Predictable ROI
from AI-Assisted
Engineering.

When AI tools increase individual coding speed, they typically increase PR sizes by 15–20%. Those larger, faster-arriving PRs land in the review queue of your most senior — and most expensive — engineers. Your developers are faster; your review pipeline isn't. The result is flat or worsening organisational lead time despite real improvements in individual output. Review Economics is the discipline of measuring and resolving that bottleneck — it's the difference between AI making your organisation faster vs. making individuals faster while the organisation stalls.

Yes — DACH (Germany, Austria, Switzerland) and Nordic (Sweden, Denmark, Norway, Finland) are my primary markets. I understand both the regulatory landscape (EU AI Act, GDPR, Works Council requirements under § 87 BetrVG) and the engineering culture. Based in Kraków, Poland (CET/CEST), I cover EU business hours naturally. I also work with UK and US enterprises — particularly those with European subsidiaries navigating EU AI Act compliance obligations for their engineering teams.

Article 4 requires organisations deploying AI systems to ensure staff have sufficient AI literacy to understand the capabilities, limitations, and risks of the tools they use — including AI coding assistants. This is not just a training checkbox. It requires documented competency assessment, a governance framework, and for DACH enterprises, a Works Council-approved deployment plan ensuring AI tools aren't used for performance monitoring, as required by German labour law (§ 87 BetrVG). Organisations without this documentation are exposed in any future audit or Works Council dispute.

SDD uses machine-readable specifications — not prose Jira tickets — as the authoritative source of truth. A formal spec defines behaviour, contracts, and acceptance criteria in a structured format that AI agents can consume directly. Instead of an LLM guessing intent from a description, it generates code from a deterministic spec — dramatically reducing rework and eliminating hallucinated logic. Typical outcome: feature implementation time drops from days to hours. I build the full toolchain: spec format, agent pipeline, output validation, and CI integration to verify spec conformance automatically.

I'm accepting 1 new engagement for Q2 2026. I cap active engagements deliberately to protect the quality of every client's work — so book a discovery call this week if your timeline is urgent. The call typically happens within 2–3 business days. We spend 30 minutes on your current AI tooling stack, delivery metrics, and regulatory exposure. If there's a clear fit, I scope a fixed engagement within 48 hours. No lengthy proposals, no retainer lock-in upfront.