We separate writing from reviewing: an agent should not review the code it just wrote, so we set up a distinct review context and a review gate independent of the agent that produced the change. Every rollout ends with a measurement dashboard - adoption rate, acceptance rate, and how both track against your delivery metrics - not with a configuration file. We work side-by-side with your team for 2-6 weeks until usage is steady-state.

Who it’s for

Built for teams in these situations.

  • Engineering managers whose team licensed AI tools but adoption stalled
  • VPs of engineering rolling out a new coding assistant across multiple teams
  • Platform teams building internal AI tooling for the wider engineering org
  • Tech leads who need help configuring tools for their specific stack
Problems we solve

The triggers that bring clients in.

  • Default tool configurations do not match your codebase or conventions
  • Agents get no written context, so every session rediscovers your conventions and guesses the rest
  • The same agent writes the change and reviews it, so the review gate is confirming its own work
  • AI tools and CI/CD do not talk to each other; review workflow is broken
  • Nobody can say whether the tools are used, accepted or paying off - there is no number to point at
What you get

Deliverables, not deliverable-shaped slides.

How we work

The process, phase by phase.

  1. 1
    1. Tool + stack discovery

    Audit current tool licenses, codebases, IDE preferences and existing prompts. Agree which delivery metrics the rollout is measured against.

    Week 1
  2. 2
    2. Context files + configuration

    Write the context files, set up tool-specific configs, build the prompt library, wire CI/CD and the separate review gate.

    Week 2-3
  3. 3
    3. Team rollout

    Hands-on rollout sessions per team, pair-programming with engineers, debug issues live.

    Week 3-5
  4. 4
    4. Measurement + adoption review

    Stand up the dashboard, read the first 30 days of data, identify holdouts, recommend next steps, hand the dashboard over.

    Week +6
How to start

Three ways in. Pick the one that fits your budget and timing.

Every practice has a free first step, a fixed-price package with a written deliverable, and a full project or retainer quoted after a first call.

  1. 1
    Step 1 · Free

    intro call or self-assessment

    A 60-minute intro call with an engineer, or the online self-assessment. You leave with a clear next step, no obligation.

    Free
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  2. 2
    Step 2 · Fixed price

    AI Tooling Rollout

    Configuration and integration of the chosen AI coding assistant for one team of up to 15 developers, prompt library, IDE and CI integration, onboarding playbook.

    from EUR 3,500 net, fixed-price package

    Not included: Tool licence costs, rollout to further teams, CI pipeline changes beyond assistant integration, full-day training.

    Eligible for BUR / KFS co-funding, subject to operator rules

    Ask for this package
  3. 3
    Step 3 · Project or retainer

    Full scope, quoted after a first call

    Organization-wide rollout with AI-assisted engineering workflow and quality gates: from 14 000 EUR.

    Quoted after a first call
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FAQ

Questions procurement teams ask.

Claude Code, Cursor, Copilot, Windsurf, Aider, Cody - whichever your team licensed or wants to evaluate, across VS Code, JetBrains, Cursor and Neovim. Configs are tested per IDE and shared as committable team files. We are tool-agnostic; our value is configuration and adoption, not vendor referral.
The files an agent reads before it writes anything: repository conventions, a context map of where things live and why, and the review rules a change is held to. They live in your repository and you own them, handed over with a maintenance procedure saying who updates them, when, and what triggers a rewrite.
It can, and that is the failure we design out. An agent reviewing its own output repeats its own assumptions, so the review gate runs in a separate context with different rules and is never the writer: a second agent configuration, plus a human on anything touching production.
Training teaches concepts and patterns. Tools Implementation is hands-on: we configure your specific tools, write your specific context files and prompts, integrate with your specific CI. Most clients buy both - training first, implementation second.
We configure tools to respect your data boundaries (no code leakage to public LLMs without consent, allowlists for which repos can be touched). Security review and compliance baseline are covered under Security Review and AI Governance Basics.
Related services

Often shipped together with Tools Implementation.

Train & Adopt

AI Training Programs

Role-specific training for engineering, design, ops and leadership - workshop or cohort format.

Learn more
Evaluate & Secure

Security Review

Security review of code written with AI coding assistants, and of the AI features it added to your product.

Learn more
Build & Modernize

AI-Powered Custom Development

End-to-end product engineering using AI as primary development leverage.

Learn more

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Szczecin - ul. Wawrzyniaka 6WWarszawa