For a long time, the web3 ecosystem had to organize and communicate on web2 platforms. From the memes of crypto twitter to the project-specific communities that congregated in Discord and Telegram, there were no dominant web3 platforms. That is changing quickly and there is something special happening in web3 social right now.
Over the past several years, we have seen a series of new projects emerge that finally give the web3 community a place of their own. They are unique, constantly evolving, and growing quickly. These projects have real tailwinds because people who like crypto have an explicit preference to use crypto-native products instead of web2 ones (even if they are less convenient to use), they are willing to experiment with and try new things, and nascent communities are always more fun than big ones with a lot of noise.
The trend for a lot of these projects is that they begin as a skeuomorphic representation of their web2 counterparts to attract an initial audience, and then they rapidly experiment to introduce weird and crypto-native features. This is just the beginning of what we are seeing:
I’m sure there are plenty of other examples I am missing here. In all of these instances, the web3 version initially mirrors the web2 counterpart, but then they quickly diverge. A lot of times this divergence is marked by some crypto-native feature: financialization and minting as a web3 version of “liking,” things that can only happen because of web3 composability like Frames, the emergence of memetic tokens that transcend applications like DEGEN, etc. All of these things are new, they are weird, and they are uniquely web3. The other characteristic they share is they are simply more fun and entertaining than anything that exists in web2.
We are now beyond the hand-wavey language and posturing and pounding the table on “everything needs to be open and portable and LOUD NOISES” We are seeing applications emerge that are fun, have real DAU and utility, are birthing products and memes that transcend beyond those communities, and represent the beginning of a new wave of emergent social networks that are fundamentally different. And while it’s still early (when will it not be“early?”), things feel more promising, useful, and engaging than they ever have.
At the very least, it’s a joy to see so many people rapidly experimenting together, building new products and features that could have never existed before, trying new things, and having a good time. It’s very reminiscent of early Twitter where an early community of curious people took a platform and morphed it to their liking. Now it gets to happen all over again, just with a new set of tools, functionality, and a permissionless and open system to ensure its future belongs to everyone.
One of the most important skills founders must hone is their ability to tell a compelling story. Part of that story, if they plan or want to use venture capital as a tool to grow, is articulating how much money they want to raise and what they plan to do with that money.
When raising capital, it amazes me how many founders will say something along the lines of, “Well, right now the market for Series A companies is $X, so that’s what we want to raise.” I find that type of finger-in-the-wind talk extremely lame and weak. It means that you haven’t taken the time to truly think about what your goals are - e.g., growth objectives, what you need to learn, build, and prove, and what resources you need to accomplish those things - and the capital requirements to get them done.
One of the things my investors taught me is that entrepreneurs need to be good stewards of capital, and part of that is having a very keen sense of what to do with it. When raising money at groupme and fundera, we always had a crystal clear idea of how much money we wanted to raise and why. Sometimes it was to be able to pay for some rapidly accelerating variable costs attributed to our fast growth; other times, we needed to invest in hiring people with different types of skills to build things like new mobile clients, or we wanted to scale a sales team after we had a basic sense of our payback periods and how we’d operationalize onboarding and ramp cycles. This wasn’t rocket science or even calculus, it was just a simple model we’d build in a spreadsheet. It demonstrated that we had some modicum of an idea as to what we’d spend money on, when we’d spend it, and why. And it’d be reflected in a basic pro forma and financial model that would grow in sophistication as we learned more about our business over time.
GroupMe first launched as an SMS-only application. All groups were assigned a unique phone number that you could add to your contacts as Family, College Friends, or Music Crew. You’d add members to the group with a series of SMS commands. When you sent a message to your group’s phone number, a text would be relayed to everyone else in the group. All of this was built using Twilio, which at that time had found a way to abstract away all the complexity of integrating with telecommunications infrastructure so application developers could focus on building great user experiences. We would have never existed without Twilio, but it also led to a real problem with our business: we paid for every single message we sent. The average size group was six people, so we paid when someone sent a message to the group phone number, and then we paid to relay that message five times to everyone else in the group. One message meant paying for it six times on average. We also paid every month to lease the group phone numbers.
This became an extremely expensive endeavor for a free service with no means of monetization. The product grew virally. For every group that was created, one user would go off and create their own, adding five new people to the network. Every group and message sent was a variable cost, and we were beholden to Twilio’s prices. We tried negotiating but could never get prices to a place that wouldn’t put us out of business. My co-founder Steve even proposed doing an equity swap with Twilio to align our respective fates, which was a wonderful idea but sadly rejected. Our only chance of survival was to raise enough money for VCs to subsidize our text messaging product while we found ways to drive down SMS costs and migrate our user base to an over-the-top mobile messaging application similar to WhatsApp.
