Mike Luloh

AI Training for
Regulated Industries

The slope is real, but the timeline is wrong. Practical AI guidance for engineering and R&D leaders in medical devices, pharma, and life sciences.

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The Problem

Most AI training isn't built for regulated industries.

The training options available to R&D leaders are either too generic (prompt engineering for beginners), too theoretical (strategy decks with no practical application), or too technical (ML courses built for data scientists). None of them account for design controls, 62304, 14971, audit trails, or the reality that "move fast and break things" doesn't work when the thing is a surgical instrument.

Our Approach

Judgment over enthusiasm.

AI is a powerful tool that produces its best work when guided by domain expertise and good judgment. Without that, it generates confident-sounding output that can be generic, wrong, or risky in regulated environments. This program focuses on what works reliably today, what's genuinely emerging, and what's still hype.

We help you make good decisions about AI. Not sell you on it.

The Format

45 minutes a week. No homework.

Traditional AI courses deliver a fixed curriculum that's outdated before you finish. This program is built to evolve. Structured enough to build real capability, fluid enough to respond when FDA drops new guidance or a tool changes overnight.

Live demos

Practical AI workflows you can use the same day. Not slides. Real tools, real work.

Weekly briefing

"What changed this week in AI," curated for regulated industries. We filter the noise so you don't have to.

Open Q&A

Tied to your actual work. Bring real problems, get real answers.

What We Cover

Topics include, among others:

Practical AI Skills

What works today, what's hype, and how to tell the difference, with live side-by-side comparisons

AI-assisted technical writing in regulated environments (and where it hallucinates dangerously)

AI for engineering leadership: synthesizing project status, spotting schedule risks, preparing for design reviews

AI in the Regulated Product Lifecycle

AI and IEC 62304: what's possible, what's permissible, what's coming

Accelerating DHF documentation without compromising compliance

AI for risk management (ISO 14971): hazard analysis, FMEA, and new risks AI introduces

Evaluating AI/ML-enabled medical devices: SaMD classification, FDA guidance, strategic implications

Strategic AI Leadership

Rolling out AI tools to your engineering team, Monday morning, without creating a compliance nightmare

AI vendor evaluation: how to cut through the pitch decks and avoid a 6-month POC that goes nowhere

A capability maturity map: what works now, what's emerging, and what's still vaporware, updated continuously

Your Instructor

Mike Luloh

30 years in safety-critical software engineering, including 24 years at Alcon in Director-level R&D roles. Applied software engineer who built real-time LASIK control software, invented novel optical metrology methods for IOL production, and led development of cloud-based surgical planning platforms serving 100,000+ surgeries monthly. AAMI SM/WG 01 voting member on the IEC 62304 international standards committee.

Engagement Options

Three ways to work together.

Individual

Weekly cohort sessions with peers from across the industry. Learn what's working, what isn't, and what to do about it.

Team

Private cohort for your leadership team. Tailored examples, shared vocabulary, aligned decision-making.

Executive 1:1

Private advisory for leaders who need a trusted guide on AI strategy, vendor decisions, and org readiness.