3 Lessons Web3 Founders Can Take From ChatGPT’s Success
First impressions are everything for a startup trying to be taken seriously by top VCs and catch the attention of new users.
But what happens if your project, or entire industry, gets off on the wrong foot? Many Web3 projects introduced themselves to the world during the metaverse boom a year and a half ago after Facebook’s rebrand as Meta Platforms. Instead of seizing the momentum to push forward the development of blockchain applications, too many of them fell into the hype trap.
The crypto industry is littered with projects, protocols and corporations that made crucial mistakes, leaving a bad taste in the mouths of industry stakeholders and driving the market as a whole to stagnate.
Bonnie Cheung is the head of strategy at Sending Labs.
Now, founders have a unique opportunity to learn from ChatGPT, the artificial intelligence platform developed by OpenAI, and the astounding success it has had in shifting the AI development paradigm. While Web3 and AI face similar problems in the public eye – part of a general “techlash” against seemingly reckless innovation and profligate spending – crypto can adopt ChatGPT’s approach to development and branding to increase adoption.
Web3’s primary impediment today is that its grand vision of unmediated computing and finance has outpaced practical and user-focused development. That is rather than a lack of enthusiasm for the technology behind it.
Many crypto founders and developers have a “north star,” but that often does not prevent them from getting caught up in the hype of a bull market or trend and forgetting the most essential part of building a product – making something people will love or want to use.
See also: Crypto Long & Short: Finding Alpha in AI-Related Crypto
Looking back at the history of adoption tidal waves, massive growth only really happens when elements of interoperability and user experience (UX) come together. Tangibility, how tech feels for potential users, is crucial when it comes to practically every new tech development, especially concerning abstract concepts like AI or Web3.
Consumers have been using AI for years through Google searches or Netflix suggestions, often without knowing it. But they only started to care about machine learning after ChatGPT commanded attention by plainly showing how impressive generative AI can be.
In contrast, Web3 remains nebulous. A majority of people can’t see or use most of its applications, leaving projects struggling to justify why anyone should care about it.
Here are three ways Web3 can adapt to a rapidly changing environment, as GPT-4 comes online.
1. Build a product within the industry instead of starting from scratch
Yes, it’s important to have a grand vision of what Web3 can be, but not every company can carry the weight of an entire industry on its back. Solidifying a niche, or a “hero product,” that contributes meaningfully to the entire ecosystem when developers achieve what they set out to build can set a model for others.
During the last blockchain boom, too many projects sought to build all-inclusive ecosystems that would essentially replace banks or dominant blockchains. Of course, the idea that a single company can upend and replace an industry shaped by centuries of experience and growth is absurd. Web3 is not exempt from economic reality.
To actually make it in Web3, much like practically every other industry, founders have to start with a gap they can realistically address. The impetus for starting Sending Labs, for example, came from our founding team noticing that Web3 had virtually no cohesive communications infrastructure, especially at the group level.
This created a sort of catalyst to start building a product that concretely worked to solve this glaring issue in the wider context of Web3. Sure, we could have set our sights on developing an entire ecosystem from scratch. But if the fundamentals are already there in technology such as blockchain wallets, improving upon a foundation that people already use is a much more feasible way to achieve our own goals as a company and, ultimately, push Web3 as an industry forward.
2. Don’t make your sector your selling point
If you’re making the blockchain the main draw of your product, you’ve already shot yourself in the foot. Just as you don’t see the gears turning behind ChatGPT, users don’t even need to know they’re using blockchain. Not to say that a product’s underlying technology should be a secret or a black box, but outsiders shouldn’t need to have an encyclopedic knowledge of blockchain processes to enjoy a product.
Making your sector a selling point can also alienate outsiders who don’t necessarily understand your project’s underlying technology. If you’re leveraging blockchain to offer users concrete utility, they should be able to feel those benefits in the use of the product rather than read about how blockchain is revolutionary in your white paper.
Having the product stand on its own while giving users the chance to learn more if they care to do so can make their connection to the technology more substantial. Again, OpenAI doesn’t make it essential for you to know how its AI model actually works to use ChatGPT to outline your essay or come up with an eye-catching tagline.
3. Not every Web3 product needs to target crypto outsiders
Most consumer-focused blockchain projects dream of being the ones to crack the code on mainstream adoption. But it’s essential to provide something of utility and novelty to the communities that are either somewhat familiar or fully engrossed in blockchain before shifting to mainstream audiences.
When a crypto project promises “privacy-preserving” alternative internet services to the wider public, they’re clearly targeting the wrong audience. People who have never purchased bitcoin won’t care – that is if they even hear about it. This is a sure pathway to keeping projects permanently locked at square one.
Rather, to build out Web3, innovative founders should meet the needs of consumers who are already engaging with Web3 products at some level. If your product is actually effective and offers utility to the audiences that have already seen it all in crypto and blockchain, they will be able to vouch for it.
This type of expert-level, word-of-mouth adoption happens in any nascent industry or new technology. Think about it: If you were thinking of downloading a new investment app, you’re probably likely to ask a friend that’s familiar with investing and finance and that has seen a million different similar programs to say if it’s a worthwhile addition. The same principle applies to drawing in industry outsiders to Web3.
Tech’s unstoppable momentum can be curtailed by humans
Web3’s design as a comprehensive ecosystem presents a unique challenge for startups in terms of creating products that address the entirety of Web3. Building the train while the train track is being laid is hard enough.
Imagine building the train and contributing to the laying of the track at the same time. It requires tremendous discipline and laser focus. This type of development model is unsustainable because projects either lack resources or stretch themselves thin trying to solve every sector-specific problem instead of trying to solve one specific issue.
OpenAI didn’t create ChatGPT to fix the world or get everyone to understand neural networks. It started with a single prompt where no one needed instructions to start using it, so audiences could experience for themselves how this simple prompt can make their lives better. Web3’s ChatGPT moment will come when we can do the same for Web3 users.
See also: The Truth About Artificial Intelligence and Creativity
Social media has the potential to drive widespread adoption of Web3, and the building blocks are already in place. Decentralization can serve as the backbone for subsectors, such as direct messaging, group communications and the blockchain’s commercial value can all build on in an accessible way.
Creating an entire ecosystem and infrastructure from scratch is uniquely daunting and challenging for Web3 startups. Just having the conviction to build a technologically cool product is not enough. If ChatGPT has taught us anything, it’s the need to always remember that adoption comes when users find your product fun and enjoyable to use.