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Hey there AI-curious product people 👋

OpenAI just launched the GPT Store - a cool spot to unleash your AI creativity. They're making AI easy, paying creators, and aiming for wild innovations.

But are these custom bots just flashy distractions or real value? Also, OpenAI's gotta balance the cash flow without overshadowing progress. Let's peel back the layers on the potential bumps in the road - see my 📣 Weekly Soapbox.

Here’s a summary of what’s covered in this week’s Product Prompts:

📣 Soapbox: The strategy and risks for OpenAI with its GPT Store launch

👀 AI startup to watch: Perplexity - quick, easy, trustworthy research on demand.

🧠 Things to know: 

1. Generative AI for iPhone and for creating apps, is coming

2. Deloitte is rolling out a generative AI chatbot (developed in-house) to 75,000 employees.

🛠️ AI Toolkit:

Prompt ChatGPT from inside Excel and Google Sheets; rapidly prototype interactive web apps using natural language; your always on AI-driven research analyst; and monetise your GPT with Stripe, ahead of GPT Store launch.

📖 ReadMe:

New Google Bard leak reveals a ton of new features headed for Google's ChatGPT rival

Weekly Soapbox 📣

OpenAI is launching its GPT Store this week. (If you haven’t tried building your own GPT yet, you’re missing a trick.)

Here's my perspective on OpenAI's potential product strategy with the GPT store:

Driving adoption through accessibility

By making AI creation incredibly easy and accessible, OpenAI likely aims to dramatically expand the number of people actively using and engaging with their models. More hands-on adoption drives visibility, mindshare, and continued model improvement through broadened data collection.

Monetising power users

For those product teams or power users who create valuable GPTs, the store lets OpenAI monetise and incentivise them to keep creating. They become an indirect sales channel, creating tools that provide value on top of OpenAI's core platform.

Emergent innovation

OpenAI is placing a bet that by fostering a bustling ecosystem of creators, emergent innovation will arise that even they couldn't predict. Niche use cases and creative integrations that would never surface otherwise may flourish in a decentralised marketplace.

Road-testing business models

This is a relatively low risk environment for OpenAI to experiment with different monetisation models and incentives before rolling them out more broadly. Testing revenue sharing rates, pricing structures, etc. provides key learnings.

Market feedback on capabilities

Popular use cases bring strong signals about where capabilities are lacking vs. excelling. This user-driven feedback helps guide OpenAI's roadmap based on real-world demand rather than hypotheses.

An App Store blueprint

OpenAI is taking inspiration from proven platform business models like Apple's App Store. While not fully analogous, the App Store's runaway success likely provides confidence in the viability of a decentralised, creator-driven marketplace.

So while the GPT Store does have a sound basis in terms of product strategy for OpenAI, as with any big new launch from the world's leading AI company, it does raise some broader considerations beyond strategic objectives.

As much as the store offers opportunities to advance OpenAI's goals, it also poses risks if not really carefully executed and monitored - from the need to provide real value beyond novelty, to walking the line between democratisation and responsibility, to ensuring financial motivations don't override ethical progress.

While the potential benefits are enticing, realising the upside is going to take some proactive mitigation of the downsides. OpenAI must keep one eye fixed firmly on long-term positive impact as they nurture this fledgling marketplace. Although an app store model provides a solid strategic blueprint, applying it thoughtfully to AI demands unique care and perspective.

If done right, the GPT store could accelerate global access to beneficial generative AI - but potential pitfalls await if priorities become misaligned.

Let’s go deeper on these potential banana skins for the store.

The value litmus test

A key question swirling around OpenAI's GPT store is whether the customised bots will provide meaningful new value - both for product teams using AI to enhance workflows and for end users ultimately consuming these tools.

On the product side, some narrow task bots could yield efficiency gains, especially if tightly integrated into existing stacks. But generalised novelty bots built for mass appeal are unlikely to move the needle. The true test will be enduring productivity lift versus one-off novelty.

And for end users, early GPTs may impress initially through humor or novelty, but interest could quickly wane without true utility. For both creators and consumers, the store will have to evolve beyond gamification and gimmicks.

The key is scalable value - where time savings compound, workflows tangibly improve, and customer experiences genuinely benefit. One-off gains will give way to sustained transformation. But maximising this requires thoughtfulness - mitigating risks, intricately integrating GPTs, and co-evolving hand-in-hand with human usage.

For OpenAI, this means carefully curating and guiding the marketplace beyond superficial tricks. For product teams and users, it means approaching with clear eyes and measurable value as the litmus test.

I reckon the GPT Store is a smart move in theory. You look at big software players like Shopify, Valve, Apple, and Roblox - a chunk of their success comes from the moolah generated by their platforms and the network effects. GPTs and the GPT Store are pretty much like that, turning a general AI into an app with prompts and data.

