AI SDLC Consulting
AI training for software teams
Buying AI tools is the easy part. Using them well takes practice, shared habits and judgement about when not to trust the output. Our role-based, hands-on programmes teach developers, QA, architects and engineering leaders to work with AI on their own code, then coach them as the habits take hold.
Who this is for
For teams that want skills, not slideware
Generic AI courses rarely change how a team works on Monday morning. We build training around your stack, your tools and your development loop, so what people learn applies straight away.
Developers and QA engineers
People who use assistants daily and want to get dependable results, not just faster ones.
Architects and tech leads
People who set conventions, review AI-generated changes and decide where AI fits in the design.
Engineering leaders
People who need to plan adoption, manage risk and measure whether it is working.
What we do
Programmes shaped by role
Each programme mixes short explanations with plenty of hands-on work.
Developer track
Working in the plan, generate, review, test, refine loop, writing specs and prompts, and reviewing AI output critically.
QA track
AI-assisted test design, generation and maintenance, and how to judge whether a generated test adds real protection.
Architect track
Context engineering, guardrails, model and tool choices, and keeping AI-generated code maintainable.
Leadership track
Adoption planning, risk and governance, measuring productivity honestly and supporting teams through change.
Labs on your code
Exercises run against your own repositories or a realistic sample, so the practice transfers directly.
Follow-on coaching
Sessions after the workshops to answer questions on real work and reinforce the habits that matter.
What you get
What your team takes away
Materials and habits that outlast the workshop.
- Role-based workshops. delivered remotely or on site. [TBD: typical duration]
- Lab exercises. hands-on tasks your team can repeat and extend.
- Reference guides. short, practical notes on the patterns covered.
- Coaching sessions. follow-on support on live work.
- Skills check. a simple before-and-after view of confidence and practice. [TBD: metric]
How it works
How a training programme runs
Step 01
Plan
We talk to leads and a few team members about your stack, tools, skill levels and goals.
Step 02
Tailor
We adapt the tracks and labs to your codebase and the practices you want to adopt.
Step 03
Deliver
We run the workshops and labs with small groups so everyone gets hands-on time.
Step 04
Coach
We follow up on real work and adjust the material based on what people found hardest.
FAQ
Frequently asked questions
No. We assess starting points during planning and pitch each group accordingly, from first steps to advanced practice.
Yes. Training often follows an assessment or Loop Engineering pilot, so teams learn the way of working they will actually use.
Our cloud upskilling service covers cloud platforms; this programme focuses on AI in software delivery.
Related offerings
Keep exploring.
AI SDLC Consulting
All seven offerings for AI-enabled software delivery.
Loop Engineering
A plan, generate, review, test, refine loop your team can trust.
Prompt Engineering
Reusable, versioned, testable prompts for engineering teams.
AI-Enabled Test Automation
AI-assisted test design, generation and maintenance.
Right Tool for Each SDLC Stage
Vendor-neutral tool selection without the sprawl.
Contact Stavir
Tell us how your team works with AI today.