The aspiration to only raise a single round of funding, while still building a great company, has been around for a long time. But until the viability of AI-assisted and AI-led everything, it was virtually never achieved. Instead, it was one of those bold claims some founders made before realizing how almost impossible it was to achieve. This article brings the one-and-done concept into the age of AI, examines different strategies for achieving it, and explores the implications that might result.
Why is One-and-Done Now Possible?
Let’s start with the fundamental reasons why startups need to raise funding in the first place. They either want the funding or they need the funding. Historically, almost all startups raised funding because they needed it. Not doing so would otherwise drain their bank account to a zero balance, causing the founders and their team to pack up their toys and go home.
Multiple rounds of funding were typically required, before reaching a point of self-sustainability. The earliest rounds of funding were used to build the product and get it launched. The next rounds of funding were used to gain customers and grow enough to become self-sustaining. The exact timing and amounts of funding varied greatly based on the type of product being built – software, hardware, biotech, etc.
For a software startup, a very large majority of the funding went towards staffing. For a hardware or deep tech startup, still a lot went towards staffing, but funding was also needed for specialty equipment, multiple prototype iterations, clinical trials, substantial cloud compute infrastructure, and other things.
In the age of AI, things change dramatically as it relates to the personnel-related costs. The founder of a software startup can build the first prototype, and even the v1.0 product, by themselves. After that, some technical experts will probably be needed to achieve scalability and hardening, but not very many.
Founders will be able to rapidly experiment, and course correct (pivot), without wasting much time or capital. This means the time-to-launch will be greatly accelerated. After launch, AI-assisted and AI-led customer acquisition campaigns mean far less staff and, therefore, much less needed capital.
Surely you see where I’m going with this. Faster time to self-sustainability with far less staff means one round of funding, timed correctly, could be all that’s needed for an ever-increasing mix of software startups. There will be a day when a founder of a software startup that had to raise two or three funding rounds will be consoled by their counterparts.
Of course, I’m using the past tense with many of my statements, as if this has already happened. But the AI-assistance and AI-led trend is starting to take hold and will increasingly make its impact over the remainder of this decade. Software startups with $20M in annual revenue and with 10 or fewer employees will be commonplace by the end of the decade.
The Best Time to Raise the Single Funding Round
Bad things won’t happen to startups that end up needing two or more funding rounds. But how nice will it be when founders that start with 30-50% equity ownership can exit with 20-40%? This requires smart timing for the single funding round. Raising it too early increases the odds of needing another funding round in the future. Raising it too late might slow the time to $1M or $10M in revenue, giving other startups a chance to slingshot into a leadership position.
It seems to me that bootstrapping through the prototype phase is the obvious right strategy. Doing so through the product launch and acquisition of the first paying customers will become increasingly practical and, therefore, a sound strategy.
The single funding round should be timed when it will provide the best bang for the buck. Below is a list of some priorities that could help determine that timing:
- Hiring some badass ninja technical types to optimize the software architecture or implement some really challenging capabilities.
- Paying some legal and accounting professionals to double-check the way things were previously done and help get the company into a “by the book” mode.
- Paying some marketing ninjas to dramatically increase awareness.
- Implementing AI-native software tools for every company function.
All the above-mentioned personnel, whether they’re employees, contractors, or service providers, will undoubtedly use AI for a substantial amount of their work. That just makes them hugely efficient and effective, which means less costly overall for the desired benefit.
It seems to me that most software startups will choose to raise their single funding round after achieving some initial repeatability in their customer acquisition strategy, but before it is mostly optimized. Basically, after achieving initial product-market fit.
I’m sure there will be other indicators of optimal timing. But at the time of writing this article, this future is still just a little too vague for me. I’ll probably come back each year or so to add my thoughts in that regard.
Who Gets Left Out?
“Left out” in this context just means one round of funding won’t be sufficient to reach self-sustainability. I’m mostly referring to hardware and deep tech startups that need to do a lot more than put their hands on the keyboard to build their product. But all those startups also have software as part of their solution and all of them engage in customer acquisition and growth strategies after their product is launched. They will benefit greatly from the age of AI in ways that dramatically reduce their funding requirements.
I predict that over the course of several years, startups that currently must raise $50M+ of lifetime funding will only need 30-50% of today’s amount. I can’t substantiate that or break it down into its component parts. But I believe it will happen.
Key Enablers
While AI’s foundational role is clear, a deeper dive into its specific applications across core business functions reveals just how transformative it will be:
- Software Development – Tell the AI what you want built or what features you want added, and not only is the source code generated, but also debugged, tested, and deployed to your production cloud instance.
- Competitive Analysis – This new world will enable new competitors to appear out of nowhere. AI market scouts will detect them, analyze their offerings, and provide both comparative analysis and recommendations for your action. Those recommendations will automatically get fed into your software development AI, which will immediately whip up prototype concepts of each product-related action for your review and decision.
