For boards, CTOs, and leadership teams
Your AI strategy is not the problem. Your execution plan is.
94% of organizations face AI implementation challenges despite it being a board priority. The gap is not vision — it is the bridge between strategy and reality.
Bain / AWS, 2025
How does 33coders move AI from strategy slides to shipped results?
AI Strategy Definition
Built on your actual capabilities, not a generic framework. I assess where you are, identify what is possible, and design a strategy that your team can actually execute.
AI Governance Framework
Only 5% of organizations feel prepared for AI workforce implications. I build governance that enables innovation instead of blocking it.
AWS / Bain, 2025
Rollout Planning
Successful organizations invest 70% of their AI budget in people and processes, not tools. I design rollout plans that reflect this reality.
BCG, 2024
Ongoing Advisory
A retainer model with bi-weekly sessions. I stay close to your progress, adjust the plan as reality evolves, and keep execution on track.
What does a 33coders leadership engagement look like?
Discovery
I start with a deep-dive into your current state. What AI initiatives exist, where they stalled, what governance is in place, what the team actually thinks (not what they say in meetings). This takes 1-2 weeks of interviews, document review, and an honest assessment you probably have not gotten yet.
Strategy
Based on what I found, I build a roadmap that accounts for your real constraints — budget, team capacity, technical debt, regulatory requirements. Not a 50-slide deck. A working document with clear priorities, timelines, and ownership assignments.
Execution
We implement in phases. Each phase has measurable outcomes, not just deliverables. I stay involved — reviewing decisions, unblocking teams, adjusting the plan when reality diverges from assumptions. Because it always does.
Ongoing support
Bi-weekly sessions to review progress, course-correct, and tackle new challenges. Plus async support between sessions for urgent questions. The engagement evolves with your needs.
Who this is for
- CTOs and VPs of Engineering building an AI strategy from scratch or restarting after a failed first attempt
- Leadership teams with stalled AI pilots that need someone who has shipped AI at scale to diagnose what went wrong
- Boards and executive teams that need an AI governance framework before regulators force one on them
- Organizations with 50-500 engineers where AI adoption is happening bottom-up but without coordination
Who this is not for
- Teams looking for a prompt engineering course — that is a team-level workshop, not a leadership engagement
- Companies wanting a chatbot slapped on their website — I work on organizational AI adoption, not single-feature development
- Anyone expecting overnight transformation — real AI adoption takes months of sustained effort, not a weekend sprint
Why does an operator-advisor deliver better AI results?
Most AI consultants operate from frameworks built on case studies and industry reports. I operate from daily practice. I lead AI adoption for 100+ engineers at a major Polish insurer every single day — making real decisions about tool standardization, governance enforcement, and productivity measurement. When I advise your leadership team, I am drawing on what I did this morning, not what I read in a report last quarter. That distinction matters because AI adoption fails in the details: the process that looked clean on a slide but breaks when engineers actually use it, the governance policy that blocks innovation instead of enabling it, the productivity metric that measures the wrong thing. I catch these failures because I live with their consequences daily. An advisor who only advises cannot see what an advisor who also operates sees every day.
What changed
A financial services company had 12 stalled AI pilots and no governance framework. Engineering teams were buying tools independently, legal was blocking everything, and the board was asking why they had spent 18 months with nothing in production. After a 4-month engagement: 3 pilots moved to production, a governance model was approved by the board, and the remaining pilots were either killed (saving budget) or given clear paths forward with timelines.
The cost of waiting
AI initiative abandonment accelerated from 17% to 42% in a single year. The organizations that waited for perfect conditions are the ones pulling the plug.
S&P Global, 2025
Common questions
How long is the typical engagement?
Most engagements run 3-6 months. Discovery takes 1-2 weeks, strategy definition takes 2-4 weeks, and the rest is execution support. Some clients continue with a lighter advisory retainer after the initial engagement.
Do you work on-site or remotely?
Primarily remote with regular video calls. For the discovery phase, I prefer at least one on-site visit if you are in Poland or nearby. For international clients, fully remote works well — I have done it for teams across Europe.
What industries do you work with?
Financial services, insurance, and technology companies are where I have the deepest experience. But the organizational challenges of AI adoption are remarkably similar across industries. If you have engineering teams and are trying to move AI from experiment to production, the patterns apply.
How is this different from a big consultancy engagement?
Big consultancies send junior associates who research your industry for two weeks, then present frameworks they have used elsewhere. I operate daily — I lead AI adoption for 100+ engineers right now. When I tell you something will not work, it is because I tried it this month, not because I read a case study.
What does the advisory retainer include?
Bi-weekly 60-minute strategy sessions, async support via email or Slack between sessions, document and decision reviews, and access to my network of AI practitioners. The retainer is month-to-month — no long-term lock-in.
Further reading on AI strategy
Read more on AI strategy and governanceLooking for team training?
If your teams need hands-on AI skills — Claude Code workshops, tools evaluation, or process automation — check the workshops designed for engineering teams.
30 minutes. No slides. Just clarity.
A direct conversation about where you are, what is blocking you, and what to do next.