Jason Martin @JasonKMartin

@martymadrid Yes! Throw in ChatGPT too.. can’t forget the SmarterChild bot 😂

@ColinGardiner Nothing better!

@msuster Just called the number today, super impressed! This tech's going to kickstart a ton of new vertical specific tools.

AI Agents have the potential to democratize knowledge work in the same way that SaaS democratized software. And as we've seen in the past couple of decades with software, every time you make a service cheaper and more available, you dramatically increase the size of the total addressable market.  Let's take, for instance, what happened in the early days of SaaS. The biggest mistake that most people and investors made was looking at the market sizes of traditional on-prem software to see how big the market could be for this new crop of companies. In fact, some even felt the markets would actually be *smaller* because the software may be cheaper to run for an enterprise. All these theories were wrong, by an order of magnitude. What we actually saw happen was not that SaaS initially replaced or went after traditional incumbent software products for existing customers, but instead, the biggest early customers were actually smaller businesses or teams in large enterprises that previously didn't have access to traditional on-prem enterprise software. On-prem software, from CRM systems to ERP platforms, were notoriously expensive, hard to manage, and required significant IT teams and partners to operate. This meant only the largest enterprises in the world could actually implement best-in-class technology for their enterprise.   Enter SaaS. Starting with Salesforce and NetSuite, for the first time small businesses had access to effectively the same tech stack that a large enterprise had. This led to a gold rush of software. AWS ushered in an era where a one person startup could build an app and scale it without ever visiting a datacenter. Box let businesses of all sizes manage documents and content securely. Shopify let anyone have access to a powerful ecommerce system, leading to a huge boom in direct-to-consumer product companies and other retailers being able to sell successfully online. Stripe gave any developer a full payment stack. All of these new services --and thousands more-- led to a 10Xing (or more) the size of traditional markets by serving customers that previously didn't have access to these types of tools. Now, if you extrapolate out what we're seeing in the earliest days of AI, the same dynamic could hold true for AI Agents. While large enterprises have traditionally had access to nearly every specialized form talent or an abundance of labor, the vast majority of businesses don't have this same luxury. For most small startups just getting going, they often don't have the resources to do outbound sales, full customer support, specialized legal work, and so on. And as a startup scales, you're constantly making resource trade-offs that are less driven by what's best for the business, but instead driven by how much capital you have. In the future, by making the barrier to entry to getting knowledge work done as simple as a website signup or API call, we will likely see a massive increase in usage of “services” that previously were near-impossible to access easily. And what's amazing is the vast majority of the usage of these AI Agents will likely come from previous areas of "non-consumption". That is to say, these will be customers that would not have spent anything on similar labor categories in a pre-AI world. Now, of course, in many cases, AI will start out worse on some dimensions than traditional forms of solving these problems, but as tooling gets better, models get cheaper and higher quality, we know the capabilities will improve over time dramatically. We're in only the very beginning of this new era of AI-driven work, but the scale of the opportunity and the market will be massive.

We're at an interesting time in AI apps where viral consumer growth leads to enterprise adoption. The most popular consumer products (largely creative tools / productivity, think ElevenLabs, Midjourney, HeyGen) get adopted by individuals in companies and pulled upmarket. As a result, you can build a sizable enterprise business with no sales team or outbound marketing - and either entirely self-serve or via "light touch" business plans. IMO, this is one of the reasons we're seeing AI companies with faster revenue growth than ever before - there's massive consumer adoption and large enterprise contracts layer on + provide a sticky revenue base.

AI will make expertise near free. Who will build the first billion $ revenue company with <100 employees with near free programmers/doctors/advisors/etc etc? Worth attempting!! The power of ideas powered by entrepreneurial energy will be hugely multiplied as the scarce resource

Anthony Edwards is expected to debut the low-top edition of his signature @adidasHoops AE 1s during the NBA Playoffs. Edwards’ 1st signature shoe has become one of the industry’s best-selling basketball shoes since launching in December.

great to see everyone at AI rabbithole event today! as promised, here's my deck with abbreviated narrative. (video was recorded, will share when available)

What do marketplaces look like in the age of AI? Some will grow, some will shrink, and some will disappear. It's a new era for the marketplace model! My take on who will be impacted - and how 👇

@garyvee @VeeFriendsCards @fanaticslive The @VeeFriendsCards community has a free home waiting for them on @NextGemApp ❤️ 📩DM!

Whenever a new enabling technology appears, it allows new marketplaces to arise that couldn't exist before. SEO + Search: Trulia, Zillow, Indeed Mobile: Uber + Lyft AI will have the same effect The potential of AI-first marketplaces here + below: nfx.com/post/ai-first-…

LeBron James Nameplate on NextGem! 🔥 #KingJames #LBJ #Lakers 🏀

It’s impossible to look at the big apps today and learn anything about how to launch your new app. The smartest founders dig in to understand bootstrapping stories as they craft their own. I was recently asked about musical.ly / Tiktok and shared:

@ColinGardiner Ok ok — where’s this truck located?

@ColinGardiner We made it really easy to check price comps. Here’s a quick vid of how to do it on @NextGemApp.

Exploring the 2nd order effects of generative AI in marketing and martech chiefmartec.com/2023/04/explor… #martech

AI apps Context: The AI stack has 4 layers. From bottom to top, infrastructure (eg Nvidia), foundational models (eg GPT), AI tooling (eg Hugging Face) and Apps (eg Harvey for legal). There are many sub-buckets within each layer, but for the purposes of the post below, I’m talking about the highest layer (apps). There will be mega winners in both horizontal and vertical AI apps. I include functional (sales / marketing / etc) AI apps within the horizontal bucket. Vertical here refers to an industry focus (eg healthcare, legal, etc) Early stage horizontal AI apps face competition from other startups due to relatively low barriers of entry (eg half a dozen strong products in the sales tooling space) as well the looming threat of incumbents making it into a feature of their products. Results in horizontal AI apps likely facing an extended period of intense competiton and consolidation before we can pronounce a winner. On the other hand, vertical AI apps don’t face exceptional incumbents, need more domain expertise leading to fewer startup competitors, have a unique data advantage and focused GTM, leading to higher chance of winner take most. Even seemingly narrow niches of a vertical are absolutely massive opportunities. Easier to justify an early stage investment.

@michaelpschulte Check out the material from @tdavidson — he has been teaching it for a while and has a variety of templates, webinars, etc.

Big Ideas 2023 is out! Here is a quick summary of the Digital Consumer section. Thread ⬇️🧵 Also, a massive shout-out to @andrewkimARK and the entire ARK team for all the hard work. ark-invest.com/big-ideas-2023…

@andruyeung 👋