There are companies we don’t even know, haven’t been started yet, their names aren’t known, might be extraordinarily big winners in the AI thing. AI is a much bigger landscape, opportunity landscape, than all the previous technologies we have known combined. Combined.
Sundar Pichai, CEO of Alphabet at the All In podcast
Startups have always been hard.
Turning an idea into a product, and a product into a business, is a marathon full of sprints—and most don’t make it to the finish line. Founders juggle 100 decisions a day, from building a team and talking to users, to raising money and staying ahead of competition. The emotional rollercoaster is real.
The startup landscape, however, has undergone a profound transformation.
With the rapid rise of generative AI and foundational models, startups are able to do more with less: from coding to marketing. In some ways, it’s easier than ever to launch something new. In other ways, it’s never been more complex or competitive. And some things never change…
Here’s a look at what’s changed, what’s stayed the same, and how founders can navigate the AI-powered startup landscape today.
? What Hasn’t Changed
“The most important thing for an entrepreneur is to have a good team. The second most important thing is to get to market, prove product-market fit, and then raise money.”
Ron Conway, SV Angel founder
Despite technological revolutions and shifting market dynamics, certain startup fundamentals remain stubbornly constant.
Let’s start with some things that didn’t change with AI
- The need for focus remains paramount. Chasing too many opportunities simultaneously is still the silent killer of early-stage startups. The temptation to pursue multiple directions has only intensified with AI opening new possibilities, but successful founders understand that resources—time, money, and attention—are always finite. As Airbnb co-founder Brian Chesky often reminds entrepreneurs: “It’s hard to do a lot of things really well.”
- Human connection continues to drive success. While AI can generate content and code, it can’t replace the authentic relationships you build with customers, team members, and investors. The most successful founders spend significant time talking directly to users, understanding their pain points, and translating those insights into solutions. These human connections become your most valuable asset when navigating uncertainty.
- Execution ultimately trumps ideas. The startup graveyard is filled with brilliant concepts that were poorly implemented. Whether you’re building an AI application or a traditional SaaS product, your ability to ship, measure, learn, and iterate remains the fundamental rhythm of startup success. As Box founder Aaron Levie puts it: “Ideas are cheap. Execution is everything.”
? What’s Easier Now
“It’s never been easier to build a product. But it’s still hard to build a business.”
Sam Altman, co-founder and CEO of OpenAI
The rise of generative AI and related technologies has dramatically lowered certain barriers to entry, creating unprecedented opportunities for resourceful founders:
- Prototyping at lightning speed. Today’s founders can transform ideas into functional products in days rather than months. It starts with “vibe coding”, but doesn’t end there – every week it seems like founders of AI-first startups are getting a new set of super powers. With APIs for everything from machine learning to payments, entrepreneurs can assemble sophisticated MVPs without reinventing wheels. This acceleration means more iterations, faster learning, and quicker paths to product-market fit.
- The rise of micro-teams. We’re witnessing the emergence of formidable “small-by-design” startups. Companies that once required dozens of employees can now operate effectively with skeleton crews. Consider Notion’s early days—they built a product challenging Microsoft and Google with just a handful of people. Today’s solo founders can leverage AI for code generation, content creation, design work, and customer support, allowing them to validate business models before scaling their teams.
- Democratised expertise. AI has flattened the knowledge curve across domains. Non-technical founders can now prototype apps, technical founders can craft marketing copy, and both can quickly develop baseline knowledge in unfamiliar territories. This doesn’t eliminate the need for expertise—it just lowers the threshold for getting started. When Canva launched, design software was complex and intimidating; they made it accessible to everyone. Today’s AI tools are doing the same for coding, writing, and countless other skills.
- Global reach from day one. Distribution channels have matured alongside AI tools. Founders can now launch globally using established platforms, reach niche communities through targeted strategies, and leverage digital tools to establish credibility quickly. When Figma disrupted Adobe, they used a browser-based approach and community-driven growth to rapidly gain market share—strategies that are now even more powerful when combined with AI-enhanced personalization and outreach.
