AI and no-code tools are fueling a new solo builder economy – where individual creators launch and scale products faster than traditional startups. Freed from VC dependence, these creators use lean tech stacks, automation, and AI assistants to build profitable micro-SaaS ventures. As platforms like Microns.io show, this movement is redefining what it means to found, grow, and sell a startup, transforming the concept of a “team” into a dynamic ecosystem of tools, freelancers, and AI-driven efficiency.
In the new age of AI and No-Code, a quiet revolution is reshaping entrepreneurship. Small, nimble solo builders are shipping products faster than funded startups, using lean tech stacks and limitless curiosity.
Take Jake Tan, the founder of CraftMyPDF, as a prime example. While working on a freelance project, he was frustrated by the lack of a user-friendly PDF template editor in existing services. He then built and launched his own no-code platform, featuring a drag-and-drop editor. Starting with just $800, Jake grew his solo-built micro-SaaS to $180K/year in revenue, proving that a single builder can rapidly deliver a high-value, profitable solution by filling a specific market gap.
I spoke with Maksym Kunytskyi — CTO at Microns.io, an online marketplace for buying and selling micro-startups — to dive deep into the tectonic shift occurring at the intersection of AI and no-code, exploring how solo builders are leveraging these technologies to create a new economy that bypasses traditional VC routes and rapidly delivers market-ready, revenue-generating products.
Defining the New Economy and its Enablers
Maksym, how do you define the new economy emerging around AI and no-code tools? In your view, what are the core enablers that allow solo builders—often without traditional funding or team structure—to ship market-ready, profitable products faster than conventional startup teams?
For me, the new economy around AI and no-code is the shadow economy of solo builders, freelancers, or founders who don’t build a full-fledged team and don’t raise money from VC and angel investors. Yet, they bring their product, startup, or innovative solution to the final user—increasing its valuation and ultimately selling it. It’s “shadow” not because it’s hidden or illegal, but because it develops outside the traditional startup playbook.
The core enablers are the new technologies and innovative combinations of the tech stack that make solo implementation possible. Accessible infrastructure for the backend, frontend, and database, as well as AI assistants and social media—all of these components can work together to deliver results for a solo builder. And, of course, a healthy dose of entrepreneurial enthusiasm.
Ethics, Regulation, and the “Grey Zone”
In a broader sense, though, the “shadow economy” isn’t just about efficiency; it also raises questions about regulatory evasion, lack of ethics, or transparency. Do you believe this economy is becoming a “grey zone” for experimentation without rules?
I see this more as a new stage in the development of the digital economy, where technology moves faster than the regulators. The vast majority of solo builders operate completely legally, paying taxes, processing payments through established companies, and cooperating with official platforms like Stripe or PayPal.
Yes, there’s currently a lack of established rules regarding AI content, authorship, and data transparency, but this is natural for an industry in its early stages. What seems like a “shadow” today will become the norm tomorrow, with clear frameworks, ethical standards, and reasonable regulation. I view it as an experimental space where a new wave of entrepreneurship is forming.
Trade-offs: Speed vs. Scalability
Speed is a big advantage for solo builders. What trade-offs do you increasingly observe—particularly around long-term quality, scalability, architecture, and maintenance—when a venture is built primarily with no-code/AI stacks?
No-code and AI enable a quick launch, but if the logic is built chaotically and messily, problems arise later. I often consult on products where the business logic is “smeared” across many services, and no one knows where to update what. The simple solution here is documentation.
Trade-offs also depend heavily on the developer’s background. Sometimes, developers spend less time on the frontend or the application’s usability, and others on marketing planning or basic security. For instance, if a founder has always been a frontend developer, they’ll quickly assemble a complete project but will always prioritize the backend over the frontend.
Innovation vs. Simple Wrappers
Many AI/No-Code products appear to be just wrappers for ChatGPT or API plugins. How do you distinguish genuine innovation from simply good marketing based on a readily available API?
Innovation isn’t about the tech stack; it’s about creating new value. If it simply duplicates the basic function of a large model, it’s not a breakthrough.
However, when a product deeply understands the user’s context, solves a specific pain point, and automates a real process—even an open API can serve as the basis for something new.
The biggest added value, in my opinion, appears when the AI has access to specific data—such as internal knowledge bases or documentation. This allows it to “think” within the boundaries of a particular product or domain. A good example is AI assistants within software that replace support staff; they are familiar with all the product’s nuances and provide accurate, contextual answers. True innovation here lies in the ability to integrate artificial intelligence seamlessly into the user experience.
Shifting the Concept of a “Team”
If one individual can handle development, marketing, operations, and so on via AI and no-code tools, how does that shift the relevance of traditional small startup teams (e.g., 2-5 person VC-backed teams) versus single-founder micro-SaaS/marketplace ventures?
I believe the very concept of a “team” is changing. With an AI assistant, one person can have the productivity of several. Research, analytics, and content creation are significantly accelerated. However, cooperation with professionals doesn’t disappear—it just becomes more flexible.
Instead of employing full-time staff, the founder will engage experts on a point-by-point basis—a designer and a marketer for consultation or a specific launch, or an engineer for a particular project. The classic 3-to-5-person startup team evolves into a fluid ecosystem of freelancers and tools.
The “Build to Flip” Trend
So, we move from a permanent, salaried team to a dynamic ecosystem of freelancers and tools. Are we also moving from “build to scale” to “build to flip”—and do we risk losing the next big ideas by chasing quick sales?
