TL;DR: Microsoft CTO Kevin Scott urges AI startups to prioritize experimentation over waiting for perfect models
AI startups must act now. Microsoft CTO Kevin Scott emphasizes that hesitation in waiting for "better models" stifles innovation. Entrepreneurs should leverage existing AI tools, experiment affordably, focus on practical integrations, and embrace failure as a part of growth.
• Today’s AI technology, like ChatGPT built on older models, already offers massive potential.
• Low-cost platforms like Azure and Hugging Face streamline AI prototyping.
• Iteration and user feedback turn experiments into breakthroughs.
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In the fast-paced world of AI development, time waits for no one. And yet, as Microsoft CTO Kevin Scott pointed out during a 2025 fireside chat, many AI startups are still hesitating, waiting for “better models” before diving into experimentation. His message was clear: stop waiting, and start experimenting. For someone like me, a European serial entrepreneur deeply connected with the startup ecosystem, this advice resonates. Innovation happens not in theory but in execution.
Every industry today faces pressure to implement AI-powered tools, but the “gold rush” mentality often clouds entrepreneurs’ judgment. Scott’s challenge to AI startups, “do the damned experiments”, is the wake-up call many founders need. Let’s explore his advice, its implications for entrepreneurs, and actionable lessons to implement immediately, with a special focus on the European tech startup landscape.
Why Are AI Startups Hesitating?
Despite the rapid advancements in AI, there’s a pervasive reluctance among startups to take risks. Many founders focus on waiting for the “next GPT” or something with revolutionary capabilities. As Kevin Scott noted, the most significant barrier is often not the models themselves but the lack of real-world experimentation. Importantly for European innovators, this hesitation is compounded by challenges like restricted funding, conservative investor expectations, and a culturally ingrained fear of failure that differs from Silicon Valley’s bold risk appetite.
There’s also the allure of novelty. Startups may feel pressure to wait for cutting-edge AI tools to differentiate their products. Yet, as Scott emphasized, today’s technology already offers tremendous potential. ChatGPT, for instance, was built on an older model but gained massive traction through clever execution, not state-of-the-art advancements.
- The fear of failure: European entrepreneurs tend to adopt a conservative stance, which often delays product iteration.
- “Capability overhang”: Current AI systems remain underutilized because startups focus too much on what “could be.”
- Integration hurdles: Developing practical applications from AI models requires solving “unglamorous” engineering challenges that startups may avoid.
What Can Entrepreneurs Learn From Microsoft CTO’s Advice?
Scott’s advice speaks directly to the heart of entrepreneurial action: iterate, fail, and refine. Here’s how startups can heed his advice:
- Leverage existing AI technology: Stop waiting for elusive “perfect” models. Use what exists now, such as open-source tools like Hugging Face models, and focus on building practical solutions.
- Experiment cheaply: Experimentation has become significantly more cost-effective. Cloud-based platforms from AWS, Azure, and Google Cloud allow startups to prototype AI solutions without massive upfront investments.
- Focus on integration: What sets solutions apart is not model sophistication but how well they address user problems. Integration is key, spend resources on creating versatile applications instead of developing inadequately generalized algorithms.
- Reframe failure: Instead of fearing failure, treat it as an essential part of the process. Iterations born out of failed experiments often create groundbreaking solutions.
How to Start “Doing the Damned Experiments” Today
Here’s a brief strategic guide to get your experimentation efforts off the ground without succumbing to analysis paralysis:
- Identify small, testable ideas. Create a list of potential product features or concepts you’d like to experiment with. Focus on ideas where prototype testing can yield quick results.
- Build minimum testable versions. Use platforms like OpenAI to test concepts quickly without needing full-scale development.
- Seek user feedback. Once you develop a prototype, engage early adopters to gain insights into its effectiveness and usability.
- Track and iterate. Make use of tools like Microsoft Fabric for real-time tracking. Identify improvements based on gathered data and repeat the process.
Common Mistakes AI Startups Must Avoid
While experimentation is now cheaper than ever, startups still fall into traps that derail progress. Avoid these mistakes to stay focused:
- Over-reliance on cutting-edge models: Breakthroughs happen through execution, not merely through waiting for the latest tools.
- Ignoring integration challenges: Most AI ideas fail at implementation due to improper systems integration into existing business frameworks.
- Failure to collect feedback: Relying entirely on internal testing without actual customer insights often blinds startups to critical flaws.
- Neglecting user education: If customers can’t understand or use your AI tool, the tech itself is irrelevant.
Final Thoughts: The Time Is Now
Kevin Scott’s advice isn’t just provocative; it’s a rallying cry for action. For European AI startups, this is an opportunity to overcome challenges like conservative tendencies or limited funding by embracing affordable experimentation. As someone who built startup after startup in various tech niches, I can assure you that the magic happens through iteration, adjustments, and grit, not through perfectionism.
So, my fellow founders, the challenge is simple but profound: Roll up your sleeves and try. The technology exists. The resources are available. What’s missing is your willingness to “do the damned experiments.” Let failure guide you into success. Who knows? Your MVP might just turn into a trillion-dollar product.
Interested in tools or platforms to start your experiment journey? Check out resources like GeekWire insights or platforms offering accessible AI infrastructure like Azure AI offerings. The future of AI belongs to doers, not dreamers.
FAQ: Acting on the Advice from Microsoft CTO Kevin Scott to AI Startups
Why does Kevin Scott urge AI startups to experiment now rather than waiting for better models?
