Thoughts on AI product management, automotive technology, and building great products. Practical perspectives from 15+ years in the industry.
In early 2026, a bombshell study from the National Bureau of Economic Research (NBER) dropped: 6,000 CEOs, CFOs, and executives across the U.S., U.K., Germany, and Australia admitted AI has had lit...
AI project failure is primarily a leadership and organizational problem, not a technical one. Here's what really goes wrong and how to fix it.
Most founders scale without answering fundamental strategic questions. Here are the 6 questions that prevent unfocused growth and team misalignment.
OKRs are powerful, but most AI teams implement them wrong. Here's how to set meaningful objectives and key results for AI projects at every stage.
Bad meetings are the biggest hidden tax on tech companies. A 10-person team wastes €200K+ annually. Here's how to fix them with the Meeting Maximizer framework.
Most AI strategies are built on borrowed assumptions. First principle thinking strips these away to find what actually matters for your business.
In 2024, fine-grained visual reasoning—the ability to analyze images with human-like precision—remains the biggest unsolved challenge for enterprise AI. Traditional vision-language models (VLMs) li...
Your EHR data is lying to you.
In 2024, European enterprises face a critical challenge: scaling AI projects while maintaining transparency and compliance. The ArchWiki, a community-driven technical documentation resource for Arc...
At any point in time, every company has one metric that matters more than all others. Finding and focusing on your Critical Number is the highest-leverage strategic decision you can make.
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Binary goals set teams up for failure. The MTO system — Minimum, Target, Outrageous — gives teams a range that motivates performance at every level and makes quarterly planning actually useful.
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Greece announced a landmark EUR 150 million AI support scheme for SMEs. Here's how Hyperion Consulting helps Greek businesses seize this once-in-a-generation opportunity.
Verne Harnish's One-Page Strategic Plan has helped thousands of companies from startups to Fortune 500s align their strategy on a single page. Here is how to adapt it for tech companies.
Your marketing message is confusing. The Before/During/After framework cuts through the noise and gives potential customers the clarity they need to say yes.
How does your industry compare on AI adoption? Based on 200+ enterprise assessments across Europe, here's where each sector stands — and where the opportunities are.
Enterprise deals are won or lost in discovery. This 12-question framework, adapted from Confident Conversions, ensures you understand the buyer's world before you pitch your solution.
Most AI products fail not because the technology is bad, but because they are positioned as vitamins instead of painkillers. The Kellogg urgency framework reveals why — and how to fix it.
70% of AI proofs-of-concept die before deployment. The failure isn't technical — it's structural. A 4-phase framework to bridge the gap from impressive demo to reliable production system.
Two-thirds of employees say they would leave if they did not feel appreciated. The 5 Languages of Appreciation at Work gives you a practical system for fixing this — before your best people walk out the door.
Most founders hire too early or too late. Here is the actual math — cost of delay vs. cost of hiring — that tells you exactly when to make the leap.
You are not too busy. You are too undisciplined about what you spend your time on. The Eisenhower Matrix, adapted for tech leadership, is the fix.
Delegation is essential, but some decisions should never leave the CEO's desk. Here are the 10 decisions that define your company's trajectory — and why delegating them is the most expensive mistake you can make.
Most culture initiatives drag on for months and produce generic values nobody remembers. The Culture Identifier framework gets you to authentic, actionable culture in a single focused day.
Traditional feedback is broken. Marshall Goldsmith's Feed Forward method focuses on future improvement rather than past mistakes — and the results speak for themselves.
From 'AI will replace all our developers' to 'we need perfect data first' — these persistent myths are costing companies millions in missed opportunities and failed initiatives.
Trust is the operating system of high-performing teams. Brené Brown's BRAVING framework gives you a concrete, actionable way to build and repair it — especially in distributed tech teams where trust erodes fastest.
Most strategy meetings fail because leaders ask the wrong questions. Here are 21 coaching-grade questions that cut through politics, assumptions, and groupthink to reach real strategic clarity.
Jim Collins' Hedgehog Concept is one of the most powerful strategy frameworks ever created. Here's how AI companies can use it to find their strategic sweet spot and stop chasing every shiny opportunity.
The EU AI Act enforcement deadline is approaching fast. Here's a practical compliance roadmap for enterprise AI teams — with timelines, risk classifications, and concrete action items.
The role of product manager is evolving faster than ever. In 2026, AI fluency isn't optional—it's essential. Here's what separates successful AI PMs from those left behind.
Forget the race to build bigger models. In 2026, the smartest enterprises are deploying smaller, specialized language models that run faster, cost less, and perform better for specific tasks.
The factory floor is becoming intelligent. Edge AI enables real-time quality inspection, predictive maintenance, and autonomous operations—but getting from pilot to production requires careful architecture.
Building AI in-house costs 3-5x what vendors quote. Buying locks you into someone else's roadmap. A TCO framework with real numbers to make the right call for your organization.
GPT-4 API costs $100K/month at scale. Self-hosted Llama 3 70B? $15K. Compare Llama, Mistral, Qwen and DeepSeek — with real deployment architectures, cost breakdowns, and security checklists.
Prompt injection is the #1 security vulnerability in production LLM systems. Here's how to defend against it with layered security — from input validation to output filtering.
The EU AI Act's high-risk requirements take effect August 2, 2026. Fines reach €35 million or 7% of global turnover. Here's exactly what you need to do—and when.
Your RAG demo works perfectly. Production is a disaster. Hallucinations, 3-second latency, costs 10x over budget. 7 battle-tested techniques to fix retrieval, reduce hallucinations, and cut inference costs.
Everyone's talking about AI agents. Your board wants an 'agentic AI strategy.' But most agent deployments fail. Here's how to build production agents with proper guardrails.
Exploring how the automotive industry can leverage collective intelligence and open collaboration to accelerate SDV development and innovation.
A comprehensive look at how the automotive industry is transforming through software-defined architecture and what it means for the future of mobility.
How product management practices must evolve to address the unique challenges of AI and Web3 technology startups.
How digital platforms are enabling new forms of innovation and value creation in the software-defined vehicle ecosystem.
Weekly AI implementation insights for leaders who ship.
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