- Marketing – Tell the AI what types of sales leads you’re pursuing and the amount of money you have to spend and it will not only secure them, but will first do various small tests to optimize the combination of quantity and quality of leads.
- Sales – The AI automatically listens to every sales call and provides both a scorecard and specific recommendations on improvement. In time, you won’t even need human SDRs or sales reps because voice-enabled AI agents will do it all for you.
- Finance – Closing the books and updating your financial forecasts is easy. Your AI systems and agents not only do it for you, but are ready for any questions and what-if scenarios you want to throw at it.
These pervasive AI capabilities, and several more, will fundamentally redefine the operational efficiency and capital needs of a startup, creating the fertile ground for the one-and-done unicorn.
Where is the Promised Unicorn?
To achieve the coveted $1B+ unicorn valuation, most software startups need annual revenue in the range of $100M with an exciting track record of growth. Achieving profitability is sometimes a criteria and sometimes not, depending on which end of the pendulum swing the venture capital and public stock markets happen to be in at the time.
In this new world, a $50M software startup with hyper-growth (versus just “exciting”) and high profitability might easily be rewarded with a unicorn valuation. Just imagine such a startup that is tripling revenue each year and throwing off 60% net profit. Wow!
But the very premise of valuation might shift under this model. If the founders and executives are earning huge annual compensation and don’t need to raise more funding or pursue an exit, why is a valuation even needed? I guess there will be some reasons like M&A or IPO, but not the ones that caused the “unicorn” moniker to become so well-known – Series D/E/F funding rounds.
Implications for the Startup World
The number of software startups will skyrocket compared to today. The number of teenage founders will skyrocket. After all, what does a founder have to lose by making a run at the idea they’ve always wanted to pursue? By the time they reach the point of raising their single funding round, they’ll already have a shipping product and paying customers.
Every startup of every type will get lots more swings at the ball. Pivots will be far less punishing, because they can occur quickly and with less wasted funding. In fact, many startups will simultaneously build two or more variations of their product at the same time, just because they can. Or maybe they’ll build a single product, but launch it into multiple markets (industries, target audiences, etc) at the same time, just because they can.
As I mentioned before, lots of software startups will reach $20M in annual revenue with fewer than 10 employees. In fact, such startups that need 30+ employees to reach that milestone will be asked what went wrong. Startups with $100M and 10 employees will also happen by the end of the decade. Imagine how hugely profitable they will be!
I believe that having far fewer investors will result in much less pressure to exit via acquisition or IPO. The typical early-stage funding instruments used with angels and VC’s will shift to revenue or profit sharing, until the investor has been paid back some reasonable return. Instead of the 10X return target we often hear about in the venture investing world, a 3-5X payback could become acceptable. Much of that is because the revenue/profit sharing payments will start soon after investment, rather than having to wait 6-10 years for an exit. This changes the risk-reward dynamic quite substantially.
After the one-and-done investors have been paid off, I believe many founders will choose to reward themselves and the executives they hire with significant profit-sharing payments. Their $300K+ salary will be met with double to triple that amount in profit sharing, and maybe much more. Over a 10-year period, they can still make millions of dollars, just in a different way than waiting for an acquisition exit. If what they worked on for 5-8 years becomes obsolete due to something new and innovative, no problem. They’ll shut it down after having already made millions of dollars along the way.
The Rise of Unconventional Startup Ecosystems
The new era of one-and-done funding for software startups should give aspiring startup ecosystems a far better chance of success. Traditionally, the lack of early-stage venture capital has been a huge impediment. Those same ecosystems will experience many more startups reaching the point of product-market fit.
As the startups are ready for their first-and-only funding round, this new financial dynamic makes it more reasonable for high-net-worth individuals in these aspiring ecosystems to fund startups. If investment returns are more based on lower-risk profit and revenue sharing rather than a high-risk and distant exit, non-venture style investors will be far more willing to engage. Every community has high-net-worth individuals. But many don’t have tech-oriented angel investors. Investing in a tech startup will have more similarities to investing in real estate or a traditional small business. Game changer!
Funding isn’t the only fundamental need of a startup. They’ll still need to get good at securing customers and recruiting high-caliber talent. And they’ll still benefit greatly from sage advice and being part of a thriving community of other founders. But all that just means one-and-done funding won’t make building a great company easy. It will just make it easier. Just ask any founder in a second or third-tier US city or in a foreign country where entrepreneurship isn’t already embedded in the culture.
In this new era, AI-assisted tools for customer acquisition and remote talent scouting also become a great equalizer. A startup in a less-known city no longer needs a local network of marketers or a huge team of salespeople; AI-led campaigns can reach prospects anywhere from day one. Similarly, AI-driven platforms can help find and vet high-caliber remote talent, allowing a lean team to hire the best from anywhere, not just their immediate geographical area.
The Founder Persona for One-and-Done
Many of the traditional personas of successful entrepreneurs (read my related article titled “The 8 Personas of Successful Entrepreneurs”) will remain viable, as will proven leadership talents. But certain strengths and areas of focus will be especially rewarded in this new world.