? What’s Harder Now
“Starting a company is like chewing glass and staring into the abyss.” –
Elon Musk, Tesla & SpaceX founder
While AI has democratised certain aspects of company building, it has simultaneously introduced or intensified challenges that today’s founders must navigate:
- Breaking through the noise has never been more difficult. The “AI gold rush” has created unprecedented market saturation. When Buffer launched as a social media scheduling tool in 2010, the category was relatively uncrowded. Today, announce an “AI for marketing” startup and you’ll compete with dozens of similar-sounding ventures. Founders must now develop razor-sharp positioning and genuinely differentiated solutions to capture attention.
As a16z’s Andrew Chen noted: “In a world where everyone can build quickly, your defensibility comes from unique insights, proprietary data, or network effects that others can’t easily replicate.“
- Technical sophistication is the new baseline. The days when a simple integration could impress users are fading fast. Founders must now demonstrate meaningful technical value beyond basic AI implementations. Companies like Adept AI and Runway didn’t just apply existing models—they pushed boundaries to create genuinely novel capabilities. For non-technical founders, this means forming deeper technical partnerships or making strategic hires earlier than they might have previously planned.
- Navigating an evolving ethical landscape. AI introduces complex challenges around bias, transparency, privacy, and copyright that can create significant business risks if mishandled. When Harvey AI launched its legal assistant, they had to carefully address concerns about confidentiality and accuracy in a highly regulated industry. Founders must now build with responsible AI principles from day one—not as an afterthought but as core business strategy. This requires understanding both technical and ethical dimensions of AI development.
- Managing platform dependencies creates vulnerability. Many startups rely heavily on APIs from OpenAI, Google, Anthropic, or other providers—creating existential risk if those relationships change. When OpenAI adjusted its pricing model in 2023, numerous startups had to scramble to adapt their business models. Smart founders are implementing multi-provider strategies, building abstraction layers, or developing proprietary components to reduce reliance on any single platform.
- Keeping pace with the acceleration of innovation. The rapid evolution of AI capabilities means that competitive advantages can evaporate overnight. Products that seemed cutting-edge six months ago may now feel outdated. Diffusion models revolutionised image generation in just two years—faster than many startups could pivot. This compression of innovation cycles forces founders to balance shipping current products while continuously scanning the horizon for disruptive advances.
? The Series A Crunch
And then there’s funding. According to the latest data by Carta (based on US data mainly), only 15.5% of companies that raised a seed round in Q1 2023 have raised series A in 2025. As I’ve previously shared on VC Cafe, the time period between rounds has gotten longer and therefore, the bar for raising seed and series A has gone up.
While pre-seed and seed rounds remain relatively active—especially for AI-native ideas—the bar for Series A has gone way up. Investors are looking for more traction, clearer metrics, and durable growth.
This “Series A crunch” means founders must either:
- Get to product-market fit faster, or
- Build capital-efficient businesses that can survive longer on seed capital
It’s no longer enough to raise on hype or a great team. Startups need real signals of demand, usage, and stickiness—ideally all three.
“In today’s market, seed is the new Series A. And Series A is the new Series B.” — Anonymous VC
? So, Should You Build a Startup Right Now?
Absolutely—if you have:
- A clear problem worth solving
- An insight others are missing
- The stamina to weather ups and downs
AI isn’t a cheat code. It’s a tool. The best founders will use it to move faster, validate ideas quicker, and build smarter. But the fundamentals—deep user understanding, relentless focus, and great execution—still win.
Shameless plug – Remagine Ventures
The majority of the startups that we back at Remagine Ventures are AI-first startups in stealth mode (both B2C and B2B). AI has democratised certain aspects of early company-building, allowing founders to build more with less initial capital by leveraging no-code/low-code tools and AI assistants. However, the bar for differentiation has risen significantly, as AI enables more people to quickly launch similar solutions.
To increase the chances of making your first meetings with investors go exceedingly well, you need to put yourself in your shoes and show that you’ve been able to de-risk some of the most important aspects VCs look for when evaluating opportunities: a strong team, a huge market and a good answer to the question ‘why now/ why you’.
I'm a former general partner at google ventures, head of Google for Entrepreneurs in Europe and founding head of Campus London, Google's first physical hub for startups.
I'm also the founder of Techbikers, a non-profit bringing together the startup ecosystem on cycling challenges in support of Room to Read. Since inception in 2012 we've built 11 schools and 50 libraries in the developing world.
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