Kevin Scott emphasizes that current AI models, like GPT, hold immense untapped capability. Instead of waiting for a more advanced iteration, startups should focus on practical experimentation. The cost of experimentation today is notably low due to accessible resources, such as cloud-computing platforms and open-source tools. Scott underscores that innovation isn’t about having the most advanced models but about finding practical solutions by executing and iterating. Explore startup essentials for successful innovation.
How can startups overcome the fear of failure when experimenting with AI?
Scott encourages reframing failure as learning rather than defeat. In innovation, failed experiments often pave the path for breakthroughs. To get comfortable with this, founders should start small, testing minimum viable products (MVPs) before complete development. Gathering user feedback early helps refine prototypes effectively. This iterative approach, coupled with available cloud tools, reduces the risks and barriers to trying new ideas. Learn to develop resilience through the Female Founder Mindset framework.
What specific AI tools should startups leverage to “do the damned experiments”?
Startups should take advantage of existing tools like Hugging Face models and OpenAI’s APIs to prototype quickly. Platforms such as AWS and Azure offer scalable, pay-as-you-go cloud resources, facilitating cost-effective experimentation. These tools can enable early testing and help startups pivot based on results. For a more comprehensive toolkit, check out the Female Founder Resources for Europe.
How can European AI startups prevail despite cultural challenges like conservative risk approaches?
European startups often face ingrained fears of failure and conservative investor expectations. Overcoming these requires shifting the perspective around failure to see it as an essential part of the growth process. Joining progressive communities and accelerator programs geared toward innovation can also help. For instance, consider applying to a Europe-based accelerator program for female founders.
Why are integration challenges such a significant roadblock for AI development?
One major hurdle for startups isn’t just model sophistication but integrating those models effectively into usable, scalable products. This unglamorous “plumbing” , connecting systems with AI solutions while ensuring functionality and scalability , is critical for success. Skipping this step often results in software that looks promising but fails in real-world applications. Explore lessons on scalable startup systems here.
What role does user feedback play in AI product experimentation?
User feedback is vital to ensuring that an AI product meets real customer needs. Startups should build minimum testable versions of their product to quickly gauge usability, effectiveness, and areas of improvement. Platforms such as Microsoft’s Fabric tools can help startups collect and analyze behavioral data in real-time. Read about how entrepreneurs can validate product ideas through testing and feedback.
How can experimentation help startups to avoid over-reliance on cutting-edge models?
Waiting for the latest tools often leads to missed opportunities. Instead, experimentation allows startups to differentiate by focusing on execution and practical applications rather than model innovation. This approach lets startups find unique value even in mature or seemingly "outdated" tools. Learn how execution trumps novelty in startup success.
What mistakes do AI startups often make during experimentation and execution?
AI startups commonly fail by:
- Overlooking the importance of easy system integrations.
- Ignoring external user feedback.
- Lacking proper user education for complex AI tools.
These are critical missteps as they alienate customers and stifle growth. Startups must address these points proactively; discover actionable fixes for startup challenges here.
How should entrepreneurs prioritize AI applications to maximize impact?
To ensure lasting impact, startups should focus on AI solutions that address urgent, real-world user problems instead of chasing “moonshot ideas.” Integration and scalability are more impactful than showy breakthroughs. Learn how AI Startups can target the right markets in European Female Founder Ecosystems.
What is the long-term value of Kevin Scott’s “do the damned experiments” mantra for Europe-based AI founders?
For European founders, this mindset provides a clear path to innovation by emphasizing actions over theory. Experimentation helps bypass limitations like funding constraints or venture conservatism. For success, founders should embrace failures as learning opportunities and use resources like accelerators and open-source tools to keep pushing boundaries. Explore how founders in Europe can grow fearlessly with focused action.
About the Author
Violetta Bonenkamp, also known as MeanCEO, is an experienced startup founder with an impressive educational background including an MBA and four other higher education degrees. She has over 20 years of work experience across multiple countries, including 5 years as a solopreneur and serial entrepreneur. Throughout her startup experience she has applied for multiple startup grants at the EU level, in the Netherlands and Malta, and her startups received quite a few of those. She’s been living, studying and working in many countries around the globe and her extensive multicultural experience has influenced her immensely.
Violetta is a true multiple specialist who has built expertise in Linguistics, Education, Business Management, Blockchain, Entrepreneurship, Intellectual Property, Game Design, AI, SEO, Digital Marketing, cyber security and zero code automations. Her extensive educational journey includes a Master of Arts in Linguistics and Education, an Advanced Master in Linguistics from Belgium (2006-2007), an MBA from Blekinge Institute of Technology in Sweden (2006-2008), and an Erasmus Mundus joint program European Master of Higher Education from universities in Norway, Finland, and Portugal (2009).
She is the founder of Fe/male Switch, a startup game that encourages women to enter STEM fields, and also leads CADChain, and multiple other projects like the Directory of 1,000 Startup Cities with a proprietary MeanCEO Index that ranks cities for female entrepreneurs. Violetta created the “gamepreneurship” methodology, which forms the scientific basis of her startup game. She also builds a lot of SEO tools for startups. Her achievements include being named one of the top 100 women in Europe by EU Startups in 2022 and being nominated for Impact Person of the year at the Dutch Blockchain Week. She is an author with Sifted and a speaker at different Universities. Recently she published a book on Startup Idea Validation the right way: from zero to first customers and beyond, launched a Directory of 1,500+ websites for startups to list themselves in order to gain traction and build backlinks and is building MELA AI to help local restaurants in Malta get more visibility online.
For the past several years Violetta has been living between the Netherlands and Malta, while also regularly traveling to different destinations around the globe, usually due to her entrepreneurial activities. This has led her to start writing about different locations and amenities from the point of view of an entrepreneur. Here’s her recent article about the best hotels in Italy to work from.