Before a prep call and a short questionnaire. We map your stack, your tools, and your constraints — including what your corporate environment does and doesn't allow — and design the exercises around them. The workshop runs on your real setup, not a demo repo.
Private AI-SDLC workshop
What a private AI-SDLC workshop actually leaves your team with
Two days, hands-on, on your stack. Your team leaves aligned on one way of working with AI — with working agent setups, guardrails, and an adoption plan they can iterate on. Not a tools tour. Not an inspiration session.
Why generic AI training doesn't stick
Every team has its own SDLC. Different constraints, different review culture, different definition of done. So every team ends up using AI differently — and a workflow copied from a conference talk or another company's blog post rarely survives contact with your codebase.
Engineers who've been through our workshops arrive at the same conclusion themselves: there is no one-solution-fits-all for agentic workflows. Whatever your team adopts has to be adapted to your project's needs — tried, tested, then standardized.
That's why this workshop is private and built around your stack, not a generic curriculum.
The gap isn't between companies — it's inside your team
In the teams we work with, the split looks the same: a few engineers are far ahead — experimenting, building their own custom agent workflows — while most are still at the prompting stage. Individual speed diverges; the team's way of working doesn't change at all.
Change starts with getting everyone onto a shared baseline and putting something concrete on the table the team can iterate on. That's the job of these two days.
The two days
Day 1 — align. Where AI actually helps across your lifecycle — requirements, code, review, testing, release — and where humans stay in the loop. Hands-on from the start: pre-planned exercises scoped to complete within your environment, with tracks for engineers already building agent workflows and for those still prompting.
Day 2 — build. One complete end-to-end example on your stack — from ticket to reviewed, tested change — then teams apply the same pattern to their own workflows. The goal is explicit: leave with working setups, not notes.
After your team keeps everything: the agent setups, a prompt/skill library seeded with your workflows, guardrail definitions (where agents act, where humans approve), and an adoption plan to iterate on. If you want help running that plan, that's what adoption support is for.
Who it's for — and not for
For
- Engineering teams of 10–60 developers — including teams inside much larger organizations
- Already using Cursor, Copilot, or Claude Code: individual productivity is up, team-level delivery isn't
- Review, testing, release, or coordination is now the bottleneck
Not for
- Teams looking for an AI inspiration talk — this is work, not a keynote
- Teams that haven't put AI coding tools in developers' hands yet
- Outsourcing — we don't deliver your roadmap; we change how your team delivers it
Milko Slavov
Founder · AI-SDLC.services
Who runs it
Milko Slavov — 20+ years shipping software, IC → Staff Engineer → CTO, US patent holder. I build with background agents daily and write about it publicly, wins and failures — you can see how I think before you book anything.
Delivered as public editions through conf.ai and privately — a 2-day workshop for an enterprise infrastructure company.
Frequently asked questions
What engineering leaders ask before the workshop.
- What is included in a private AI-SDLC workshop?
- The engagement includes preparation around the team's stack and constraints, two hands-on workshop days, one end-to-end workflow example, working agent setups, a prompt and skill library, guardrail definitions, and an adoption plan the team can continue using.
- Is the workshop customized to our engineering stack?
- Yes. A preparation call and questionnaire map the team's stack, tools, workflows, and corporate constraints. The exercises are then designed around the team's real environment rather than a generic demonstration repository.
- Who should attend the workshop?
- It is built for engineering teams already using AI coding tools where individual productivity has improved but review, testing, release, or coordination remains a bottleneck. It is not an introductory inspiration talk or an outsourcing engagement.
- What does the team keep after the workshop?
- The team keeps the working agent setups, a prompt and skill library seeded with its workflows, definitions for where agents can act and where humans approve, and an adoption plan for continued iteration.
Tell us what's slowing your team down
The form takes two minutes. Describe your team, your tools, and where delivery drags — you'll get a straight answer about whether a workshop would help, within two business days.