Purpose
This note is the first entry point for people who want to use this project.
It is not the internal project ramp-up note.
It is the adopter-facing starting guide for:
- individuals
- Staff Engineers
- managers
- technical enablement leads
- teams exploring an initial pilot cohort
What this project is
This project is a practical delivery model for AI-enabled software teams.
It is designed to help teams use AI without collapsing into either:
no AI at allblind delegation
The core stance is:
paired engineering with verification, learning, and judgment still visible
What this package is not
- not a vendor catalog
- not a prompt-count adoption program
- not a universal rollout recipe
- not a justification for cutting apprenticeship before replacing it
Who should start here
Start here if you are asking:
- what this project is
- whether it fits your context
- where to begin without reading everything
- which artifacts matter for your role
Fast orientation
If you only read four things first:
- One-Pager - Paired Engineering at a Glance
- Project Charter
- Executive Deck - Paired Engineering for an Initial Pilot Cohort
- Practitioner Playbook - Paired Engineering with AI
Choose your starting path
If you are:
- an executive or sponsor: start with Executive Deck - Paired Engineering for an Initial Pilot Cohort
- a manager: start with Manager Deck Slide Copy - Leading Paired Engineering in Delivery Teams and Manager Coaching Guide - Paired Engineering in Delivery Teams
- a Staff Engineer or technical enablement lead: start with Staff Engineer Deck Slide Copy - Paired Engineering Through Influence
- a practitioner: start with Practitioner Playbook - Paired Engineering with AI
- a workshop facilitator: start with Workshop Pack - Paired Engineering with AI and Exercise Worksheet Pack - Paired Engineering with AI
- a public reader: start with Public Overview Deck Slide Copy - Paired Engineering
Then continue with Adopter Learning Path - Paired Engineering.
Smallest useful adoption pattern
Do not try to consume the whole framework at once.
The smallest useful starting pattern is:
- pick one workflow
- define one verification path
- choose one honest measure of improvement
- review what helped and what created hidden cost
Recommended first artifacts by need
If the problem is shallow rollout pressure
- Leadership Note - Capability Building Versus AI Cost-Cutting
- Leadership Note - Why Usage Metrics Are Not Adoption Metrics
If the problem is day-to-day team behavior
- Manager Coaching Guide - Paired Engineering in Delivery Teams
- Manager and Technical-Lead Responsibilities for AI Enablement
- Verification Standards by Artifact and Work Type
If the problem is workshop or skills development
- Workshop Pack - Paired Engineering with AI
- Exercise Library - Paired Engineering with AI
- Exercise Worksheet Pack - Paired Engineering with AI
If the problem is tool choice
Common mistake to avoid
Do not start by asking:
How do we get everyone using AI more?
Start by asking:
Which workflow are we improving, how will we verify it, and what hidden cost are we watching for?
Next step
Use Adopter Learning Path - Paired Engineering to choose a role-specific path through the project materials.