Tips for Competing With Big Tech

My biggest fear as an AI startup founder? Getting crushed by giants before proving our value. 6 counterintuitive strategies that helped CrewAI win against better-funded competitors: When I started CrewAI, we faced tech giants with unlimited resources and VC-backed startups with massive teams. I was just a Brazilian developer with an open-source project. Today, we power 50M+ agents monthly and partner with IBM, Cloudera, PwC, and NVIDIA. 1. Turn "small" into speed While others debated in meetings, we shipped product. Our size became our superpower - we could experiment faster than anyone else. 2. Build in public, strategically We shared every win and lesson learned. This wasn't about transparency. It was about creating a movement people wanted to join. Our community became our strongest evangelists. 3. Education drives adoption Two courses with Andrew Ng on Deeplearning.[ai] changed everything. Instead of pushing features, we taught AI agent orchestration. Our customers became champions because they truly understood the value. 4. Focus on tomorrow's problems We looked 3-5 years ahead: Companies will deploy thousands of AI agents. They'll need ways to manage this complexity. While others chase today's features, we're building the control plane for the agentic future. 5. Be a partner, not a vendor Enterprise leaders don't want another tool. They want partners who share their vision for AI transformation. This mindset attracted IBM and PwC as partners. 6. Let competition fuel growth Each new competitor made us stronger: • Their presence validated our market • Their size made us more agile • Their complexity highlighted our simplicity The key insight? Today's AI winners aren't just building tools. They're preparing for what's next. Soon, every enterprise will run hundreds of AI agents handling sales, support, content, and analytics. How will you manage them all? That's why we built CrewAI - tomorrow's AI infrastructure to help enterprises orchestrate agents, ensure compliance, and scale securely. Want to future-proof your AI strategy? DM me or follow @joaomdmoura for insights on the agentic future. ⚡

Here's a playbook for incumbents to win: 1) Recognize that you have a distribution advantage, but an innovation disadvantage because you face the innovator's dilemma. (Strong pull to do predictably profitable things). 2) It's hard to pick exactly how a big tech paradigm shift is going to play out, so have several bets on the table. 3) Resist the temptation to reject all the possible things that are "not proven yet". That's why they're called bets. You don't have to bet the company, but you *do* have to put some of your best people on these projects. (Side benefit: Some of these people will likely leave if you *don't* align them with these kinds of projects). 4) Once it's clear that a particular bet is showing real promise, put the full weight of your global distribution resources behind it. The key idea is to to mitigate your disadvantage of slower innovation by creative, entrepreneurial bets (that are effectively a rounding error for you), and then once you have some visibility into what's working, amplify your outcome using your distribution and brand advantage. That's how you win. Easy to say, hard to do.

AI is killing the software feature battle. Let's be real. We're heading into a world where your competitor can copy your new feature in days, not months. I talk to founders every week who are stuck in the feature race. They build something new, and their competition copies it. Rinse and repeat. It's exhausting and it's about to get worse. So how do you win when features alone won't cut it? Here's where I see smart founders shifting their focus: → Service: Make customers feel like VIPs → Quality: Build stuff that actually works without breaking → Speed: Make it faster to purchase or get to value → Pricing: Charge based on the value you create, not what everyone else charges → Niche Focus: Be the absolute best solution for a specific type of customer → Availability: Show up where your competitors aren't → Brand Story: Stand for something bigger than your feature list I've watched too many founders pour months into feature development only to see their competitive edge vanish overnight. The hard truth? The stuff that truly sets companies apart usually can't be replicated with a few lines of code. Your competitors can copy your features, but they can't copy your culture, your relationships, or how you make customers feel. What are you doing to win on the stuff AI can't touch?

In 1911, a small company in New York started selling cheese and salad dressings. Nothing revolutionary, just simple food products. That company was Kraft Foods. Today, it's a $26 billion behemoth. You might wonder what this has to do with AI startups competing against tech giants. More than you'd think. The story of Kraft isn't about cheese or salad dressing. It's about finding opportunity in the mundane, iterating relentlessly, and delivering what customers actually want - not just what's technologically impressive. Today's AI landscape might seem like a game rigged in favor of the incumbents. They have the data, the talent, the compute power. How can a startup possibly compete? Here's the counterintuitive truth: the very things that make these giants seem unbeatable can be their Achilles' heel. Let's break it down: 1. The Power of Boring Big tech companies are like teenagers at a high school dance - they all want to be where the action is. But real opportunity often lurks in the corners, in the "boring" verticals that giants overlook. I'm reminded of a conversation I had with an AI startup founder. "We're using AI to trawl through google maps, fetch unlisted houses and collate video without someone having phyiscally visit them all," he told me. Not sexy, but solving a real problem that extracts a toll from those who are looking to buy a house. Remember, Kraft didn't start by trying to reinvent food. They just made cheese and salad dressing really well. 2. The Magic of User Experience In 2007, the iPhone wasn't the most technologically advanced phone. But it was magical to use. That magic is what makes people switch. I saw the demo of an AI tool call [suno.ai](http://suno.ai) that auto-generated music albums. The tech was impressive, but what stood out was how it made musicians' eyes light up. It wasn't just smart; it was a joy to use. Your AI doesn't need to pass the new AGI test. It needs to pass the "wow, this makes my life so much easier" test. 3. The Advantage of Speed Big companies move like ocean liners. Startups can be speedboats, zipping around, trying new things. In the world of AI, being first often matters less than being the first to get it right. I'm reminded of something an AI entrepreneur told me: "We're not in the artificial intelligence business. We're in the human empowerment business. AI is just our tool." Your job as an AI startup founder isn't to build a better version of what already exists. It's to build what should exist but doesn't yet. And who knows? Fifty years from now, we might be telling stories about how the AI landscape was transformed not by the tech giants of 2024, but by a small, scrappy startup that dared to make something as mundane as plumbing supply chains work better. After all, in the world of startups, David doesn't beat Goliath by building a bigger sling. He wins by aiming at a target Goliath didn't even know was there.

Big Tech is firing thousands while 10-person AI teams hit $200M ARR. It's not even close. I’ve been seeing something fascinating in the numbers that people are just beginning to talk about: Midjourney: $200M ARR, team of 10 Cursor: $100M ARR, team of 20 Eleven Labs: $100M ARR, team of 50 Mercor: $50M ARR, team of 30 Basically my wife in healthcare would call this a clear diagnosis. Here's what's actually happening in the real world: - Big tech burning billions on "AI transformation" - Hiring thousands of engineers - Getting outperformed by teams that fit in a conference room - Shipping quarterly instead of weekly - Writing "restructuring" posts while tiny teams scale But the wildest part? These small teams are: - Moving 10x faster than enterprises - Staying closer to real customers - Burning 90% less money - Building what users actually want - Learning from every interaction I've seen this play out dozens of times in my career. The winners aren't the ones with the biggest teams. They're the ones that stay lean and close to their customers. Truth is–massive AI teams aren't an advantage, they're a liability built of coordination costs and slow decisions. Real success? That's having a small, focused team that can: - Ship weekly - Talk to customers directly - Make decisions instantly - Learn from every interaction - Let revenue fund growth Stop optimizing for headcount. Start optimizing for speed and customer impact. Your margins (and your survival) will thank you for it.