What's funky about GPTs, though, is how easy it is to fork and create them. Charging for something everyone can toss a prompt or knowledge into - that's the head-scratcher. It's like, how do you put a price tag on the very essence of what makes the "app"?

I'm intrigued to see how this all plays out.

Thinking about it:

🤔 Maybe the whole low entry bar doesn't bother most users; they just want a solid GPT without the DIY hassle. That's generally been the case.

🤔 OpenAI might just be aiming for a bunch of apps built on ChatGPT, creating a sweet ecosystem.

🤔 The crazy low entry might spark more competition in making kickass GPTs.

🤔 Winning the GPT Store might end up being more about marketing and positioning than the actual development.

But, hey, there's this little thing called Action.

Actions (aka Agents), like plugins, could be the bomb with GPTs.

And it would also throw in a barrier, creating a competitive moat.

Monetisation motives in focus

OpenAI's move towards an app store model is undoubtedly a money game. While not inherently shady of course, there's a risk of putting short-term profits above smart AI growth. A bustling marketplace might shift the focus away from responsibly advancing the core technology.

Democratising AI has its perks, but it's not all rainbows. Easy access means more experimentation, but it also opens the door to a flood of sketchy or biased content. The flip side of casual creators whipping up GPTs in minutes is a potential mess.

Nipping misuse in the bud for customised GPTs is a massive challenge. OpenAI needs to juggle democratisation with responsibility as they navigate this fresh territory. It's on them to make sure money matters don't overshadow ethical AI strides.

AI startup to watch 👀

Perplexity

Launched in August 2022, Perplexity, a startup with a bold vision to challenge Google, combines the elements of a chatbot and a search engine, delivering real-time information with transparent sources.

If you haven’t tried it yet, you really should, especially for competitor research:

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Despite not yet turning a profit, the company boasts an impressive growth to 10 million monthly active users, and the mobile app has gained over one million installations on both iOS and Android.

They’re #10 in terms of web traffic to all AI apps:

Interest in Perplexity AI grew 20530% over the past year, compared to the year before, putting it at a current volume of 471K searches per month, as of last month:

Key takeaways for product teams

Perplexity's emergence in the search engine arena could have several implications for product teams and how they approach building products:

💡 With Perplexity focusing on direct answers rather than traditional search results, product teams may need to reconsider how users access information within their products. This could involve implementing more intuitive and efficient ways for users to obtain relevant information quickly, reducing reliance on extensive search result lists.

💡 Perplexity's Pro version allows users to choose from various language models, including OpenAI's GPT-4 and others. You should evaluate the potential benefits of integrating different AI models into your products based on user needs, preferences, and the specific context of their applications.

💡 The emphasis on real-time information and source transparency by Perplexity suggests a growing user demand for trustworthy and up-to-date content. Product teams may need to focus on enhancing user experiences by ensuring the accuracy and reliability of the information provided within their products and incorporating features that highlight data sources.

💡 Perplexity's subscription-based Pro version demonstrates an alternative monetisation strategy in the AI-driven product space. Product and growth leaders might explore similar subscription models or innovative pricing structures to generate revenue while providing users with customisable features and options.

💡 User expectations are changing: Perplexity's CEO anticipates a behavioural shift in how people access information online. Product teams should stay attuned to these changing user behaviours and preferences, adapting their products to align with evolving expectations in information retrieval and consumption.

Things to know 🧠

🧠 Apple is on schedule to announce a series of generative AI-based tools at its WWDC in June. Link.

🧠 Deloitte is rolling out a generative AI chatbot (developed in-house) to 75,000 employees. “PairD” can be used to answer emails, draft written content, write code to automate tasks, create presentations, carry out research and create meeting agendas - all in an attempt to boost productivity. Link.

AI toolkit 🛠️

Numerous AI - Prompt ChatGPT from inside Excel and Google Sheets

GPT engineer - rapid prototyping of interactive web apps using natural language

CBInsights - your always on AI-driven research analyst

Stripe Your GPTs - monetise your GPT with Stripe, ahead of GPT Store launch

📖 ReadMe

New Google Bard leak reveals a ton of new features headed for Google's ChatGPT rival. Link.

AI co-pilots to make you both less smart and smarter. Link.

OpenAI hits back over New York Times lawsuit. Link.

How is the UK government approaching AI regulation? Link.

But that’s not quite all for this week!

Every Sunday, I’m starting a new edition of Product Prompts called The AI Advantage, where a stellar guest from the product world shares the AI-powered tactics and prompts they use to supercharge their workflow.

The first week has a fantastic guest so keep an eye out in your inbox for this Sunday’s edition.

Remember, if you're enjoying this content, please do tell all your product friends to check it out and hit the subscribe button :)