“I achieved the Holy Grail: I built software that builds software” | Ctech

At just 31, seemingly out of nowhere, Maor Shlomo became the poster child for the modern high-tech exit dream. As a solo entrepreneur with no investors, no employees, and no marketing or sales team, he built a product, launched it, and within six months sold the company to website-building giant Wix for $80 million.

Beyond the headline number, Shlomo’s story crystallizes the moment we’re in: artificial intelligence is reshaping how software gets made—and who gets to make it. His startup was itself built with AI, improved rapidly by AI, and ultimately enabled anyone to build applications using AI with almost no human involvement. In Shlomo’s own words, it was a shot at the “Holy Grail”: software that builds software.

The solo founder who moved like a team

What once demanded a coordinated effort across product, engineering, QA, DevOps, and go-to-market functions was compressed into the output of a single relentless builder augmented by AI. Without outside capital or a formal organization, Shlomo focused entirely on the core engine: an AI system capable of turning high-level intent into functioning applications. The result wasn’t a demo; it was a product compelling enough to be acquired at speed by a public company.

From prompt to product

The promise behind the technology is simple to state and hard to execute: describe what you want, and the system designs, codes, tests, and deploys it. In practice, that means:

• Understanding natural-language requirements and translating them into architecture and specifications.
• Generating front-end and back-end code, scaffolding databases and APIs, and wiring integrations.
• Running automated checks, iterating on failures, and packaging for deployment.
• Continuously refining the output as the user adjusts the intent.

The human becomes a product thinker and editor rather than a line-by-line coder. The system handles the repetitive scaffolding and boilerplate, and it learns quickly from feedback loops to improve robustness.

Why it matters

AI-native software creation reframes the economics and speed of building digital products:

• Velocity: Weeks of work can compress into days or hours, enabling rapid experimentation and iteration.
• Accessibility: Non-developers can prototype and even ship apps, expanding who can participate in software creation.
• Focus shift: Developers spend more time on product decisions, edge cases, and security rather than boilerplate.
• Cost structure: Early-stage companies can reach product-market validation with fewer resources.

For incumbents, these capabilities can turn platform users into creators, reduce time-to-market for new features, and unlock long-tail use cases that were previously uneconomical.

The acquisition signal

Wix’s purchase underscores a strategic shift: the next frontier of website and app creation is conversational and automated. By integrating AI that can architect and generate applications, a platform moves from template-based building to intent-based creation. It’s not only about making development easier; it’s about collapsing the entire build process into a guided dialogue where the platform does the heavy lifting.

Promises and pressure points

“Software that builds software” raises both excitement and hard questions:

• Quality and reliability: AI-generated code must be testable, maintainable, and observable at scale.
• Security: Guardrails, dependency hygiene, and secure defaults become non-negotiable.
• Ownership and compliance: Clarity on licensing, data usage, and provenance is essential.
• Human oversight: Even as AI takes on more of the stack, product sense and ethical judgment remain human strengths.

The winners will pair automation with strong governance and a clear developer experience, giving creators confidence to ship and iterate safely.

A new creative loop

The most profound shift may be cultural. Software development has long balanced craft and efficiency; AI tilts that balance toward vision and feedback. The fastest builders will be those who can articulate desired outcomes, evaluate trade-offs quickly, and guide the AI through precise prompts and constraints. In that world, “development” looks less like typing and more like product design, systems thinking, and decision-making.

What comes next

Shlomo’s exit is a milestone, not an endpoint. Expect rapid progress on multi-agent systems that plan, code, test, and monitor collaboratively; tighter integrations with deployment platforms; and richer tools for auditing and editing AI-generated code. The platforms that thrive will make creation feel conversational while keeping power users firmly in control.

If the last decade was about no-code and low-code, the next one will be about intent-to-production. The Holy Grail once sounded like a dream. This deal suggests it’s beginning to look like a product.