AI-Powered Engineering Excellence
More software. Higher quality. Faster delivery through AI.
A comprehensive enablement and transformation program for AI-assisted software development. Measurable gains in developer productivity, delivery velocity and software quality through the professional use of AI.
Does this sound familiar?
- 01Copilot & co. are rolled out, but delivery isn't getting measurably fasterfound
- 02AI tools are used ad hoc — without standards, guidelines or shared workflowsfound
- 03Every team experiments on its own, and insights stay in silosfound
- 04It's unclear how AI usage fits your governance, security and code quality requirementsfound
- 05Delivery pressure keeps rising, but the team can't grow proportionallyfound
- 06Reviews, documentation and testing eat capacity that features needfound
From ad hoc tool use to real adoption
We combine assessment, enablement, tool integration, operational support and lasting knowledge transfer — built for organizations with established engineering teams, complex IT landscapes and high pressure to innovate and deliver.
Integrated, not isolated
AI-assisted ways of working get integrated into your existing development processes, toolchains, CI/CD pipelines and governance structures.
Proven standards
Standards for using Claude Code, GitHub Copilot, agentic workflows and modern developer platforms.
Real behavior change
Lasting adoption instead of one-off training or tool rollouts — anchored through champions and multipliers.
What you gain
- More software delivered with the same team
- Higher delivery velocity through AI-assisted development processes
- Faster turnaround on features and requirements
- Less manual effort on development, documentation and reviews
- Better code quality through best practices and AI-assisted quality assurance
- Lasting know-how instead of isolated tool rollouts
- Higher output from existing teams without proportional headcount growth
- Clear steerability through productivity, quality and adoption metrics
- Lasting adoption through internal champions and multipliers
- Faster time-to-market at equal or higher quality
Six phases to an AI-native engineering organization
Engineering Assessment
Analysis of existing development processes, tool landscapes, team structures and delivery metrics. Identification of concrete productivity levers and AI opportunities. Definition of a target state for AI-powered engineering.
Foundations & Enablement
Technical training on AI-assisted software development. Best practices for Claude Code, GitHub Copilot and modern AI coding workflows. Introduction of shared standards and guidelines.
Pilot Teams
Delivery of concrete pilot projects and pilot stories. Pair programming with AI. Direct application on real development projects. Measuring the first productivity and quality gains.
Operational Excellence
Integration into existing delivery, QA and CI/CD processes. Building governance, security standards and development guidelines. Shared methods for using AI in day-to-day engineering.
Scaling
Rollout to further teams and areas. Building internal AI champions. Train-the-trainer approaches. Community and knowledge-sharing formats.
AI-Powered Engineering Excellence
Lasting adoption of modern AI-assisted development processes. Continuous optimization of productivity, quality and delivery. Building an AI-native engineering organization.
How we work with your teams
Developer assessment
A technical inventory of your toolchain, CI/CD, repositories, coding standards and test coverage.
Foundations workshop
A compact technical introduction to LLM concepts, prompt engineering, security and data privacy.
Tool setup in the dev toolchain
Setting up and integrating AI tools — IDE plugins, CLI, CI jobs, code review assistants like Claude Code.
Coding best practices with AI
Patterns, anti-patterns, prompt templates, AI-assisted testing and safe use of generated code.
Hands-on workshops
Pair programming, live coding on real stories, AI-assisted debugging, before/after comparisons.
Pilot stories
Jointly implementing 1–2 pilot stories per team — fast value, reproducible workflows.
QA & integration testing
Test cases for AI outputs, automated regression testing and code quality metrics.
AI coaching & pairing
Ongoing support from AI coaches — code reviews, best-practice checks, troubleshooting.
Productivity metrics
Cycle time, PR size, review duration, bug rates and tool adoption at the team level.
Train-the-trainer
Training internal champions so skills and processes stay in the team and scale.
Compliance & secure use
Lightweight policies for secure model use and handling sensitive data in the code flow.
Development partnership (optional)
Time-boxed collaboration from experienced engineers and coaches embedded in your sprint cycles.
From the field
Retail group
Designed and rolled out a comprehensive AI enablement program for engineering teams — including workshops, tool evaluation, hands-on support and defined development standards.
Software & platform organization
Introduced structured standards for using AI in development and delivery processes.
Industrial company
Integrated modern AI-assisted ways of working into existing CI/CD and quality assurance processes.
Technology-driven scale-up
Built reproducible development processes and more efficient software delivery through modern AI coding tools.
Hands-on support for adopting and using Claude Code, GitHub Copilot, agentic workflows, and AI-assisted testing and review practices.
What companies use this for
How we can work together
Rapid Response Team
A small Aclue team delivers autonomously — from idea to production-ready solution.
Embedded Experts
Our specialists strengthen your team directly, on-site or remote.
Hybrid Team
A joint team of your people and ours — with knowledge transfer from day one.
Development Team
A complete development team for your product — including processes and operations.
Special Expertise
Targeted support: architecture, reviews, coaching, workshops.
More about our collaboration models →
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Learn more →Ready for AI-powered engineering excellence?
In a free initial conversation, we work together to identify the biggest productivity levers for your engineering organization.
Discuss engineering enablementEnablement-Team
„Wir befähigen Ihre Teams, KI im Alltag produktiv einzusetzen."
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