For a long time, the web3 ecosystem had to organize and communicate on web2 platforms. From the memes of crypto twitter to the project-specific communities that congregated in Discord and Telegram, there were no dominant web3 platforms. That is changing quickly and there is something special happening in web3 social right now.
Over the past several years, we have seen a series of new projects emerge that finally give the web3 community a place of their own. They are unique, constantly evolving, and growing quickly. These projects have real tailwinds because people who like crypto have an explicit preference to use crypto-native products instead of web2 ones (even if they are less convenient to use), they are willing to experiment with and try new things, and nascent communities are always more fun than big ones with a lot of noise.
The trend for a lot of these projects is that they begin as a skeuomorphic representation of their web2 counterparts to attract an initial audience, and then they rapidly experiment to introduce weird and crypto-native features. This is just the beginning of what we are seeing:
I’m sure there are plenty of other examples I am missing here. In all of these instances, the web3 version initially mirrors the web2 counterpart, but then they quickly diverge. A lot of times this divergence is marked by some crypto-native feature: financialization and minting as a web3 version of “liking,” things that can only happen because of web3 composability like Frames, the emergence of memetic tokens that transcend applications like DEGEN, etc. All of these things are new, they are weird, and they are uniquely web3. The other characteristic they share is they are simply more fun and entertaining than anything that exists in web2.
We are now beyond the hand-wavey language and posturing and pounding the table on “everything needs to be open and portable and LOUD NOISES” We are seeing applications emerge that are fun, have real DAU and utility, are birthing products and memes that transcend beyond those communities, and represent the beginning of a new wave of emergent social networks that are fundamentally different. And while it’s still early (when will it not be“early?”), things feel more promising, useful, and engaging than they ever have.
At the very least, it’s a joy to see so many people rapidly experimenting together, building new products and features that could have never existed before, trying new things, and having a good time. It’s very reminiscent of early Twitter where an early community of curious people took a platform and morphed it to their liking. Now it gets to happen all over again, just with a new set of tools, functionality, and a permissionless and open system to ensure its future belongs to everyone.
One of the most important skills founders must hone is their ability to tell a compelling story. Part of that story, if they plan or want to use venture capital as a tool to grow, is articulating how much money they want to raise and what they plan to do with that money.
When raising capital, it amazes me how many founders will say something along the lines of, “Well, right now the market for Series A companies is $X, so that’s what we want to raise.” I find that type of finger-in-the-wind talk extremely lame and weak. It means that you haven’t taken the time to truly think about what your goals are - e.g., growth objectives, what you need to learn, build, and prove, and what resources you need to accomplish those things - and the capital requirements to get them done.
One of the things my investors taught me is that entrepreneurs need to be good stewards of capital, and part of that is having a very keen sense of what to do with it. When raising money at groupme and fundera, we always had a crystal clear idea of how much money we wanted to raise and why. Sometimes it was to be able to pay for some rapidly accelerating variable costs attributed to our fast growth; other times, we needed to invest in hiring people with different types of skills to build things like new mobile clients, or we wanted to scale a sales team after we had a basic sense of our payback periods and how we’d operationalize onboarding and ramp cycles. This wasn’t rocket science or even calculus, it was just a simple model we’d build in a spreadsheet. It demonstrated that we had some modicum of an idea as to what we’d spend money on, when we’d spend it, and why. And it’d be reflected in a basic pro forma and financial model that would grow in sophistication as we learned more about our business over time.
GroupMe first launched as an SMS-only application. All groups were assigned a unique phone number that you could add to your contacts as Family, College Friends, or Music Crew. You’d add members to the group with a series of SMS commands. When you sent a message to your group’s phone number, a text would be relayed to everyone else in the group. All of this was built using Twilio, which at that time had found a way to abstract away all the complexity of integrating with telecommunications infrastructure so application developers could focus on building great user experiences. We would have never existed without Twilio, but it also led to a real problem with our business: we paid for every single message we sent. The average size group was six people, so we paid when someone sent a message to the group phone number, and then we paid to relay that message five times to everyone else in the group. One message meant paying for it six times on average. We also paid every month to lease the group phone numbers.
This became an extremely expensive endeavor for a free service with no means of monetization. The product grew virally. For every group that was created, one user would go off and create their own, adding five new people to the network. Every group and message sent was a variable cost, and we were beholden to Twilio’s prices. We tried negotiating but could never get prices to a place that wouldn’t put us out of business. My co-founder Steve even proposed doing an equity swap with Twilio to align our respective fates, which was a wonderful idea but sadly rejected. Our only chance of survival was to raise enough money for VCs to subsidize our text messaging product while we found ways to drive down SMS costs and migrate our user base to an over-the-top mobile messaging application similar to WhatsApp.
