The Era of Scaling Without Growing & The Meaning Economy
The emergence of AI-powered intent-driven tools will unleash a wave of small businesses like never before, driven by consumer demand for meaning.
Edition #20 of Implications.
This edition explores forecasts and implications around: (1) a new tech stack emerging that empowers small businesses to scale without growing their teams, (2) why the “meaning economy” may supplant the creator economy, (3) lessons learned in the trenches, and (4) some surprises at the end, as always.
If you’re new, here’s the rundown on what to expect. This monthly analysis is written for founders + investors I work with, colleagues, and a select group of subscribers. I aim for quality, density, and provocation vs. frequency and trendiness. We don’t cover news; we explore the implications of what’s happening. My goal is to ignite discussion, socialize edges that may someday become the center, and help all of us connect dots.
Check out recent analysis and archives here. Recent highlights getting the most discussion/scrutiny include “the law of displacement speed” (which explains why AI leaders get little sleep these days, the rise of disruptive interfaces and luxury software, and observations on abstraction and its many implications. Alright, lets dive in.
The Era of Scaling Without Growing
As smaller companies modernize using a new AI-native stack of technology, they no longer need to grow their team to scale their ambition. What a wild concept, but it will be increasingly true. Small teams will gain superpowers once limited to the world’s largest organizations — from how marketing is conducted and inventory is managed, to transcending the constraints of geography and language. As a result, small teams will increasingly be able to run — and compete with — big businesses. Notably, this trend will not only be powered by new AI tools that allow teams to stay small, but also by a shift in consumer preferences toward human-crafted brands and experiences (the magic that a business often compromises as it scales their team). Allow me to explain, and let’s explore some of the implications…
Every function of an organization will be refactored in ways that allow small teams to scale their reach and ambition without growing headcount proportionately. Within a few years, small business owners will be able to pose simple questions to their data using natural language. Their business tools will advise on pricing, optimization for taxes, converting leads to sales, and will offer various forms of “autopilot” for operating a business. Small teams will be able to make sense of data and gain enterprise-grade security that was never possible without large teams. For example, the small teams I meet using modern AI-infused marketing tools like Adobe Express don’t think about building a “marketing team,” they think about achieving intended outcomes. They want to drive more sales using marketing. If they could just “push a button,” they would. While most of these small businesses could never afford a marketing team of their own, new AI tools unlock these capabilities. We will see the same story emerge across other functions. It is exciting to imagine what small businesses will be capable of and whether this makes owning a small business more lucrative for more people. Will we see 1000x more small businesses that make $10M+ (or $100M+?) in revenue over the coming years? In the era of AI, the small get the advantages of the big.
A modern “intent-driven” AI tech stack will replace the classic functional-driven stack of tools. Rather than hire out teams of specialists for every function, companies will have the opportunity to purchase AI capabilities — often in the form of agent-based tools or “AI teammates” — that (or is it who?) automate parts of a process or entire workflows within individual functions. What does this mean? Instead of buying a sales tool and hiring a proportionate number of sales people, or a procurement tool with an ever-growing procurement department, you’ll engage specialized AI to optimize revenue, and specialized AI to source vendors and optimize spend. Rather than buy “seats,” you may pay personified AI agents or teammates for work completed or results. A few examples from those I am involved with: 11x develops “Alice,” an AI-powered sales development rep that leverages trillions of datapoints to help generate meetings for a salesforce. Thanks to Alice, sales people can focus more on the less scalable and more human process of building relationships with warm leads. Another example is Globality, where “Glo” helps you source, compare, and optimize the entire procurement process (and is now in place with some of the world’s largest enterprises). In both instances, the AI is oriented around intent rather than a function, technical specialists are freed up for more general and non-scalable work, and stakeholders beyond the function are able to engage with the work. Incumbents have an incredible opportunity to deliver intent-driven AI offerings within existing workflows — and are in trouble if they don’t. Here’s how I would juxtapose the old with the new:
The modern intent-driven AI tech stack will unleash a STBB “Small Team, Big Business” Wave. No doubt, we should expect massive growth in the number of small businesses started or refactored with revenues in the millions and healthy margins. Some of these businesses will sell software, and this great post by Anu Atluru on the rise of the Silicon Valley small business covers what we might expect (thanks Semil Shah for the reference). But most of these businesses will be refactored versions of previous era small businesses (and large businesses) with a modern AI intent-driven stack. We’ll see countless new STBBs and brands emerge that would have either (1) always been constrained by size, or (2) required massive capital to scale. I discussed this a bit with Sam Lessin on a recent “More or Less” podcast, and Sam made the point that the proliferation and indispensability of AI tools would likely yield a barbell outcome — where we’ll have massive growth of small businesses, and also a discrete set of “AI winner” trillion-dollar behemoths that power this transformation. One implication here is the marginalization of the middle. Will medium-size companies beleaguered by a large cost basis and a dependency on the AI winners get crushed as this future unfolds?
