Next Monday, our next AI Incubator Student Demo Day, you’ll see 5 new students present their latest AI prototypes – and in doing so, each of them had to make a big decision:
Do I create a product for consumers?
Or a process that I can use to enhance my existing business workflows?
And if you look at previous Demo Days, you'll see that Laura and Grady focused on products, while Erich and Mircea built processes.
But they didn't just take a wild guess to decide on their approach – there's a straightforward framework to determine which is right for you. In today's email, I'll show you how they decided what to build.
Let's break down the two major categories:
1 - AI Products are software/tools that are built for public use by customers.
Products can take the form of a software-as-a-service subscription (like paying $20/mo for EveryAlt, which I created) or a one-off purchase like the ones offered by Nakkara.ai, which turns AI-generated images into real-life 3D-printed objects. (Nakkara was created by one of our students – you can watch Karl demo it here.)
2 - AI Processes are internal workflows that you use to improve the speed, quality and/or efficiency of your existing job or business.
They are not intended for use by the general public. Instead, they help you make more money by supercharging your existing non-AI products or services.
One of our students, Erich, is an Emmy-winning television producer who built an internal process that combines 10 GPTs to take vague requests from studios and turn them into living, breathing, highly creative “sizzle reels” that act as pitches for new TV shows.
At Demo Day, he showed us how he used AI to create dozens of pitches for new History Channel shows.
His new process takes a matter of minutes, but would have taken months (or been impossible) without AI. It allows him to go from creating four sizzle reels a year to dozens, and each one has the potential to be a new TV show (and a big payday).
Another student, Matt, built a new AI process to allow him to rapidly produce reports for clients of his wellness consulting company, Intwelligence.
In the past, it would take 10 hours for him to build a report and a set of recommendations for one of his clients.
Now, with the help of AI, he can generate those reports in about 20 minutes. He uses no-code AI tools to analyze the answers his clients give him on a questionnaire, then adds his unique subject-matter expertise to get the AI to output smart recommendations and accurate summaries.
(By the way – Karl, Erich and Matt launched all of these ideas without writing a single line of code. You can see exactly what they built in the free replays of Demo Day.)
Which path is right for you?
Since products are more public, they’re usually top-of-mind for our students when they’re generating ideas. However, the product approach will not necessarily be the right one for you – and at the very least, it may make sense to start with a process and then move on to a product later.
Let’s look at the pros and cons of each approach – while also remembering that you can eventually do both (or create many variations of each) once you’re in the groove of AI creativity.
AI Products can scale up dramatically over time.
For example, let’s imagine Karl’s typical customer spends $100 with Nakkara.ai. If he gets three new customers this month, that’s fun but not really financially meaningful. But if he scales that up to 80 customers a month, he’s now bringing in $96k a year in revenue, which is a big deal.
Karl could handle the extra 77 customers a month with zero additional expenses on the e-commerce platform he built.
Every order would be profitable, and it would likely take him a few minutes of manual work to fulfill each one (and even that could be made more efficient over time).
When a product scales, revenue growth significantly outpaces growth of expenses, and you get a super-profitable power law growth chart that looks like this:
Products aren’t perfect, though. The biggest challenges are:
If you create a product, you have to enjoy marketing and selling that product. So if marketing makes you squeamish, it will be very hard for you to create a successful product. Not to be too self-referential here, but I actually ENJOY making training videos for all of you, and I enjoy hosting the live calls. I also enjoy telling more of you about it because I genuinely enjoy it. As you think of creating your own thing, ask yourself – would you enjoy telling people about it?
Products can be costly to build, especially if you don’t have a clear plan for creating a prototype and validating it right away. In the course, we help students solve this problem by teaching them how to create 10-Hour Prototypes and sell to real customers before the full product is ready. (I call this “Selling the Table of Contents.”)
Even in the best-case scenario, some products will be less popular than you expect. You may need to try 5 or 10 prototypes before you find a hit. (That’s why we teach you how to build prototypes extremely quickly.)
The last challenge is that there are a lot of psychological traps around product-creation that stem from fairy-tale stories of entrepreneurs who made billions after starting in their garage. These stories are true, of course, but they’re a tiny fraction of reality. If you have your heart set on being the next Mark Zuckerberg or Steve Jobs, you’re setting yourself up for disappointment and confusion. (In the Innovating with AI course, we talk about how to create a more realistic mindset that allows you to build solid income streams without straying into fantasyland.)
AI Processes can 3x or 30x your productivity
I love creating internal AI processes because they don’t require all the prototyping, validation, research and marketing that comes with creating a product. Instead of worrying about the outside world, you can look specifically at the thing you know best – your own job – and figure out where AI can make it easier.
