Inside The Post-ChatGPT Playbook: A Founder’s Lessons On Building AI-Native Startups
Share:
AI hype is reaching a tipping point. Every brand is racing to stay ahead of the adoption curve, but not every approach yields the same results. In the first half of 2025, billions of dollars flowed into the U.S. AI startup ecosystem. But the game has changed. We’re entering a “post-ChatGPT era,” where generative AI isn’t a differentiator, but a necessity.
If a founder wants their AI startup to stand out and lead the next wave of innovation, it needs to be more than AI-enabled. That’s why today’s founders need to embrace an AI-native strategy.
Why does being AI-native matter now?
As a repeat founder, I’ve learned the value of this through relaunching a legacy brand as AI-first. Just bolting on AI isn’t enough to stay competitive. Founders need to cultivate reinvention and operate like an AI-driven company from day one.
If you’re still tacking AI onto your product as an afterthought, you’ve already fallen behind. Being AI-native matters now more than ever as it’s the foundation of market competition.
This next generation of startups will shape their architecture, go-to-market strategy, and customer value proposition as AI-first. This requires an important mindset shift to begin solving problems created by AI.
Existing startups may rethink their approach. Ask yourself, “If we were starting this company today, how would AI define our business?”
AI-native startups are positioned to thrive
Adopting an AI-at-the-core mindset comes with clear competitive advantages.
- Growth often comes with risks in the startup space, especially when it veers from established timelines or roadmaps. An AI-native approach allows teams to scale at startup speeds without burning out. They’re given the ability to automate, experiment and deploy faster with fewer roadblocks.
- Personalization drives a huge portion of customer demand in terms of what they expect from their digital journeys. AI and automation play a clear role here, providing startups with the ability to tailor products, services and experiences in real-time.
- Staying agile and adaptable in a turbulent tech economy is crucial. AI-native companies pivot with market changes and evolving customer needs with less friction, all built upon an adaptable, reliable infrastructure.
Trust as a cornerstone of AI strategy
AI clearly offers companies practical advantages and solutions to common startup pain points. But embedding AI is more than rebranding and deploying models into workflows. It’s crucial to cement responsible practices as well.
The promise of AI is powerful, but founders can’t afford to ignore risks around data quality or misinformation. These concerns remain very real for customers, employees and potential investors.
Founders need to be champions of responsibility and accountability by designing governance and guardrails into their startups’ core.
The result? AI-native companies that move fast and build lasting trust.
Lessons from a repeat founder
The founder’s playbook has changed. Just a few years ago, you could build powerful human-centered products and add automation later. Today, founders must operate differently.
- Tackle the real challenge: Don’t build another LLM wrapper. Real, defensible businesses solve the new problems created by AI, such as governance, security and verification.
- Assume AI adoption: Build for customers who are already using AI and grappling with the complex consequences. Your product should make their AI strategy safer and more effective.
- Turn speed into your superpower: The window to build and adapt is shorter than ever. Your ability to learn and pivot faster than your competition is your greatest competitive advantage. Long-term, static roadmaps are a liability.
- Prioritize trust: In a world of infinite AI-generated content, trust is the most valuable asset. Focus on tools that ensure accuracy, reliability and brand integrity.
My experience has taught me to listen to the market, especially when it tells you to change.
The winners in this next chapter of startups won’t just use AI to make things faster or cheaper, they’ll leverage it to make their businesses safer, more reliable and adaptive to a changing world.
Matt Blumberg is the CEO of Markup AI and has more than 30 years of leadership in scaling global disruptive technology businesses. Before launching Markup AI, he successfully launched and led brands and companies including Acrolinx, MovieFone division of 777-FILM (acquired by AOL), Return Path (No. 2 on Fortune Magazine’s “Best Companies to Work for” list and later acquired by PSG/Validity), the nonprofit Path Forward, and Bolster, a disruptive platform for executive search in the tech industry.
Illustration: Dom Guzman
In This News
Coins
$ 0.187
+0.28%
$ 0.00...361
$ 0.569
-3.25%
$ 0.0869
$ 0.000269
Share:
In This News
Coins
$ 0.187
+0.28%$ 0.00...361
$ 0.569
-3.25%$ 0.0869
$ 0.000269
Share:
Read More
Germany’s AI Image Generator Black Forest Labs Raises $300M At $3.25B Valuation As European AI Fundings Scale Up
Sector Snapshot: Defense Tech Funding Hits Record High
Inside The Post-ChatGPT Playbook: A Founder’s Lessons On Building AI-Native Startups
Share:
AI hype is reaching a tipping point. Every brand is racing to stay ahead of the adoption curve, but not every approach yields the same results. In the first half of 2025, billions of dollars flowed into the U.S. AI startup ecosystem. But the game has changed. We’re entering a “post-ChatGPT era,” where generative AI isn’t a differentiator, but a necessity.