Consumer demand for smaller scale and human-crafted versions of everything will grow in an AI world. While the future of work might lend itself to small business creation, let’s ****not forget the demand side of the equation. We are going to crave artisanal and story-driven sources and experiences. Why? As every big company floods the zone of our attention with increasingly enticing marketing and cheaper and more personalized versions of everything, we — as consumers — will crave more scarce and authentically human experiences, often provided by a small business run by passionate people. In response, more artisanal-like and privately-owned businesses will emerge, powered by AI-driven tech stacks. Their products and their vision will be intensely personal, but the mechanics of their billing, marketing, etc. will be machine-driven. Quick side-note: Whenever I’m in Tokyo, I am blown away by the highly crafted experiences — from eight-seat restaurants and tiny bars to tiny manufacturers of home goods, owl cafes, and artisanal cotton candy shops. I often ponder, why aren’t there 1000x more of these experiences across all societies? In the US, are potential small business owners discouraged by the basic startup and operating costs, frictions of incorporation, and compressed margin profile of small businesses? Perhaps this, combined with a culture of insatiable desire for growth, make small businesses less desirable? But all this is changing. As functions like marketing, HR, accounting, and security become automated, will the value proposition of operating such a small business change? Especially as the labor force shifts out of bloated big companies, will more people become entrepreneurs?
What new businesses must be built to enable the “scaling without growing” era for small businesses? This new world we imagine will require new tools tailor made for STBBs, new ways of stitching these tools together, new ways of hiring and incentivizing top talent, and even new ways of incorporating or acquiring a small business. I am seeing a fascinating array of startups emerge, like:
Modern marketplaces for small businesses to be bought and sold — facilitating the transition of these businesses from non-tech-savvy founders to digital-native owners
Valuation services for SMBs, and new forms of dashboards that mount all sources of data and surface insights in natural language.
New platforms like ShareWillow, that help a business motivate employees by issuing “equity” in the form of compensatory units without the business owner actually having to sell any of the business — as well as enable a level of transparency that helps employees see the impact of every expense or incremental revenue on their own compensation
A new breed of “stack management tools” for small businesses that stitch all of these AI tools together, often using APIs that abstract that actual tools away from the end-user interface.
And, of course, myriad AI-infused content creation and marketing products from companies like Adobe as well as many startups, and the same for productivity from companies like Notion, Airtable, and Microsoft, among others.
No doubt, small companies will have the tools they need to scale their ambition without growing their teams.
Hit List: Top of Mind & Implications
The Meaning Economy. What we have long called the creator economy is evolving to become more of a “meaning economy,” where the creators and brands and experiences that engage us will do so through story, craft, and a deeper and more sophisticated sense of meaning. The creator economy was ultimately driven by content (enabled by ubiquitous access to content creation and distribution tools) and the power of social media to spread content for free. Fast forward, with the rise of AI-powered products that can automate and optimize the creation and distribution of content, humans will be inundated and overwhelmed. In a world of content abundance and zero-cost content creation, “meaning” will command a premium. What is meaning? It is the story, the purpose, the myths behind the creators themselves, and the brand value. When anything becomes commoditized or ubiquitous — whether it is shoes or a popular restaurant that becomes a chain — consumers tend to crave a more scarce and differentiated version in response. What makes something scarce and differentiated? Meaning. Of course, the drivers of this economy are the humans themselves — especially as their capacity is unlocked by all of the great AI tools that we are always talking about these days. As I often remind teams, the science of business is scaling, but the art of business is the things that don’t scale. In the meaning economy, the art part becomes increasingly critical. One major implication is the need for curation and “taste development” tools. As artists spend less time doing mundane repetitive stuff (thanks to AI), they’ll have more time to explore ideas and create better stories. This is something my teams and I are thinking a lot about these days.
Adaptability > Strategy. It’s provocative, but during times when “the law of displacement speed” (covered in edition #19) kicks in, how many great ideas fail because leaders aren’t willing to make the tough decision to change strategy fast enough? I am seeing many passionate founders and promising startups (and some larger product teams) struggle to change things up, as if such shifts in strategy are an admission of weakness rather than an indication of self-awareness and boldness. Companies are particularly proud of resilient strategies that stay consistent over time, but should consistency be the goal during a Cambrian explosion? Playbooks cannot be sacred cows. On the contrary, they expire quickly when you’re working at the edge of what’s next. Sunk cost fallacy is a fatal blow during periods like the current platform shift to AI. I am reminded of an old leadership lesson around the difference between technical challenges and adaptive challenges. Technical challenges have a solution, you just need to change your technology. In contrast, with adaptive challenges YOU have to change. The world needs more adaptive leaders today. Be very open to switching it up.