Ride It to the Sky
Ride It to the Sky
Some frameworks for this can be a simple comparison of what your company looks like today versus what it will look like in a future state due to this fundraise across a series of different attributes: team size and composition, customer or user growth, revenue growth, product features, releases and milestones or markets you’re live in, etc. Demonstrate and convey what will be different about your business when you raise the money. “We want to raise $10m to accomplish these things and have some buffer to invest in new initiatives opportunistically” is an infinitely better answer than “$10m feels right for us.” One shows you might be a thoughtful steward of capital, and the other is a total turn-off.
The process of doing this work isn’t super time consuming, and it’s remarkably important to help you think through just what it is you want to accomplish with money. If you’re asking for capital, at least have the wherewithal to answer these basic questions for yourself let alone investors. You’re selling a piece of your company. Be thoughtful about why you want to do that and why it will be worth it.
To get off Twilio, we first had to understand how to get closer to telecommunications infrastructure, or “the metal,” as industry veterans called it. We hired consultants who ramped us up and helped us to identify two companies, Bandwidth and Level3, that Twilio was using to build their service on top of while they hammered out deals directly with telcos. These companies were not developer-friendly friendly, and we had to task Brandon Keene with the mission-critical responsibility of migrating GroupMe off Twilio and figuring out how to rebuild all of our SMS infrastructure while maintaining acceptable service levels for our users. We also had to play Bandwidth and Level3 off each other to negotiate bulk pricing that wouldn’t put us out of business and enable us to scale for the years ahead. We were in our early 20s and had no clue what we were doing.
We miraculously managed to cut a deal with Bandwidth, migrated off of Twilio, and bought ourselves enough time to wait for most of our users to switch to the native mobile app where we didn’t have to pay exorbitant SMS costs as the service scaled.
Lately, I have seen many companies that remind me of this GroupMe experience. They are building consumer-facing applications that sit on top of LLMs, primarily Open AI, and when they get some form of traction and grow, variable costs start skyrocketing. Similar to GroupMe, very quickly monthly costs ramp up to hundreds of thousands a month, but now it’s inference instead of SMS. Over time, these costs will come down for application developers. Market competition, open source, and locally hosted models will all make inference more affordable, but it’s unclear if we are operating on a timeframe of one year or five.
For most application developers, it’s not really an option to not use these models. Consumers are growing to expect the type of functionality and features they deliver. Once things start working, there will inevitably be some form of scaling and expensive inference costs that are meaningfully higher than what pre-LLM companies have experienced. Having to deal with these issues when you are growing is really hard. You effectively have to rebuild the engine of your machine mid-flight. It’s hard enough to improve your user experience continuously, hire people, do performance management, and run your company. Adding the capital sink of inference costs creates a whole new series of challenges.
This means it is incumbent upon founders to get ahead of this issue. Several things feel like best practices now:
Plan for using more than one model when you start, and begin to diversify at signs of inflecting. Being beholden to a singular LLM is likely a recipe for disaster. You have no leverage and are subject to pricing whims. Plan to be multi-model. This doesn’t mean starting with three integrations out the gate, it just means knowing who you’ll expand with and having an idea as to when you’ll do it and what the process will look like.
Learn how to route prompts to the right models. Not all models are created equal, and some are better at certain things than others. One of our portfolio companies has a wizard-like mastery of this. There are now many companies that act as an intermediary between applications and underlying LLMs, but I think if AI is a core part of your value proposition you need to master this yourself and can’t outsource it.
Find your Brandon. Someone inside your company needs to shoulder responsibility for owning your LLM strategy and executing the plan. Like all mission-critical things, accountability is everything.
Find a group of advisors who know how this all works. While LLMs feel reasonably new to a lot of people starting companies, there are experts out there who are excellent at helping assess which models best fit your needs, and understand how to think about competitive pricing and prompt routing. It’s probably a good idea to have a circle of 2-3 advisors who have some skin in the game that you can turn to with specific questions, both strategic and tactical.
Hone your business development chops. You’re going to be in a constant conversation with model providers asking for things: pricing, integrations, access to private betas, etc. These relationships matter. Invest in them.
Raise a little more money than you think you need as a buffer so you’re not always caught on your heels reacting to these costs. When things really work it means your costs will escalate faster than expected. Extra capital on your balance sheet may provide you with some peace of mind.