Disciplined & Frugal: The founder must excel at capital allocation and avoiding unnecessary spending, particularly during the bootstrapping phase.
Problem-Focused: Possessing a deep understanding of the problem being solved and the necessary solution, allowing them to execute on the product vision themselves initially.
Adaptable/Resilient: Able to pivot quickly with minimal emotional turmoil, reacting to market feedback efficiently.
Experimentation: In this new “anything-is-possible quickly” world, a strong aptitude for conducting regular small-scale experiments will be hugely valuable for rapid iteration.
Questioning: One of the most valuable skills in the age of AI will be the ability to ask the right set of nested questions to guide AI systems towards the ideal strategy or outcome.
Challenges and Pitfalls of the One-and-Done Model
All of this sounds straightforward and amazing, right? Well, there’s no free lunch. Even this amazing new world will come with its own challenges and punches to the face. After all, you can’t really be a startup founder without numerous punches to the face, over time – right? Following are some challenges and pitfalls I can predict, so that you can hopefully prepared and adjust accordingly:
Unexpected Capital Needs: After your single funding round, and anticipating no more needed, you might rightly stop your investor discovery and investor networking efforts. After all, you don’t need future investors. But what happens if you end up needing to raise another funding round? You’d be caught very flat-footed and have to start from scratch.
- Remedy: Don’t shut off your investor discovery and investor networking efforts until you’re fairly certain the coast is clear on sustainability.
Competitive Landscape: If spinning up a viable startup only requires a few weeks of effort from a couple of crazy founders that have a different approach to solving the same problem you’re solving, you’re going to be looking over your shoulder all of the time.
- Remedy: Never assume you’ve got a lock on your market. Instead, adopt the principles of Andy Grove’s book “Only the Paranoid Survive”.
Lack of VC Pressure and Guidance: The best venture capitalists push and challenge the CEOs of their portfolio companies. Even if they’re mostly doing it to help ensure a significant return on investment, it better helps guide the CEO to building a great company that changes the world. If you don’t need VCs, who is going to push and challenge you in the same way?
- Remedy: Don’t just assume you’ll do it for yourself. Instead, bring on highly-trusted advisors and coaches that are compensated in ways that motivate them to really challenge and test you, every step of the way.
Implications for the Venture Capital Industry
I’ve already described why most software startups won’t need to raise millions in funding from VC’s. Hardware and deep tech startups will still need to raise tens or hundreds of millions of dollars before they can become self-sustaining. That means most venture funds will need to shift in that direction to avoid becoming obsolete. But getting good at investing in hardware and deep tech is way different than software. That means many will fail and not be able to raise their next fund, resulting in far fewer venture funds than today.
Additionally, as AI speeds the time to market and dramatically reduces the operational staff that many hardware and deep tech startups need to grow, the VC industry will need to further adjust. Large funds with $500M or more in assets under management will need to pursue the really big deep tech opportunities. Specifically, the ones that will still need to raise hundreds of millions, or even billions, in funding. Space and aerospace, next-generation energy production, biotech, and advanced materials are a few examples.
These shifts will cause significant competition for the limited venture talent and due diligence advisors that understand certain segments of deep tech well. Before they can refine their strategy and find this talent, and as the pressure to shift their investment strategy begins, a lot of “dumb money” will slosh around.
Venture capital funds can’t just sit on the sidelines for a year while they adjust their strategy and tactics. Rather, they need to deploy the capital they raised within a 2-4 year period. The combination of these factors, combined with too many funds as compared to the amounts actually needed in the market, could cause valuations to get a little crazy – until the eventual fallout and cleansing period.
Summary
In an unprecedented shift, the “one-and-done” funding strategy for startups is no longer a founder’s fantasy, but rather a tangible reality, primarily catalyzed by the pervasive capabilities of AI. This article has demonstrated how AI-assisted and AI-led operations drastically reduce personnel costs and accelerate both time to product-market fit and profitability – from code generation and competitive intelligence to automated marketing, sales, and financial management.
This new paradigm redefines the path to unicorn status, where extreme capital efficiency and high profitability can yield multi-billion dollar valuations, even with much leaner teams and lower traditional revenue milestones. Such a model encourages bootstrapping through initial stages, with a single, well-timed funding round injected precisely where it delivers maximum impact. While hardware and deep tech ventures will still require multiple funding rounds, AI will also significantly mitigate their amounts.
The implications are profound: a surge in new software startups and younger founders, unprecedented operational profitability, and a fundamental reshaping of investor-founder dynamics towards revenue and profit-sharing models. This shift will challenge the traditional venture capital landscape, forcing them to pivot towards capital-intensive deep tech or else risk obsolescence.
Ultimately, the “one-and-done” era empowers a new breed of disciplined, adaptable, and AI-savvy founders to build highly valuable companies, offering both personal wealth and a transformative impact on the startup world, with far greater control and less reliance on external fundraising.