overview
Overview
A robust AI coding benchmark designed to evaluate genuine problem-solving capabilities of agentic AI on novel, unseen scenarios.
A robust AI coding benchmark designed to evaluate genuine problem-solving capabilities of agentic AI on novel, unseen scenarios.
Stork Quadrant
An LLM can do most of what this tool's UI promises. No moat, no agent presence.
“This is a benchmark tool, which means its core product is a curated set of problems and a scoring harness. LLMs can generate novel coding problems, and the open-source community already produces competing benchmarks freely. There is no proprietary data, no network effect, no regulatory gate. This will be commoditized fast.”
An LLM alone could replace
The only real move is to own a continuously refreshing problem set sourced from real production codebases under license — problems that can't be scraped or replicated — and sell access to that corpus to model labs who need eval data they can trust hasn't leaked into training sets.
<a href="https://www.stork.ai/en/deepswe" target="_blank" rel="noopener noreferrer"><img src="https://www.stork.ai/api/badge/deepswe?style=dark" alt="DeepSWE - Featured on Stork.ai" height="36" /></a>
[](https://www.stork.ai/en/deepswe)
overview
A robust AI coding benchmark designed to evaluate genuine problem-solving capabilities of agentic AI on novel, unseen scenarios.
For builders
AI agents read it. Buyers find it. Backlinks accrue. Your tool can have one too — live in 24 hours, indexed by Claude, ChatGPT, and Perplexity, queryable via MCP.