John MilinovichDangerously Good Product Managers
Co-authored with Harsan Sidhu Product managers play a crucial role in consumer product companies as they serve as the central point of contact between the company's users, product development teams, cross-functional teams, and leadership team. While a product manager's success is dependent on the impact and quality of their team's work, it's easy to fall into the trap of being a bad PM who contributes little to the team beyond attending meetings and writing a few documents...
John MilinovichThe crypto mullet: web2 in the front, web3 in the back
The next wave of $1B+ crypto companies will disrupt incumbents by keeping an existing consumer experience in web2 while rebuilding its back office in web3. Disruptive technologies create transformative business models when they enable a 10x better consumer experience (ie, Netflix with streaming tech vs. going to Blockbuster) or a 10x cheaper back office (ie, Instacart with mobile tech vs operating a grocery store). Today, the blockchain is arguably a 10x+ worse consumer experience for anyone ...
John MilinovichOn Chain Conglomerates
Crypto Mullets are the next wave of multibillion dollar web3 companies, and one way they’ll come to market is through on chain conglomerates powered by annuity-bearing NFTs. Traditional conglomerates are, “a combination of multiple business entities operating in entirely different industries under one corporate group, usually involving a parent company and many subsidiaries” (source). I believe this same model will come to fruition on chain to fund and create niche DAOs that generate on chain...
Passionate product manager and team player. 2x YC founder, formerly of Clubhouse, Aesthetic, Pinterest, URX and Google.
John MilinovichDangerously Good Product Managers
Co-authored with Harsan Sidhu Product managers play a crucial role in consumer product companies as they serve as the central point of contact between the company's users, product development teams, cross-functional teams, and leadership team. While a product manager's success is dependent on the impact and quality of their team's work, it's easy to fall into the trap of being a bad PM who contributes little to the team beyond attending meetings and writing a few documents...
John MilinovichThe crypto mullet: web2 in the front, web3 in the back
The next wave of $1B+ crypto companies will disrupt incumbents by keeping an existing consumer experience in web2 while rebuilding its back office in web3. Disruptive technologies create transformative business models when they enable a 10x better consumer experience (ie, Netflix with streaming tech vs. going to Blockbuster) or a 10x cheaper back office (ie, Instacart with mobile tech vs operating a grocery store). Today, the blockchain is arguably a 10x+ worse consumer experience for anyone ...
John MilinovichOn Chain Conglomerates
Crypto Mullets are the next wave of multibillion dollar web3 companies, and one way they’ll come to market is through on chain conglomerates powered by annuity-bearing NFTs. Traditional conglomerates are, “a combination of multiple business entities operating in entirely different industries under one corporate group, usually involving a parent company and many subsidiaries” (source). I believe this same model will come to fruition on chain to fund and create niche DAOs that generate on chain...
Passionate product manager and team player. 2x YC founder, formerly of Clubhouse, Aesthetic, Pinterest, URX and Google.
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Natural language is the new interface for the web, and in 2023 I predict we will see it become increasingly prevalent across many of the tools and software that we use every day. From virtual assistants and chatbots to general purpose search products and creative tools with sophisticated editors, we will see a wide swatch of existing and new use cases for natural language interfaces (“NLIs”) not dissimilar to the wave of new mobile interfaces we saw in 2008 after the App Store was introduced.
One of the key advantages of NLIs is their accessibility. By allowing users to communicate with a tool or software program using everyday language rather than a specialized syntax or set of commands, NLIs can make these tools more accessible to a wider range of users. This massively lowers the barrier to becoming a power user of otherwise complicated tools, which in turn will create tremendous leverage and creativity for people around the world.
Imagine a world where every software product was as easy to use as Google Assistant or ChatGPT. What kinds of use cases, creativity and innovation will be possible when this is something that can be taken for granted? I predict that one of the first verticals to deeply adopt NLIs will be creator tools such as Figma, Canva, Photoshop and Ableton. Instead of the build and iterate creative process being done with swipes and mouse clicks, what happens when it can be done more similar to if you were working with a professional designer at your side?
NLIs are not without their challenges. I expect to see dramatic progress in a few of the key problem areas for NLIs within 2023:
Verticalization: Large Language Models (LLMs) demonstrate powerful generalization power across a wide range of tasks, but are even more powerful when combined with augmentation layers that give domain-specific context. We’ll see a lot more applications of technologies like Dreambooth to help with this.
Education: While NLIs will become far more accessible, the onus will be on product designers and developers to create clear onboarding and education about how to use their specific breed of NLI.
Speed: Training and deploying NLIs is a very time- and compute-intensive task that requires a lot of specialized time and resources. In 2023 we’ll see a proliferation of developer tools that continue to make deploying generalized LLMs and training your own domain models easier and easier.
Despite these challenges, the potential for NLIs to revolutionize the way we interact with the web and with tools and software is clear. As more and more companies recognize the benefits of using natural language as an interface, it is likely that we will see its continued development and adoption in the coming years. Whether we are using virtual assistants to perform tasks and answer questions, or using NLIs to edit and manipulate images and graphics, it is clear that the future of the web is one where natural language plays a central role.
Natural language is the new interface for the web, and in 2023 I predict we will see it become increasingly prevalent across many of the tools and software that we use every day. From virtual assistants and chatbots to general purpose search products and creative tools with sophisticated editors, we will see a wide swatch of existing and new use cases for natural language interfaces (“NLIs”) not dissimilar to the wave of new mobile interfaces we saw in 2008 after the App Store was introduced.
One of the key advantages of NLIs is their accessibility. By allowing users to communicate with a tool or software program using everyday language rather than a specialized syntax or set of commands, NLIs can make these tools more accessible to a wider range of users. This massively lowers the barrier to becoming a power user of otherwise complicated tools, which in turn will create tremendous leverage and creativity for people around the world.
Imagine a world where every software product was as easy to use as Google Assistant or ChatGPT. What kinds of use cases, creativity and innovation will be possible when this is something that can be taken for granted? I predict that one of the first verticals to deeply adopt NLIs will be creator tools such as Figma, Canva, Photoshop and Ableton. Instead of the build and iterate creative process being done with swipes and mouse clicks, what happens when it can be done more similar to if you were working with a professional designer at your side?
NLIs are not without their challenges. I expect to see dramatic progress in a few of the key problem areas for NLIs within 2023:
Verticalization: Large Language Models (LLMs) demonstrate powerful generalization power across a wide range of tasks, but are even more powerful when combined with augmentation layers that give domain-specific context. We’ll see a lot more applications of technologies like Dreambooth to help with this.
Education: While NLIs will become far more accessible, the onus will be on product designers and developers to create clear onboarding and education about how to use their specific breed of NLI.
Speed: Training and deploying NLIs is a very time- and compute-intensive task that requires a lot of specialized time and resources. In 2023 we’ll see a proliferation of developer tools that continue to make deploying generalized LLMs and training your own domain models easier and easier.
Despite these challenges, the potential for NLIs to revolutionize the way we interact with the web and with tools and software is clear. As more and more companies recognize the benefits of using natural language as an interface, it is likely that we will see its continued development and adoption in the coming years. Whether we are using virtual assistants to perform tasks and answer questions, or using NLIs to edit and manipulate images and graphics, it is clear that the future of the web is one where natural language plays a central role.
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