Justin's AI Newsletter

The most interesting content, news, and insights in AI each week.

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Hey friends 👋,

Happy Sunday! I’m back in NYC and sitting in our new office at Cassidy​

It feels good to finally have an office space in NYC. We've been working remotely for a while, but as we continue to grow, in-person collaboration will become a necessity.

Don’t get me wrong, working from home makes sense for some people, but if you’re an early-stage startup, close collaboration is essential for success.

Now, let’s dive into AI…

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AI JOBS

🛠️ The “AI Product Manager” — The Hot Job in AI.

I released a viral video this week talking about the new role of the “AI Product Manager”. I think it’ll be one of the most valuable job in AI…

Right now, every tech company is trying to figure out how to implement AI into their products to enhance the overall customer experience. But, in order to do this, they need people who can uncover customer problems and shape out the solutions to solve those problems using AI.

That’s where the AI Product Manager comes in. A Product Manager identifies customer problems and needs, and mobilizes a team around shaping products and features which will effectively alleviate these pain points and create value.

Now, the AI Product Manager is critical because the biggest pitfall for companies will be building AI products without a purpose.

It’s important to remember that AI implementation is only impactful when it actually solves existing customers’ problems. Building AI for AI’s sake is pointless– and often detracts from the customer experience. (i.e. Snapchat’s AI is notorious here)

Here’s how to break into Product Management with no prior experience…

This is by no means easy. Product Management is a niche field that requires specialized skillsets, even without AI.

But, the best way to break in: build a product yourself. This effectively shows a company that you are able to turn an idea into a product.

Here’s how a super condensed guide to getting something out there:

1. Identify a real problem: Look for issues, even just in your own life, that could be addressed by software. Pinpointing relatable everyday problems will ensure that your product serves a real need.
2. Shape the solution and design: Envision a possible solution to tackle the problem you’ve identified and start designing how it could work. Consider how to best solve the problem using software, ensuring your solution is practical and user-friendly.
3. Develop the software: This is the most challenging part. If you have coding skills, put them to use; if not, explore no-code tools like Bubble to build your software product. Utilize every resource at your disposal– the internet is your friend here.
4. Bring it to market: Your next step is to get real users for your product. Share your project on social media platforms like Twitter or relevant Reddit communities. Engage with potential users and gather feedback for improvement. To land a PM job, you’ll need to show that you can take a product from just an idea to something that satisfies customers.
5. To be an AI Product Manager, use AI: If you want to be an AI Product Manager, incorporate tools like the ChatGPT API. Show that you can effectively build a product that incorporates AI.

The best way to break into Product Management is to actually build a product. While not easy, it’s definitely doable– and certainly worth it as demand in tech skyrockets for AI Product Managers.

Here are some of my other favorite Product Manager resources:

🔗 Ultimate Guide to Product Management​

🔗 Crossing the Chasm, Marketing and Selling Disruptive Products to Mainstream Customers​

🔗 Kevin Yien’s PRD template

🔗 How to Build a Flexible Product Road Map​

🔗 Be a Great Product Leader​

🔗 UX Crash Course​

🔗 How to Work With Engineers​

🔗 On Writing Product Specs​

🔗 The Agony and Ecstasy of Building with Data​

🔗 How the biggest consumer apps got their first 1,000 users​

🔗 Go to Market Plan​

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💡 This Week's Recommendations

🔗 Nvidia’s Q2 earnings prove it’s the big winner in the generative AI boom: Nvidia cemented its Wall Street darling status and asserted clear leadership of the generative AI space with their Q2 earnings last week. Reported revenue was $13.51 billion, a number beating Wall Street expectations, and double the revenue generated in 2022 Q2. Supplying the AI boom is proving to be incredibly valuable...

🔗 AI startups: Sell work, not software: This is an excellent article by Sarah Tavel, explaining how AI is enabling a change where startups have the opportunity to sell the work itself rather than just the software. In a lot of ways, it's what we're trying to do at Cassidy.

​🔗 10X coders beware: Meta’s new AI model boosts coding and debugging for free: Meta is making big strides in the open source AI model race. This week they released "Code LLama", a powerful open source model designed to assist programmers by generating and debugging code.

🔗 Finetuning LLMs: OpenAI recently released fine-tuning for their ChatGPT 3.5 model. Want to learn more about fine-tuning and how to do it yourself? Check out this course.

🔗 AI-Created Art Isn’t Copyrightable, Judge Says in Ruling That Could Give Hollywood Studios Pause: A federal judge in the US has upheld a finding from the US Copyright Office that a piece of art created by AI is not open to protection. The judge said that copyright law has "never stretched so far" to "protect works generated by new forms of technology operating absent any guiding human hand." We're going to see a lot more of these cases...

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Thanks for tuning in,

Justin

​Justin's Full Content Library | Previous Newsletters​

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