Erich did this with TV-show idea generation, which was a huge bottleneck for him in the past. Even if he sat around all day brainstorming, there was no guarantee that a decent show idea would come out of it. Now, his AI process ensures he can generate ideas any time with minimal effort. Pre-AI, he could generate 4 sizzle reels a year. Now, he can easily do 3x to 5x that, which means it’s way more likely he’ll create a hit show.
Matt did this with his report generator – before, the reports for new clients were a bottleneck because they took 10 hours to create. That meant that the maximum speed at which he could onboard a new client was 1 client every 10 hours. Now, he can onboard 1 client in 20 minutes, something like a 30x improvement.
Beyond the mathematical improvements, the huge benefit of an AI process is that it allows you to accomplish more while expending less mental energy. It wasn’t just time that was getting in Matt and Erich’s way – just think about how exhausting it is to spend 10 hours writing a report! Now, Matt can onboard more new clients and have more energy for the other important things in work and life.
The drawback of building an AI process is that it’s not as sexy or exciting as a product – that’s the flip side of the strange psychology in which we treat product entrepreneurs like they are rockstars or mythological heroes.
But in exchange for a little bit of sexiness, you get a huge boost – more clients, more time, more money, or all of the above – from a process that you can build in 10 hours or less.
And the best part of building AI processes is still to come...
A process can evolve into a product
When you build an AI process for yourself or for your existing company, you are scratching your own itch. But it’s highly likely that lots of other people have the exact same itch, too.
In this way, processes can actually be working prototypes of products you might build in the future. In fact, this is how pretty much all of my successful products have evolved.
For EveryAlt, we wanted to see if we could use AI to make sure our clients didn’t forget to add alternative text to their website images, since that’s very important for accessibility and compliance with the Americans with Disabilities Act. We built it for ourselves, it worked, andnow we’ve shared it with lots of other web designers who need the same thing.
Same thing for BusinessEnglish.ai, which we created to help our employees for whom English is a second language. They loved it and started using it to improve client communication, and now lots of other people are paying us to use it as well.
I also just finished a new AI process that reads and categorizes all my email for me instantly. (It’s called Inbox Autopilot, and you can sign up for the private beta now if you’d like to try it.) I’m not sure yet if it’ll be a hit product, but I know it saves me 5+ hours a week and TONS of stress since I never have to look at a cluttered inbox again. (Also, it completely eliminates cold email solicitations, which is a huge bonus.)
When you look at Erich and Matt’s processes, you can see a path for them to become products, too. Erich could commercialize his process and sell it to other studios, or they could pay him as a consultant to run his process for them. Same with Matt, who could productize what he’s doing and sell it to other wellness professionals, personal trainers, etc., who create similar reports for their clients.
In other words, you don’t have to choose between one or the other – your process may become a product, or you can experiment with both approaches once you master the art of the 10-Hour Prototype.
Now that you have a clear picture of the different paths you can take, a question – which one will you start with first? A - I’ll start with an AI product
If you’re struggling to decide or have specific questions, just reply to this email. I read every message.
See ya next time,
– Rob
P.S. The Innovating with AI Incubator is opening next week.
If you want to be the first to know when the course is open, click here to join the waitlist via text message or WhatsApp - we’re putting together an early bird bonus for those who do.
Also: iPhone Mirroring Is Here and Mostly Works, and More! How-To Geek Logo October 8, 2024 Did You Know At the end of the song "Sweet Child O' Mine," found on Guns N' Roses'
How Sonos Lost $200M: A Hard Lesson in Quality 🚨 View on the Web Archives ISSUE 240 October 8th 2024 COMMENT Welcome to the 240th issue! Back in June, I shared with you about the big problem with a new
Differences Between Python's Mutable and Immutable Types #650 – OCTOBER 8, 2024 VIEW IN BROWSER The PyCoder's Weekly Logo Differences Between Python's Mutable and Immutable Types In this
As of 2023, Hurricane Katrina is the costliest natural disaster in US history, causing over $200 billion in damages in 2024 dollars. View Online | Subscribe | Download Our App Presented by: NEW REPORT:
Daily Coding Problem Good morning! Here's your coding interview problem for today. This problem was asked by Yelp. Given a mapping of digits to letters (as in a phone number), and a digit string,
Apple's Leak, Disney's Star Wars, Google's Epic Fail, OpenAI's Space Race The Race for Server Space Apple's Leak, Disney's Star Wars, Google's Epic Fail, OpenAI's Space
Plus new ways to deploy Go apps, reflecting on reflection, and Windows gets high resolution timers in Go. | Together with Frontend Masters logo #526 — October 8, 2024 Unsub | Web Version Go Weekly
Here's how organizations can partner with Visual Capitalist to leverage world-class data storytelling, and its strong audience and reach. View Online | Subscribe | Download Our App For 13 years,