Hey,
The Deepseek news has been buzzing, and I share my take and some advice for founders on disrupting a space.
Also;
📸 - Social Snapshot- Sam Altman's comments on Deepseek
📊 - Getting from seed to Series A
🎙️ - Breaking into the UK utilities ecosystem with Penelope Hope
🆓 - Negotiate your term sheets like a pro
Welcome to issue 107.
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How Much Could You Sell Your Company For?
If a private equity firm or strategic acquirer made an offer to you today, would you take it? Would you know if it's a fair deal? Are you in the position to close a deal?
Getting acquired could transform your life.
Founders don't realize that it usually takes 12-24 months to prepare a company for a successful exit, the sooner you have a plan in place, the greater the potential outcome.
If you want to get acquired, we can help. Book a free discovery call with our team of experts to explore your options and discuss getting a plan in place that could change your life.
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Social Snapshot
💭 Sam Altman's take on Deepseek on X.
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How Rebel Energy Scaled £1.5M to £100M with Penelope Hope - EP 71
Last week's episode featured Penelope Hope, founder of Rebel Energy, a utilities company. Tune in to hear her story on how she built a renewable energy company from scratch with just £1.5 million raised, scaling it to £100 million in revenue in record time. Plus, how crowdfunding and leveraging customer retention in the space worked for her.
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Data Corner
Will You Make It from Seed to Series A?
Short answer: maybe. But when you raised your seed round has impact on the odds.
Carta pulled data from 11,114 US startups that raised a priced seed round (so no SAFEs) between 2017 and 2023. Here’s what they found:
- Roughly 45-50% of seed-stage startups will eventually raise a Series A.
- 30-35% will make it to Series A within two years of their seed round.
- Startups that raised in 2022? They're struggling. Only 17% have raised a Series A after two years.
Why the Slowdown?
Two theories:
- They’re trying to raise and failing. Given the tough market, this is likely the dominant factor.
- They’re choosing profitability over more funding. Some startups raised enough to extend their runway and avoid the fundraising mess altogether.
Bottom line: If you raised in ‘22, you’re fighting uphill. If you’re raising now, expect a grind. The bar for Series A is just higher than it used to be.
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Raising Capital for your startup?
Thunder's mission is to guide founders toward the right path to reach their North Star, be it through securing equity or debt financing or navigating the path to a successful exit.
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DeepSeek vs. The AI Establishment
Last week, I touched on this but I thought I'd take a deep dive into the Deepseek news and share some insight. I read this article and it got me thinking.
The AI gold rush has been dominated by the usual suspects: OpenAI, Google, and Nvidia. But the emergence of DeepSeek, a relatively unknown Chinese AI startup, has made big news, proving that capital efficiency might finally be catching up to big spending.
Why Did Nvidia Just Bleed $560 Billion?
DeepSeek claims it trained its R1 model for under $6 million, almost nothing compared to the billions spent by U.S. giants like OpenAI. Even more alarming? DeepSeek R1 supposedly rivals OpenAI's model o1, suggesting that cutting-edge AI might no longer require cutting-edge budgets.
That announcement was enough to spook investors, wiping out $560 billion from Nvidia’s market cap. If AI companies can train and deploy high-performing models without relying on Nvidia’s expensive GPUs, the entire AI hardware supply chain could be at risk.
Of course, Nvidia isn’t rolling over. The company quickly moved to showcase how DeepSeek R1 integrates with its own architecture via Nvidia NIM microservices, positioning itself as DeepSeek’s enabler, rather than its victim. But the damage was done: the stock tanked, and everyone started asking uncomfortable questions about AI’s cost structure.
The $6M AI Model: Is it legit?
While $6 million to train an OpenAI-tier model sounds incredible, there are questions DeepSeek still hasn’t answered.
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Data sourcing and licensing – Where did the training data come from? OpenAI has openly accused China of reverse-engineering U.S. AI models. If DeepSeek took a shortcut by scraping OpenAI's work, that’s a legal minefield waiting to explode.
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Compute efficiency – Did they truly optimize training, or are they leveraging pre-trained architectures built elsewhere? Nvidia may not have lost its grip just yet.
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Cybersecurity risks – DeepSeek has already faced DDoS attacks and scrutiny over data security. Chinese AI companies often struggle with global trust issues, especially around government influence.
Even with these concerns, DeepSeek’s emergence is a wake-up call for every founder playing in the AI space. The lesson? The real innovation isn’t just in model performance—it’s in operational efficiency. OpenAI and Google have built AI with brute force; DeepSeek is proving that maybe, just maybe, a more nimble approach is possible.
What Founders Should Learn: The New Rules of AI Disruption
If you’re a founder in AI, fintech, or any other capital-intensive industry, DeepSeek just handed you a roadmap for punching above your weight. Here’s how you should be thinking:
1. Capital Efficiency is King
Forget the myth that bigger budgets always win. If DeepSeek’s claims hold up, they just cut the cost of AI training by miles. What’s stopping you from doing the same in your industry? Look for ways to challenge current cost structures, because that’s where real change happens.
2. Move Faster Than the Incumbents
DeepSeek didn’t wait for permission. It built, launched, and caught the AI establishment off guard. Meanwhile, OpenAI and Google are stuck in legal battles and bureaucratic red tape. The speed at which you execute will determine whether you lead or get left behind.
3. Control your dependencies
One reason Nvidia got torched is that it built its empire on AI companies being 100% reliant on its hardware. But DeepSeek’s emergence suggests that AI builders are finding ways around that dependency. If your business leans too heavily on one supplier, one partner, or one distribution channel—fix that now. Because when a cheaper, more efficient alternative emerges, you’ll be the one taking a $560B hit.
4. DeepSeek isn't an outlier
Nvidia’s stock drop wasn’t an overreaction; it was a preview of what’s to come. AI is moving fast, and the next shift could come from a completely unexpected player. If DeepSeek can train a competitive model for a fraction of OpenAI’s budget, what’s stopping others from doing the same?
For founders, this isn’t just another AI headline. It’s a blueprint. Efficiency beats excess. Gotta move fast. The news already has Sam Altman innovating (check out the social snapshot above).
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- Written by Jason Kirby - https://www.linkedin.com/in/jasonrkirby
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