Anysphere Automated the First Principles of Software. What’s Next?

Anysphere’s Cursor AI coding assistant hit a million users this April, reportedly without spending a cent on marketing, and all through developer word of mouth. 

Even so, it has been more than a “trendy” product. Cursor succeeded because it met developers where their pain points live, helping them avoid the long hours lost to boilerplate debugging, and navigating complex codebases. 

But with a $9.9 billion valuation, $500 million in annual revenue, and half of the Fortune 500 on board, the company now faces a different kind of question: Can they sustain their growth, especially with a product that could essentially build itself, and evolve further? 

Explaining their Growth Rate

Anysphere’s ascent is staggering. In just three years, the MIT-founded startup grew from a dorm-room idea into the fastest-growing software company in history, reaching $100 million ARR in 14 months and $500 million shortly after. It pulled this off with fewer than 20 employees at launch and no marketing budget.

What sets it apart is a laser focus on their users. CEO Michael Truell attributes Cursor’s success to the value it provides, speeding up development, reducing cognitive load, and letting coders “vibe code” with natural language prompts instead of typing syntax line by line. 

The editor, built atop Visual Studio Code, feels familiar but layers in intelligent features that learn from your behavior, correct errors, and even act on full-project instructions in its “Agent Mode.”

Automating First Principles

The value of Cursor lies in how deeply it understands the act of coding. It’s able to analyze an entire codebase, implement project-wide changes, explain what’s happening, and debug errors with human-level intuition.

In short, it has begun to automate the first principles of software development: understanding logic, architecture, dependencies, and intent. Tools like this shift software engineering from typing and troubleshooting into high-level problem-solving and iteration, which further explains the demand it has.

Developers have already started using Cursor to build Cursor-like tools, automating even more of the coding process. In a sense, Cursor is a system that can evolve itself, with a little developer input.

But, There is Little Barrier to Competition

Cursor’s rise has drawn interest from OpenAI, Amazon (which is testing it over its own tools), and even Google CEO Sundar Pichai, who said he’s been “vibe coding” with Cursor to build personal web apps. But with rapid success come real challenges. 

A customer support bot recently went rogue, fabricating policies and sending users into a tailspin. It was a reminder that while Cursor automates development, it’s not immune to the risks of hallucination and the fragile trust humans place in machines pretending to be people.

Plus, GitHub Copilot, Windsurf, and Qodo are quickly closing the feature gap, while Microsoft and Google pour billions into their own AI IDEs. For data scientists, GitHub Copilot remains the preferred tool, especially in Jupyter environments. Switching costs for Cursor exist, but they’re not yet high enough to ensure long-term lock-in.

Counterpositioning as a Potential Strategic Moat

As a truly AI-first IDE, it doesn’t carry the baggage of legacy tooling. This counterpositioning lets Cursor outmaneuver incumbents who must retrofit AI into decades-old paradigms (See: Microsoft, Amazon).

Still, Cursor has few paths to structurally distinguish itself. Its brand isn’t yet strong enough to command loyalty, and it lacks exclusive data or a true cornered resource. Its clearest shot at long-term defensibility lies in evolving into a collaborative platform, where teams, not just individuals, build, share, and refine code using AI. If that happens, network effects and switching costs will deepen.

So What’s Next?

The next frontier is building the intelligence, structure, and ecosystem that lets people solve higher-order problems without thinking about code at all.

Anysphere’s own blog in 2023, when it raised $8M from Open AI, hinted at that future: a place where “the source code itself starts to melt away,” and where developers whip up massive applications with a few lines of pseudo code. Essentially, abstraction. It’s software becoming language.

But that vision will require more than good UX. It will demand trust, defensibility, and a platform strategy that withstands Big Tech’s copy-paste instinct. Cursor may have automated the first principles. Whether it can prolong its own advantage is next on the list…

What’s Next (For Users)?

Right now, Cursor users are essentially approvers: they review, fix, and greenlight AI-generated code. But once the underlying AI models develop further, the most valuable users may be the “idea people”, those who can simply articulate what they want in plain English and let the AI handle the rest. These users won’t need to know how to build a thing, only what the thing should do.