Five ways in. Same method.

Advising enterprise clients since 2021 on where AI actually belongs in their operation and, more often, where it doesn’t. The work is roadmap, sequencing and integration: which processes change, what the technology has to prove before it is trusted, and how the deployment aligns with the budget and the KPIs someone is already accountable for.

A staged implementation plan with named owners, a working pilot, and the measurement to tell you whether it did anything.

Multi-agent architectures with persistent memory, defined skills, business rules and safety guardrails, not a chatbot bolted onto a form. An agent is designed the way you would write a job description: what it knows, what it is allowed to do, whose rules it follows, and where it must stop and ask.

Built on current agentic frameworks and multi-model orchestration. A review layer checks the system’s output before it reaches anyone.

When the capability doesn’t exist off the shelf. C#/.NET 8 and WPF for Windows field tooling, Python and Google Apps Script for automation and data pipelines, React and Firebase for web applications. All specified in-house and built with AI coding tools. On the hardware side: reverse engineering, PCB design, 3D CAD, printing, and CNC.

The point isn’t the technology list. A problem doesn’t get parked just because it crosses the line between software and physical objects.

From live broadcasts to a regulatory deadline: thirty years of running things that must work on a schedule. Today that means forecasting, budgeting, KPI design, field team performance, inventory protocol, regulatory compliance (Enaon EDA, Greek net metering, GDPR), and executive reporting.

This is usually the part that decides whether the technical work survives.

Taking over Google Ads, Merchant Center and analytics accounts from a previous agency or marketer, for businesses whose reporting has stopped meaning anything. The first job is almost always the same: find out whether the conversion data can be trusted before anyone spends against it.

An audit first: who has access, what tracking measures, an honest baseline, what the previous setup did. Then a phased rebuild where nothing is deleted and nothing new goes live unreviewed.