Actually, the opposite. The more products are created, the greater the chance of a breakthrough idea emerging. I prefer the “start building, figure it out along the way” philosophy.
Unfortunately, I’ve seen several startups from friends and acquaintances that started with big ideas and never launched. If low/no-code had been this accessible a few years ago, many of them would’ve shipped something real within a week.
The Microns.io Perspective
From your vantage via Microns.io, how much has the share of AI- or no-code-centric products grown over the last 12-18 months, and what effect (if any) has this had on median listing price or deal multiples?
I can say unequivocally: the tech stack no longer determines valuation for sub-$1 million startups. Projects built on low/no-code with AI solutions are listed at vastly different prices (ranging from $1K to $100K), as are those on a more traditional development stack. It has long ceased to be a criterion for valuation. We’ll need more time to see clear pricing trends.
For buyers on the platform, how do AI or no-code technologies influence valuation and due diligence? What red flags or risk areas show up most?
Due diligence for low-code/no-code/AI solutions is conceptually no different from other projects. Buyers look at verified customer and revenue data, analyze product-market fit, niche, competitors, and pricing models. The technical stack analysis boils down to whether the buyer can independently support the project after the sale.
If a project utilizes AI, buyers check if the solution is genuinely functional and customized. If it’s just a wrapper—simply redirecting a request to a second LLM model—the value will definitely decrease.
Buyers also analyze the churn rate. In the AI startup sector, this metric often reaches 50% within two months. Many founders realize this problem, so one of the most effective solutions is to switch to sales for B2B / enterprise clients.
Vendor lock-in also matters. If your product relies on five to seven obscure platforms, migration can be a painful process. Attention must be paid to the vendors themselves—many companies today are confidently holding their ground and are here to stay, including my favorites: Webflow and Xano. If the stack is built with no-name vendors, the risks must be weighed carefully.
Finally, a patent or unique, custom AI technology that genuinely solves a specific problem positively influences the multiplier.
Which specific AI frameworks or no-code platforms appear to provide the strongest foundations for solo-built businesses that can be sold for a good value?
It depends on the product type. Webflow, Bubble, and Softr are used for frontend work. Xano, Firebase, and Airtable for the backend. Zapier, Make, and n8n are great options if a quick app connection is needed. Niche platforms include Beehiiv, Gumroad, and Substack. If a project has AI, the undisputed leader among vendors is OpenAI.
Are many solopreneurs aiming for a quicker, profitable exit via marketplaces like Microns, rather than the traditional VC route? How does that aim shape the typical lifecycle, features, growth path, or product-architecture of their venture?
If a solo builder creates a product, it doesn’t automatically mean they plan to sell it immediately. Reasons vary: lack of time to support it, planning the next solution, or simply fatigue.
Undoubtedly, a segment of people creates products specifically for sale. In this case, they choose products that are trending and visible.
As AI is the current trend, many developers are now mass-producing products focused on the AI sector. Such developers work using the pattern: Create -> Validate -> Earn -> Sell -> Start New Development. This leads to simpler architecture, minimalistic design, and focused functionality.
But these projects are more about craftsmanship than the pursuit of massive scale.
What documentation do you expect in a healthy data room for such assets?
At Microns, we focus on verifying revenue, traffic analytics, and category fit.
Technical audits are the buyer’s responsibility, but the product must be fully functional at the time of listing. That’s our non-negotiable standard.
Competitive Moats and the Future
In a low-barrier-to-entry world, what critical advice would you give solo builders for creating a defensible competitive moat?
I’d focus on three things:
- Deep Product Understanding and Vision: Functionality can be copied, but experience and implemented ideas cannot.
- The Right Stack: Choose a stack that minimizes development limitations for scaling and future development. My favorites are Webflow and Xano.
- Building a Community: A community provides a wealth of useful ideas and may even suggest necessary features.
What influence is this rising solo-builder economy having on early-stage venture capital/angel investing? Are VCs shifting behavior?
The market is gradually becoming saturated with small but viable projects, each with an audience, stable revenue, and proven product value. If the domain of buying startups was previously only accessible to large Private Equity and Venture Capital funds, today the barrier to entry is significantly lower—and a new class of investors is forming on this backdrop: micro-PE.
They work with smaller checks but with the same logic as large funds: they buy, optimize, scale, and monetize small but already profitable SaaS and AI projects. Instead of funding expensive experiments, these investors choose working businesses with verified metrics that can be integrated into their ecosystem or expanded into a portfolio.
Looking ahead, what do you think is the next major technological enabler or trend you expect will further accelerate the solo-builder economy and trigger a new wave of valuable acquisitions?
The true turning point will occur when low/no-code becomes an industry standard among professional developers — when the market is filled with flexible, scalable, and reliable platforms that prove speed no longer comes at the cost of quality or control. At that stage, developers will choose low/no-code solutions not because they lack resources, but because they offer unmatched efficiency.
And finally: if Low/No-Code becomes the professional standard, what will the solo builder evolve into—a universal engineer or an “AI director” who manages agents, pipelines, and datasets?
I believe development is about professionals who quickly master new tools, think systematically, and have a broad overview of innovations. “AI director” sounds grand—simply writing a prompt is not enough. You need to clearly formulate goals, format requirements, quality criteria, and know how to assemble these into reliable pipelines.
The role of the solo builder will evolve into a product-oriented engineer who manages agents, data, and integrations, and is also responsible for quality metrics, execution economics, and compliance. System design, data work, and integrations will remain necessary skills. Only the “product sense” will be added. Such individuals will make low-code and no-code a true professional standard.
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