The AI chip race heats up
gm legends. It’s Sunday funday.
In this edition:
- Nvidia moves into uncharted territory
- Why your engineers need better metrics
- When to consider a side hustle in courses
- And, as always, the most popular products that went live this week
Grab the carafe. We’ll bring the memes.
P.S. Launching soon? We’d love to hear about it → editorial@producthunt.co 🫶
Guess the Launch

Before we start, it’s time for everyone’s favorite game: Guess that Product Hunt Launch!
This launch finished #1 for August 2020. It’s an email newsletter that sends market research reports about emerging ideas to founders. It was created by Dru Riley, who this month launched HeadsUp, an “AI competitor monitoring agent.”
Can you name the product?
How Much AI Does $4T Buy?

Nvidia just hit a record in the second quarter, hitting $41.1 billion in sales. That’s 56% more than the same quarter last year. It remains the only public company with a market cap above $4 trillion.
Nvidia’s business is making and selling chips to companies, who need a lot of them for AI services. With major tech companies rolling out new AI models every other day, Nvidia is rolling in dough.
But get this: While Nvidia’s main competitors are other semiconductor firms like AMD and Intel, it’s also beginning to compete against its own customers.
OpenAI? Uses Nvidia’s GPUs and AMD’s chips. But it’s also building its own.
Google? It originally kept its homemade AI chips for internal use, but has started selling them to Apple, Safe Superintelligence, and Anthropic. The latter is lined up to deploy Amazon’s processors, whenever those come out.
And since Nvidia can’t ship AI chips to China, erstwhile Chinese consumers like Alibaba are also making their own.
All of that could cut into demand for Nvidia chips, with increased supply ultimately making AI compute services cheaper for developers like you, dear reader.
Maybe.
Remember, Nvidia does one thing, all day, every day: make chips.
Amazon and Apple often barge into new territories. Think: streaming. But people aren’t exactly canceling their Netflix accounts. Expect Nvidia to compete on quality, and developers to have some cheaper options. Everybody wins. This isn’t Squid Game, after all.
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What’s Your Number? Why Your Engineers Need Better Metrics

Adam Cohen is the cofounder of @Weave, an engineering analytics company that helps teams go AI-first. Before Weave, he was head of operations and sales at education software firm Top Hat and VP of operations and revenueat @Causal, which was acquired by Lucanet in 2024.
In sales, you always know exactly where you stand. In engineering, you don’t.
The sales leaderboard shows the top performers, the basement-dwellers, and everyone in between. At first, this is terrifying, but it quickly becomes inspiring. If you know who’s outselling you, you can reverse-engineer a way to improve. At Top Hat, I built a dashboard that showed every sales rep their conversion rates. Armed with this data, they practically started coaching themselves.
Now, tools like Gong have made it easy for salespeople anywhere to identify ways to improve. Gong pulls data from multiple sources, measures performance through metrics known to move the needle, then provides teams with actionable data.
But as I shifted to running customer success and marketing, there was nothing. No leaderboard, no analytics, no tools like Gong. Without clear and meaningful metrics, career and company development became guesswork.
I was talking about this with (my now-cofounder) Andrew, a founding engineer at Causal while I was VP of operations and revenue there. I mentioned I was trying to cobble together something like Gong for customer success using ChatGPT and other tools. That's when we both had the thought: "Wait, why don't engineers have anything like this?"
They’re building the product in the dark, with few good tools for measuring impact, even with seemingly basic things like ship rate. They don’t know what’s attributable to difficult code fixes, what comes down to individual speed, and where team communication is costing them time.
The vision became clear: give engineers the same self-improvement capabilities that transformed sales teams.
Leaderboard highlights



Teachers' Pets

Priyanka asks:Do founders make good teachers?
Some commentators argue that founders make good teachers because they’ve got firsthand experience and can take students beyond theory. Others say the key to going from founder-to-instructor is staying humble or providing proof of success. If you can't show people what they'll gain from listening to you, don't quit your day job.