I’m sure there’s a lot more to add to this list, but it’s a start. This is likely the status quo for the next several years so it’s good for entrepreneurs to be aware of the current state of affairs and have a plan for it. Exciting times come with exciting challenges.
Some frameworks for this can be a simple comparison of what your company looks like today versus what it will look like in a future state due to this fundraise across a series of different attributes: team size and composition, customer or user growth, revenue growth, product features, releases and milestones or markets you’re live in, etc. Demonstrate and convey what will be different about your business when you raise the money. “We want to raise $10m to accomplish these things and have some buffer to invest in new initiatives opportunistically” is an infinitely better answer than “$10m feels right for us.” One shows you might be a thoughtful steward of capital, and the other is a total turn-off.
The process of doing this work isn’t super time consuming, and it’s remarkably important to help you think through just what it is you want to accomplish with money. If you’re asking for capital, at least have the wherewithal to answer these basic questions for yourself let alone investors. You’re selling a piece of your company. Be thoughtful about why you want to do that and why it will be worth it.
To get off Twilio, we first had to understand how to get closer to telecommunications infrastructure, or “the metal,” as industry veterans called it. We hired consultants who ramped us up and helped us to identify two companies, Bandwidth and Level3, that Twilio was using to build their service on top of while they hammered out deals directly with telcos. These companies were not developer-friendly friendly, and we had to task Brandon Keene with the mission-critical responsibility of migrating GroupMe off Twilio and figuring out how to rebuild all of our SMS infrastructure while maintaining acceptable service levels for our users. We also had to play Bandwidth and Level3 off each other to negotiate bulk pricing that wouldn’t put us out of business and enable us to scale for the years ahead. We were in our early 20s and had no clue what we were doing.
We miraculously managed to cut a deal with Bandwidth, migrated off of Twilio, and bought ourselves enough time to wait for most of our users to switch to the native mobile app where we didn’t have to pay exorbitant SMS costs as the service scaled.
Lately, I have seen many companies that remind me of this GroupMe experience. They are building consumer-facing applications that sit on top of LLMs, primarily Open AI, and when they get some form of traction and grow, variable costs start skyrocketing. Similar to GroupMe, very quickly monthly costs ramp up to hundreds of thousands a month, but now it’s inference instead of SMS. Over time, these costs will come down for application developers. Market competition, open source, and locally hosted models will all make inference more affordable, but it’s unclear if we are operating on a timeframe of one year or five.
For most application developers, it’s not really an option to not use these models. Consumers are growing to expect the type of functionality and features they deliver. Once things start working, there will inevitably be some form of scaling and expensive inference costs that are meaningfully higher than what pre-LLM companies have experienced. Having to deal with these issues when you are growing is really hard. You effectively have to rebuild the engine of your machine mid-flight. It’s hard enough to improve your user experience continuously, hire people, do performance management, and run your company. Adding the capital sink of inference costs creates a whole new series of challenges.
This means it is incumbent upon founders to get ahead of this issue. Several things feel like best practices now:
Plan for using more than one model when you start, and begin to diversify at signs of inflecting. Being beholden to a singular LLM is likely a recipe for disaster. You have no leverage and are subject to pricing whims. Plan to be multi-model. This doesn’t mean starting with three integrations out the gate, it just means knowing who you’ll expand with and having an idea as to when you’ll do it and what the process will look like.
Learn how to route prompts to the right models. Not all models are created equal, and some are better at certain things than others. One of our portfolio companies has a wizard-like mastery of this. There are now many companies that act as an intermediary between applications and underlying LLMs, but I think if AI is a core part of your value proposition you need to master this yourself and can’t outsource it.
Find your Brandon. Someone inside your company needs to shoulder responsibility for owning your LLM strategy and executing the plan. Like all mission-critical things, accountability is everything.
Find a group of advisors who know how this all works. While LLMs feel reasonably new to a lot of people starting companies, there are experts out there who are excellent at helping assess which models best fit your needs, and understand how to think about competitive pricing and prompt routing. It’s probably a good idea to have a circle of 2-3 advisors who have some skin in the game that you can turn to with specific questions, both strategic and tactical.
Hone your business development chops. You’re going to be in a constant conversation with model providers asking for things: pricing, integrations, access to private betas, etc. These relationships matter. Invest in them.
Raise a little more money than you think you need as a buffer so you’re not always caught on your heels reacting to these costs. When things really work it means your costs will escalate faster than expected. Extra capital on your balance sheet may provide you with some peace of mind.
I’m sure there’s a lot more to add to this list, but it’s a start. This is likely the status quo for the next several years so it’s good for entrepreneurs to be aware of the current state of affairs and have a plan for it. Exciting times come with exciting challenges.