If a founder wants their AI startup to stand out and lead the next wave of innovation, it needs to be more than AI-enabled. That’s why today’s founders need to embrace an AI-native strategy.
Why does being AI-native matter now?
As a repeat founder, I’ve learned the value of this through relaunching a legacy brand as AI-first. Just bolting on AI isn’t enough to stay competitive. Founders need to cultivate reinvention and operate like an AI-driven company from day one.
If you’re still tacking AI onto your product as an afterthought, you’ve already fallen behind. Being AI-native matters now more than ever as it’s the foundation of market competition.
This next generation of startups will shape their architecture, go-to-market strategy, and customer value proposition as AI-first. This requires an important mindset shift to begin solving problems created by AI.
Existing startups may rethink their approach. Ask yourself, “If we were starting this company today, how would AI define our business?”
AI-native startups are positioned to thrive
Adopting an AI-at-the-core mindset comes with clear competitive advantages.
- Growth often comes with risks in the startup space, especially when it veers from established timelines or roadmaps. An AI-native approach allows teams to scale at startup speeds without burning out. They’re given the ability to automate, experiment and deploy faster with fewer roadblocks.
- Personalization drives a huge portion of customer demand in terms of what they expect from their digital journeys. AI and automation play a clear role here, providing startups with the ability to tailor products, services and experiences in real-time.
- Staying agile and adaptable in a turbulent tech economy is crucial. AI-native companies pivot with market changes and evolving customer needs with less friction, all built upon an adaptable, reliable infrastructure.
Trust as a cornerstone of AI strategy
AI clearly offers companies practical advantages and solutions to common startup pain points. But embedding AI is more than rebranding and deploying models into workflows. It’s crucial to cement responsible practices as well.
The promise of AI is powerful, but founders can’t afford to ignore risks around data quality or misinformation. These concerns remain very real for customers, employees and potential investors.
Founders need to be champions of responsibility and accountability by designing governance and guardrails into their startups’ core.
The result? AI-native companies that move fast and build lasting trust.
Lessons from a repeat founder
The founder’s playbook has changed. Just a few years ago, you could build powerful human-centered products and add automation later. Today, founders must operate differently.
- Tackle the real challenge: Don’t build another LLM wrapper. Real, defensible businesses solve the new problems created by AI, such as governance, security and verification.
- Assume AI adoption: Build for customers who are already using AI and grappling with the complex consequences. Your product should make their AI strategy safer and more effective.
- Turn speed into your superpower: The window to build and adapt is shorter than ever. Your ability to learn and pivot faster than your competition is your greatest competitive advantage. Long-term, static roadmaps are a liability.
- Prioritize trust: In a world of infinite AI-generated content, trust is the most valuable asset. Focus on tools that ensure accuracy, reliability and brand integrity.
My experience has taught me to listen to the market, especially when it tells you to change.
The winners in this next chapter of startups won’t just use AI to make things faster or cheaper, they’ll leverage it to make their businesses safer, more reliable and adaptive to a changing world.
Matt Blumberg is the CEO of Markup AI and has more than 30 years of leadership in scaling global disruptive technology businesses. Before launching Markup AI, he successfully launched and led brands and companies including Acrolinx, MovieFone division of 777-FILM (acquired by AOL), Return Path (No. 2 on Fortune Magazine’s “Best Companies to Work for” list and later acquired by PSG/Validity), the nonprofit Path Forward, and Bolster, a disruptive platform for executive search in the tech industry.
Illustration: Dom Guzman
In This News
Coins
$ 0.187
+0.28%$ 0.00...361
$ 0.569
-3.25%$ 0.0869
$ 0.000269
Share:
In This News
Coins
$ 0.187
+0.28%$ 0.00...361
$ 0.569
-3.25%$ 0.0869
$ 0.000269
Share:
Read More
Germany’s AI Image Generator Black Forest Labs Raises $300M At $3.25B Valuation As European AI Fundings Scale Up