Five lessons for building AI apps
We crossed 1M installs of our AI presentation maker last week, so we wanted to look back and share some of our key lessons learned on how to build a great AI app.
1. Capitalize on the hype, but tune out the noise
There is so much interest in AI, and it is growing so quickly that you should absolutely lean in to “AI” as a core piece of your marketing message.
But… it’s important to identify the customers who need to solve a specific pain point using your product vs. people who just “want to try out AI.” The “AI tourists” will give you lots of (distracting) feedback on your product, but they won’t get out their credit cards to pay.
That being said, it’s rare that people want to spend money on new products, and even rarer that they want to spend their time learning about new products. With AI, you need to take the opportunity and capitalize on it!
2. Decide how much time you want to spend educating customers
Reality rarely meets customer expectations in AI. If the average AI demo is only ~60% possible by the time you actually use the product, the average customers’ expectations are (at least) 120% of what’s possible.
Depending on your GTM motion and the type of app you are going to build, decide how much time you want to spend educating your customers on what’s possible, when, and how to use AI.
If you are selling $100K+ deals, this is just going to be part of the process. If you’re building a PLG product, find the customers who already know what to expect and how to use your tool.
You probably shouldn’t build a chatbot
ChatGPT has been a huge success, but for most use cases, AI-enabled workflows and apps are a much better interface than AI chatbots. Chat is too open-ended and doesn’t expose the right options and features to users.
For example, it’s hard to know what you can use ChatGPT or Copilot to do, and that ends up in a lot of missed expectations when people ask them to create a presentation, and they can’t create PowerPoint files.
Even when ChatGPT reaches “human level intelligence,” it will still be better to use structured apps and workflows to give AI instructions. That’s why we literally have dozens of different project management apps for humans to communicate with one another.
“ChatGPT wrappers” will be billion dollar companies
“ChatGPT wrappers” are the new “CRUD apps.” Like a whole generation of incredible SaaS companies that “just” built CRUD apps, multibillion dollar AI companies will be built around amazing user experiences, data integrations, and pairing a great product with the right GTM model.
It’s not easy to build a great app, whether AI-powered or not, so don’t feel bad if an investor calls your app a “ChatGPT wrapper.” Just focus on solving valuable problems for customers.
Ship. Get real data, and use it to improve your product.
Data really is key now. It’s hard to iterate on AI products without real-world usage of your product, but once you have it, it’s way easier than ever before to make things faster and better.
Here’s a look at our subscriber chart — the 1s at the bottom of the chart are annotations for key product releases, model updates, etc. As we built up momentum and learned more about what our customers wanted, it made it easier and easier for us to continue improving the product.
Conclusion
It’s an exciting time to be building AI products. There is a lot of potential, and there are a lot of unknown unknowns. We think the best way to learn and shape the future of AI is to build something yourself, and that’s what we are doing at Plus!
If you’re interested in trying out our AI presentation maker, we offer a free 7 day trial.
