● New release — 2026 · 200 pages · Kindle & Paperback
How Domain Experts Stay Relevant in the Age of AI. A practical guide for mid-level professionals who want to stay relevant — not by abandoning their expertise to chase AI certifications, but by coupling deep domain knowledge to the right tools in the right way.
AI is not replacing domain experts. It's replacing domain experts who don't adapt. The professionals at greatest risk are not those with the least experience — they're the ones with significant expertise whose value is primarily in execution rather than judgment.
Still Standing gives you the framework to identify exactly where your value lives, which tools to invest in learning, and how to redesign your workflows so that AI amplifies your expertise rather than replaces it.
Written from inside one of the world's most disrupted industries — automotive engineering — by a professional who has built the AI-augmented systems he writes about. Not theory. Not consulting advice. The real view from the inside.
Does this touch knowledge only you can supply?
Is this task high-frequency or high-stakes enough to invest in?
Can the outcome be fully specified for a machine to execute?
Does AI raise your ceiling, or just lower your effort floor?
▲ The DWAR Framework — core tool of the book
Pattern memory, failure knowledge, stakeholder intelligence, and systems intuition — your real professional capital, and how to develop each one deliberately.
A four-question test that tells you exactly which tasks AI should own, which need your expertise, and where the highest-leverage automation opportunities are.
Mapping your full workflow — not just automating individual tasks — to find where AI transforms the ceiling of what you can deliver, not just the effort floor.
Five questions to ask any AI recommendation before acting on it. When to trust the algorithm and when your domain expertise is telling you something it can't see.
Specific, actionable roadmaps for Manufacturing, Finance, Healthcare, Logistics, Human Resources, and Marketing — with real examples from each sector.
A sustainable sequence from automating your most painful reporting task to building domain-specific AI workflows that express your expertise at scale.
Part I
What domain expertise actually is — and why it matters more than ever in an AI-augmented world
Part II
The DWAR framework, a 12-month learning roadmap, and your first month of real AI automation
Part III
How to redesign entire workflows — not just automate tasks — and build orchestrated systems that run themselves
Part IV
Understanding, critiquing, and owning AI-assisted decisions — including when and how to override them
Part V
Dedicated chapters for Manufacturing, Finance, Healthcare, Logistics, HR, and Marketing professionals
Part VI
Career management through the transition, professional identity, and a framework for continuous relevance
Automotive, manufacturing, software, and systems engineers who want to position deep technical knowledge in a world of AI-assisted development.
Financial analysts, controllers, and risk managers whose analytical work is being transformed — and who need to know where their judgment adds irreplaceable value.
Mid-level managers facing the dual challenge of using AI to improve their team's productivity while maintaining their own relevance.
Clinical and operations professionals navigating AI tools in high-stakes environments where domain judgment remains the essential check.
People and communications specialists grappling with AI-generated content, automated screening, and where genuine human judgment is irreplaceable.
If you've spent a decade becoming genuinely excellent at something — and wonder whether that still counts — this book answers directly and honestly.
● Available now — Kindle & Paperback
The professionals who adapt now will be the ones still standing.
200 pages · 16 chapters · six industry playbooks · one clear framework.