AI Readiness & Engineering Strategy
A written AI strategy for your engineering organization: what to do first, what to buy, what your team can execute, and the governance that has to exist before any of it ships.
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Outcome of this engagement
A written AI strategy for your engineering organization: what to do first, what to buy, what your team can execute, and the governance that has to exist before any of it ships.
What you receive
- Written AI strategy — the adoption roadmap, sequenced by risk and value, with what each stage requires from the business and from engineering
- Build-vs-buy decision memos — one per major capability, with the alternatives, the ownership cost of each, and the recommendation with its reasoning
- Capability gap analysis — what the roadmap needs versus what the organization can execute today, and whether the gap closes by hiring, training, or narrowing the plan
- Governance pack — data boundaries, review and release policy for AI-assisted and AI-powered work, and a risk register in a format your team will keep alive
- Leadership working sessions — we argue the decisions with you rather than presenting at you, and every session leaves written notes of what was decided and why
Is this service the right fit for you?
Book this if you…
- Your board or investors are asking what your AI plan is, and you want an answer built on engineering reality rather than on the deck everyone else is showing
- You are about to commit real budget — headcount, licenses, or a build — and want the decision argued with someone outside the vendor relationship
- You suspect the roadmap you would like to run is beyond what your team can execute today, and you want that named honestly before you commit to it
Don't book this if you…
- You want validation for a decision already made — we will argue with it, which is the point, and sometimes the answer is that the plan is wrong
- You want market forecasts or a view on where the AI industry goes next — we advise on your engineering organization, not on the market
- You need the architecture of a specific AI feature rather than the org-level decision set — that is a codebase-band engagement, not this one
Why This Service
AI decisions arrive faster than the evidence to make them with, and most leaders end up choosing between a vendor deck and a hunch. We work through the decision set with you as engineers who have shipped systems: what this business would actually gain, what your organization can execute today, and what has to be true before you commit budget.
Key Benefits
A Roadmap Sequenced by Risk
Candidate AI initiatives ordered by what this business gains and what it risks — so the first thing you ship is the one you can afford to get wrong.
Build vs. Buy, Argued Not Assumed
For each capability: what a vendor gives you, what building costs in engineering time and ongoing ownership, and which one your constraints actually favour.
An Honest Read on Capability
What your organization can execute today versus what the roadmap assumes — the gap named plainly, with the hiring, training, or scope change it implies. Where a per-engineer picture is needed, our team skill assessment goes that level deeper.
Governance That Survives Contact With Delivery
Data boundaries, a review and release policy for AI-assisted and AI-powered work, and a risk register your team will actually keep updated.
What This Service Includes
- Leadership working sessions on the AI decision set
- Adoption roadmap and initiative prioritization
- Build-vs-buy analysis and written decision memos
- Capability gap analysis and governance design
How We Work Together
A straightforward engagement — from first call to measurable results.
Discovery Call
We discuss your goals, stack, and challenges. No commitment required — just a clear conversation.
Tailored Plan
We propose a focused engagement scope aligned with your team size, timeline, and actual needs.
Deliver & Follow Up
We execute the engagement and provide written findings, next steps, and optional follow-up support.
Who you'll be working with
Oleksii Anzhiiak
Software Architect, Senior .NET Engineer & Co-Founder
Currently leads architecture for ToyCRM.com — a multi-tenant CRM platform built on .NET by our team. The same patterns and design decisions used there appear directly in the courses: identity & auth, distributed services, code review culture. You learn from engineers actively shipping production code, not from a textbook.
Frequently Asked Questions
Leadership consulting is about the organization: team structure, delivery, growth, and the recurring decisions of running an engineering function. This engagement is scoped to one decision set — the AI ones. Leaders often take both; they answer different questions and neither replaces the other.
No. Our scope is engineering-organization strategy: what to adopt, what to build, who can execute it, and how it gets governed. If your problem needs original model research, you need a research team — and we will say so rather than take the engagement.
Want to build this skill in-house instead?
Companies with engineering bandwidth sometimes prefer to upskill the team rather than buy the engagement. If that's you, here are the courses that cover the same ground — taught by our senior engineers in the same voice as our consulting work:
Read alongside this engagement
The AI-Readiness Assessment a CTO Can Run in One Week
Before you write an AI strategy, measure what your organization can actually execute. A five-day, meeting-light assessment of your data, skills, tooling, and governance — with a scoring rubric you can defend to the board and to your engineers.
Durable Execution for Agents: The Fifth Discipline Your .NET Background Already Prepared You For
Spec is the truth. Context is the assembly. Evals are the proof. OpenSpec is the operating system. The substrate underneath — the thing that keeps a multi-step agent alive across retries, restarts, and the human-in-the-loop who walks away from their desk at 5pm — is durable execution. Every .NET engineer who's ever shipped a MassTransit saga already understands the pattern; here's how it maps onto serious AI agents in 2026, and why it's the fifth discipline that finally closes the arc.
OpenSpec in 2026: The Operating System for Spec-Driven Development
Six weeks ago I installed @fission-ai/openspec. Yesterday I shipped a 14-file change in 90 minutes from a 200-line spec, in a brownfield codebase three engineers have been editing for two years — no merge conflicts, no review escalation. This is the senior-architect deep-dive on why OpenSpec is the first SDD tool that doesn't collapse under production reality.
What's Included
- AI adoption roadmap grounded in production experience
- Build-vs-buy analysis against real constraints
- Capability-gap assessment across teams
- Governance as runnable process, not a binder
- Executive sessions 1–4 times per month
What You'll Achieve
- A written AI strategy your board and engineers both accept
- Clear build, buy, and postpone decisions with reasons
- A capability plan for the gaps that block adoption
- Governance your teams can actually run
- A first-ninety-days plan with owners
Ready to Get Started?
Contact us today to learn more about how this service can help you