My takeaway is simple: The next 2 to 3 years will reward companies that do 3 things well: → use AI internally, so leadership understands it firsthand
→ build with a clear path from pilot to industrialization
→ take control of their own models, data, and evaluation strategy
@ronald_vanloon
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Three Keys for Companies to Master AI in 2026-2028
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AI Transforms Software Development: Testing, Evaluation, Optimization
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The shift happening right now is bigger than "which model should we use?" AI is becoming a new way of building software. That means leaders need to think in terms of: → test cases
→ evaluation frameworks
→ feedback loops
→ continuous optimization If you cannot define -
Open Custom Models Strategic Advantage Over Vendor Lock-in
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The second big insight, open and custom models are becoming a strategic advantage, not just a technical preference. Why? → More control over your AI stack
→ Less vendor lock-in
→ Better fit for regulated industries
→ More value from your own enterprise data and IP General -
Enterprise AI Success: Evaluation Over Model Selection
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Most enterprises do not have an AI model problem.
— Ronald van Loon (@Ronald_vanLoon) 15 avril 2026
They have an evaluation problem.
That was one of my biggest takeaways from my conversation with @karibriski from Nvidia and @Toucas from Mistral AI at GTC.
In the agentic era, the winners will not be the companies running the… pic.twitter.com/woUGWQp3MkMost enterprises do not have an AI model problem. They have an evaluation problem. That was one of my biggest takeaways from my conversation with @karibriski from Nvidia and @Toucas from Mistral AI at GTC. In the agentic era, the winners will not be the companies running the
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BeingBeyond U1: Advanced Robotic Dexterity Innovation
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Meet BeingBeyond U1: Redefining #Robotic Dexterity Beyond Grippers
— Ronald van Loon (@Ronald_vanLoon) 15 avril 2026
by @beingbeyond_#AI #Robots #Engineering #ArtificialIntelligence #Innovation #Technology pic.twitter.com/5sruYvmkKSMeet BeingBeyond U1: Redefining #Robotic Dexterity Beyond Grippers
by @beingbeyond_ #AI #Robots #Engineering #ArtificialIntelligence #Innovation #Technology -
AI Brain Gets Smarter by Shrinking Through Neural Optimization
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The #AI Brain That Gets Smarter by Shrinking
by Bei Yan @NeuroscienceNew Learn more: https://
bit.ly/4srdo0a #ArtificialIntelligence #MachineLearning #ML #DL -
AI Researchers Challenge Founder Understanding of AI Systems
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This #AI Researcher Says the People Building AI Don’t Understand How It Works. Here’s What Every Founder Needs to Know
by Daniel Robbins @Inc Learn more: https://
bit.ly/4cdqf1b #MachineLearning #ArtificialIntelligence #ML #MI -
Connected AI Systems: Integrated Workflows Across Platforms
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The shift isn’t “more AI tools” It’s connected AI across systems What stood out to me with this approach: → Pulls data from email, CRM, Slack, docs, code
→ Works across multiple LLMs, not locked into one
→ Executes workflows, not just answers questions Example: Ask in -
Connected AI Systems Create Real Competitive Advantage
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The takeaway: AI doesn’t create advantage on its own
Connected AI does If your systems don’t talk to each other, your AI won’t either I break this down in detail in the video, including real use cases. Learn More: -
AI Tools Fragmentation Creates Data Silos in Enterprises
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I keep seeing the same pattern inside large orgs: → Marketing uses one AI tool
→ Sales relies on CRM AI
→ Devs use something completely different → Data is everywhere
→ Context is nowhere So what happens? Decisions require stitching together 5 systems
Insights get lost