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This repository is a central home for all AI Engineering Lab content across government departments. It provides reusable guidance, templates, training materials, and practices for safely and effectively adopting AI code assistants.
| Section | Description |
|---|---|
| Code of conduct | Contributor covenant code of conduct |
| Contributing | How to contribute to the AI Engineering Lab repository |
| Repository structure | Structure of the repository |
| Assessment | Readiness and maturity evaluation |
| Governance | Guardrails, compliance, and department-specific frameworks |
| Manager tool guides | Tool deployment and management guidance for leads |
| User tool guides | Developer user guides for AI tools |
| Playbooks | AI SDLC, context engineering, and model selection guidance |
| Policy | Strategic policy and compliance frameworks |
| Prompt library | Tested prompts organised by task and language |
| Quality metrics | Quality strategy and measurement frameworks |
| Security | Security policies and threat modelling guidance |
| Sustainable AI | AI environmental sustainability |
| Training materials | Onboarding, scenarios, and guided learning paths |
This repository is for:
- software engineers and engineers seeking practical guidance on using AI assistants effectively
- technical leads and architects establishing team standards and patterns
- delivery managers and product owners planning adoption within their teams
- senior responsible owners requiring governance and compliance assurance
- forward deployed engineers supporting intensive adoption engagements
- Read how AI code assistants integrate into the SDLC for an overview of deployment patterns and capability maturity.
- Read the AI assisted SDLC playbook for phase-by-phase guidance.
- Review the guardrails to understand usage boundaries.
- Explore the prompt library for proven patterns.
- Read how AI code assistants integrate into the SDLC to understand deployment options and the capability maturity progression.
- Review context engineering for repository setup.
- Establish baseline metrics using the quality strategy.
- Consider requesting forward deployed engineering support for your rollout.
- Read how AI code assistants integrate into the SDLC for an overview of what adoption involves.
- Start with comparative guidance to evaluate tools.
- Review tool-specific guides for GitHub Copilot and Amazon Q.
- Review the model selection playbook.
- Review all governance documentation in the governance folder.
- Understand the 'Risk register template'.
- Review the 'Incident response playbook'.
The programme maintains a pool of expert senior engineers with extensive AI assistant experience. Forward deployed engineers provide intensive, hands-on support for teams requiring additional help.
Forward deployed engineering support is appropriate for:
- teams with low AI maturity requiring intensive guidance
- complex technical environments or niche requirements
- important adoption challenges requiring immediate intervention
- capturing learnings for repository enhancement
To request forward deployed engineering support, contact [email protected] with:
- a completed readiness checklist
- team details
- specific support needs
To find what you need:
- use the quick start guides based on your role
- browse the repository structure for specific topics
- use your browser or IDE search functionality within documents
You can stay up to date by:
- subscribing to repository updates on GitHub
- reviewing documents against their stated review dates
We welcome feedback to improve these materials. You can submit improvements via pull request (see CONTRIBUTING.md) or contact the team at [email protected].
We encourage contributions from across government to keep this repository current and comprehensive.
Before contributing, read CONTRIBUTING.md which covers:
- content standards and style guide
- review and approval process
- accessibility requirements
- how to submit changes
Contact [email protected] for general enquiries.
Explore the AI Engineering Lab website to understand the programme and find resources and role-specific information.
Join the Knowledge Hub community to connect with other cross-government teams, share experiences and access events and support.
This repository is published under the Open Government Licence v3.0.
You are encouraged to use and adapt these materials for your own government context.
When reusing content:
- credit the original source by linking to this repository
- maintain all existing copyright notices and licence headers
- share improvements back via contribution
- ensure adaptations remain suitable for government use