🚦 Let's Build an AI Startup

Hi there 👋 
Thanks for reading Scalable, where there is practical know-how to up your game every week for free.

To all the fellow builders out there, today is a special one.
Happy World Product Day 🎉 

As a gift to all of our readers today, there is a free course in this week’s edition.

This past week in particular has been a massive week for AI. While there is a lot buzz around it, there is a lot of “fluff” around it as well.

For startup founders and product people, I lined up all of the useful stuff that you should know about, along with some top-notch picks and resources.

Here’s a snapshot of what’s on the menu today:

☝️ Scaled this past week: Wayve.AI

London-based self-driving car startup Wayve has raised a $1.05 billion round.

wayve.ai is the scale of the week!

This signals continued investor fervor for all things artificial intelligence, marking one of the largest funding deals on record for a British startup.

Wayve uses a technology called Embodied AI to empower vehicles to understand and navigate their surroundings independently, making real-time decisions without needing detailed pre-existing maps.

🧠 Deep-Dive: How not to build an AI startup

Make better decisions, and save some time in the process. That’s the gist of it.

It’s been a blessing and a curse to be around this AI boom as a product person - it’s almost like being an early adopter to Facebook at 2008. You know what’s ahead, and you know it’s big, but it’s still the early days.

Imagine someone, 20-25 years ago, telling you that they are gonna build an “internet startup”. That term today is laughable at best because as the human race, we effectively do not have any non-internet startups.

I do believe a similar paradigm shift will take place at a faster rate. In 10-15 years when someone says they’re building an “AI startup”, that term will be laughable at best because we will not have any non-AI startups.

The way it’s being executed today is often times like this:

Imagine baking a cupcake and adding sprinkles to the top.

The sprinkles do make the cupcake look nicer. They decorate the product. But that’s not the reason why anyone ever buys a cupcake. Not to mention they taste like nothing. This decorative, non-value added finishing touch might make the cupcake look more attractive, but practically exists for no reason.

These days, a lot of “AI startups” are being built like this. They barely build a product that solves a real problem, and somewhere along the line in their user journeys, they add some GPT-based generative text functionality.

The common issue is, there is usually a half-baked cupcake (an actual product that barely solves an actual problem), and the sprinkles are being over-marketed with the expectation of rendering the product a lot more attractive in the eyes of users and investors.

That rarely works.

The way to build an AI-first (or the term AI-native is being used these days as well) is “by solving a real problem in a cool way”. If the AI capabilities of your product do not solve a problem in a more efficient, faster, and cooler way - then it’s all just a bunch of sprinkles.

How to do it then? Here below is an iterative framework on how you can build a continuous feedback cycle incorporating AI capabilities for your product alongside customers.

To summarize this in a few bullet-points:

• Pick a good problem to solve in a cool way

• Prioritize areas with the highest potential for AI impact

• Start with a pilot project to test your approach

• Collect feedback and refine your strategy

• Repeat this cycle until you figure out what works and what doesn’t

Remember, nobody buys a cupcake for the sprinkles.

A message from friends at Rundown AI

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🗺️ Method: AI for Product Management Course

To all the product people out there: if you’re not incorporating AI to manage some portion of your day-to-day routine, you might be missing out.

This course below is about 2.5 hours long, and it does a pretty solid job of covering core AI use cases, best practices, and some how-tos in product.

As modern PMs are focused on driving business outcomes, AI can help them achieve those outcomes faster and more effectively - how to leverage AI throughout the development life cycle, best practices for building AI-powered features, and why product managers should view AI as a strategic tool, not a threat.

👉 Make sure to use the code “BAHRAIN”, then the course is completely free.

💡 Spotlight: Automate your meeting notes

Fireflies.ai is a conversational AI platform that specializes in automating meeting note-taking.

I know, I know, it sometimes feels intrusive by creating a sense of over-surveillance but hear me out (they are not a sponsor or anything).

I like Fireflies in particular since the free version’s coverage pretty functional and allows you to use have accurate and search through your meeting records.

Saves you time, eliminates the need of manual note-taking, collates points and sends follow-up emails. Take a look.

⚾️ Catch: OpenAI’s ChatGPT 4o

Unless living under a rock is your thing, you should know about this already.

ChatGPT 4o is OpenAI’s new flagship model that’s as smart as GPT-4 Turbo (and much more efficient).

It’s that neighbor’s kid who’s always doing better than you. Here are some of the benefits:

• 50% lower pricing. GPT-4o is 50% cheaper than GPT-4 Turbo, across both input tokens ($5 per 1 million tokens) and output tokens ($15 per 1 million tokens).

• 2x faster latency. GPT-4o is 2x faster than GPT-4 Turbo.

• 5x higher rate limits. Over the coming weeks, GPT-4o will ramp to 5x those of GPT-4 Turbo—up to 10 million tokens per minute for developers with high usage.3

Here is one of the introductory vides by OpenAI.

The line between awareness and consciousness has never been blurrier.

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