In an era where data rules, company distrust is the default. A week or so ago, our legal team pushed a routine “re-accept” to our TOU (Terms of Use), and the summary in the pop-up box customers received described poorly a change for legal compliance around scanning content on our servers for CSAM (child sexual abuse material) as “content moderation.” This description reasonably concerned customers, many of whom then read our company’s terms of use and focused in particular on a decade-old section about the limited licenses Adobe — and any other company that hosts user’s content in the cloud — requires to operate its services. This is the license “solely for the purposes of operating and improving software” that allows a product to make thumbnail versions of an image, save a rendition as a publicly accessible “share for review” weblink, publish to a Behance portfolio, etc. Despite the fact that our terms always stated “Adobe does not claim any ownership rights to your Content,” a wave of concern erupted among customers. Does Adobe train its Generative AI models on customer work? (No, we’ve always unequivocally stated that we don’t.) Does Adobe sell customer work or data? (Of course not.) And the list goes on. But this whole saga taught us some valuable lessons: (1) The terms of use that media and content companies use in the age of AI are overdue for an update (and our team has since redesigned and updated our TOU to address these modern-day customer concerns), (2) If you’re a company that stores customer content and data, you have a new responsibility to NOT just get the legal licenses you need to operate your product and features, but ALSO state what you will and won’t do with those limited licenses, and (3) In an era where “data is the new oil,” every company is distrusted by default — and you need to take active steps to show what you do and how you do it. This episode was an incredibly hard but helpful wake-up call for our team and prompted us to quickly publish a clarification blogpost followed by a more thorough update of our TOU that addresses the feedback and concerns shared by customers. Adobe now has one of the more modern and progressive terms of use that I have seen; it is creator-friendly, speaks directly to customer concerns beyond the legalese, and will hopefully inspire other content and media companies to follow suit. (And yes, I recognize it’s strange for a non-lawyer to be proud of a Terms of Use, but I am.)
The fair and altruistic center of mobs. The whole ordeal that I just articulated got started from a reasonable group of people asking very pointed but fair questions. I entered the fray because one of my greatest pet peeves is when executives of companies don’t use their own voice in real-time to address legitimate customer questions. I’ve always felt that leadership counts most when it is inconvenient and uncomfortable. At first, these exchanges were productive. However, as a mob mentality formed, I was fascinated by the increase in misinformation, abusive epithets, and completely wild and unrelated claims. I have grown tough skin over the years, and at this point have become a bit more of a sociological academic when it comes to social vitriol, asking questions like “what is at the root of this person’s anger?” So, I took the opportunity to observe how this dynamic transpired. First of all, I noticed the algorithms optimized for polarization. The more wild the comment, the more engagement it got, which served to further amplify the overall threads. The engaging (and enraging) fringe comments would rise the ranks within the threads, while more fair and factual responses immediately sank. We often ponder (and I’ve discussed in a previous edition of Implications) how conspiracy theories and extreme political stances now flow through the mainstream of modern social media. In a small microcosm, it was hard but informative to witness this happen.
Workflow is getting closer and closer to flow. In the whole space of creativity research, psychologist Mihaly Csikszentmihalyi coined the term “flow” for a highly focused mental state that is especially conducive to productive creativity. I’ve been thinking a lot lately about the impact of automation around every aspect of work — how it can remove points of friction and allow you to express whatever is in your mind’s eye without constraints or processes. In essence, with AI, humans will be able to reach the state of flow faster and stay in the state of flow longer. Recently, I came across this provocative post on Palladium that explores the potential obsolescence of knowledge work and the psychology of employment. The essay prompts all sorts of questions about a society with less “work” — at least among knowledge workers. Will people open more small businesses, as we explored above? Will human creativity have a renaissance of sorts? Will all the newfound time in our lives lead to enlightenment or depression (a lot of research shows that retirement can have negative consequences on happiness and self-worth)? All questions we must ponder for the era ahead.
Spelling mistakes will gain popularity as artifacts of humanity. In the last edition of implications, we explored “artifacts of humanity” that creators may incorporate into their work to flex the humanity behind the work. Ever since this edition, I’ve become extra cautious about sales emails and summary documents I receive that were likely composed with AI. I must say, it is refreshing to see a speling mistake every now and then - it shows the humanity.
Ideas, Missives & Mentions
And that’s a wrap for Implications #20 public edition. Now, here’s a set of ideas and worthwhile mentions (and stuff I want to keep out of web-scraper reach) intended for those I work with (free for founders in my portfolio, Adobe folks…ping me!) and a smaller group of subscribers. We’ll cover a few things that caught my eye and have stayed on my mind (including AI brainstorm partners, “last mover advantage,” concerns around context windows, and my evolving thesis for seed investing). Subscriptions go toward organizations I support including the Museum of Modern Art. Thanks again for following along, and to those who have reached out with ideas and feedback.
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