Artëm builds Stopilot, an editor that refuses to write code

Artëm built Stopilot, a code editor that refuses to write code until the developer describes the task in plain language. It answers a problem: Cursor writes too fast, and developers can't keep up with understanding what it produces. Within 8 months, Stopilot reached 1.29 million rubles a month in revenue.

AI-processed from Habr AI; edited by Hamidun News
Artëm builds Stopilot, an editor that refuses to write code
Source: Habr AI. Collage: Hamidun News.
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Article Fact Sheet & Key Figures
ParameterDetails
Primary sourceHabr AI ↗
Editor-in-Chief
Key metric #1Stops the impulse to start writing code right away
Key metric #2Forces developers to state requirements in plain language
Key metric #3Only then offers a solution

Artëm built Stopilot over a weekend: a code editor that refuses to work. To any prompt it replies: "First, state the task in plain language." After 8 months, the project reached 1.29 million rubles a month.

Why Cursor became a problem

The usual AI-tools story goes like this: a developer opens Cursor, builds a SaaS over a weekend, posts a screenshot of MRR and explains that the key is to validate hypotheses fast, without overthinking. Artëm noticed something different. Cursor solved the problem of how fast code gets written, but created a new one: code is written faster than people can understand it. The developer gets generated code and doesn't know how to maintain or scale it.

How Stopilot works

The core idea is simple. The editor does not generate code until the developer explains the task in one paragraph. It is not a replacement for Cursor but a complement for teams tired of mountains of incomprehensible code. The tool makes developers think first and code second.

  • Stops the impulse to start writing code right away
  • Forces developers to state requirements in plain language
  • Only then offers a solution
  • Sold to companies with large development teams

The first 8 months

Artëm built the MVP over a weekend. After 8 months, Stopilot reached 1.29 million rubles a month. Its customers are teams that hired many developers after the wave of AI tools and now manage a mass of generated code that nobody is able to maintain. This is not about fast growth, but about a healthy development process.

What this means

Not every AI tool has to write code automatically. Sometimes AI should help the developer understand the task rather than take it over. Stopilot showed that there is demand for pushing back on the pace of generated code, and that it is larger than it seemed.

Story

Key Questions Answered

Why Cursor became a problem?

The usual AI-tools story goes like this: a developer opens Cursor, builds a SaaS over a weekend, posts a screenshot of MRR and explains that the key is to validate hypotheses fast, without overthinking. Artëm noticed something different. Cursor solved the problem of how fast code gets written, but created a new one: code is written faster than people can understand it. The developer gets generated code and doesn't know how to maintain or scale it.

How Stopilot works?

The core idea is simple. The editor does not generate code until the developer explains the task in one paragraph. It is not a replacement for Cursor but a complement for teams tired of mountains of incomprehensible code. The tool makes developers think first and code second. Stops the impulse to start writing code right away Forces developers to state requirements in plain language Only then offers a solution Sold to companies with large development teams

What are the key details on The first 8 months?

Artëm built the MVP over a weekend. After 8 months, Stopilot reached 1.29 million rubles a month. Its customers are teams that hired many developers after the wave of AI tools and now manage a mass of generated code that nobody is able to maintain. This is not about fast growth, but about a healthy development process.

ZK
Zhemal Khamidun — CPO at Alpina Digital, product manager of AlpinaGPT. Building AI products since 2019. Hamidun News is a pet project that grew into a production aggregator with 6,000+ readers.
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