CodeScene

CodeScene is a multi-purpose tool bridging code, business and people. See hidden risks and social patterns in your code. Prioritize and reduce technical debt.

[CodeScene @codescene]

In this tutorial we use CodeScene ACE to refactor code smells using Gen-AI and through a fact-checking validation we can make sure that the refactoring has preserved the behaviour of the code.🚀

https://t.co/a0SodKYUNy

[CodeScene @codescene]

🚀New: Our Deterministic PR Refactoring Agent triggers Code Health-guided refactoring directly from a pull request. 60% defect risk when agents work on unhealthy code. 50% fewer tokens when they don't. Fix the foundation first. Read more: https://t.co/0IzUoshhdv

[CodeScene @codescene]

Agents working on unhealthy code consume up to 50% more tokens. Read the full article: https://t.co/4zt64DwnuU

[CodeScene @codescene]

We’re proud to be featured once again in the @thoughtworks Technology Radar, a big thank you to the team for the recognition. 🙏

Read more and download the full Technology Radar:
https://t.co/10fEFM17AV

[CodeScene @codescene]

We're live on Product Hunt, come and join the conversation and share your feedback 🚀

https://t.co/5rh2Br1YJn

[CodeScene @codescene]

We benchmarked Claude Code on refactoring tasks, with and without MCP guidance. The MCP-guided agent achieved 2–5x more improvements in Code Health compared to raw refactoring attempts.

Read the full blog post:
https://t.co/klmNBd7IWL

[CodeScene @codescene]

📺 How to guide AI agents with code health, and why it matters
https://t.co/keeG8Apa8D

[CodeScene @codescene]

We built the CodeHealth MCP server because we hit a very real problem.

AI can generate code quickly. But it doesn’t necessarily generate healthy code. We're changing that.

P.S..we’re opening early access.
https://t.co/II31EWCbl4

[CodeScene @codescene]

Raw vs. guided AI refactoring:

Claude Code out-of-the-box vs. guided by the CodeHealth MCP isn’t a small difference, it’s a step change. Across all scenarios, the MCP-guided agent delivered 2–5x more Code Health improvements than raw refactoring.

https://t.co/klmNBd7IWL

[CodeScene @codescene]

Why AI Performs Worst Where Enterprises Need It Most and What Leaders Can Learn from Code Health Research

Read the article:
https://t.co/bKGLc6j9ua

[CodeScene @codescene]

AI-generated changes fail 30%+ more often in unhealthy code.

That’s what our peer-reviewed study (5,000 programs, 6 LLMs) shows.

Next week, we’re hosting a live webinar on:

How to scale AI safely, without increasing defect risk.

Join us 👇
https://t.co/GmQVGdg7nz

[CodeScene @codescene]

Sign up for our upcoming webinar where we explore how to adopt and scale AI coding safely, with real-world evidence from loveholidays.

We’ll also dive into how Code Health determines AI performance, when AI introduces defects, and how to avoid them.

👉 https://t.co/sjWTKFCAUS

[CodeScene @codescene]

Code Health determines whether AI accelerates delivery or amplifies defects, and how you can mitigate the risk.

Read our latest whitepaper: https://t.co/ueunjduG6a

[CodeScene @codescene]

How @loveholidays beats the trend and proves that you can scale up AI-assisted development, keep and improve high-quality throughput and measure ROI of AI.

We're happy to be featured on International Business Times with this story:
https://t.co/a7XfD7Qmlo

[CodeScene @codescene]

Can you show real ROI of refactoring with an AI agent? Yes, you can. 💯

[CodeScene @codescene]

AI can write code fast. But without guardrails, it also writes technical debt.

Here’s a practical, research-backed “inner developer loop” to turn AI into a reliable engineering partner:

https://t.co/GiskFs2nvS

[CodeScene @codescene]

We’ll dig into why we now need a reliable code health metric more than ever, and what the toolkit for crafting healthy code looks like, whether or not you’re using AI agents.

P.S. We’ll also show you how you can make AI agents reason about code quality.

https://t.co/oLBTaY627m

[CodeScene @codescene]

📣 Only two hours to go — sign up for the webinar if you haven’t yet. We’ll dive into what it takes to make AI-generated code truly production-ready.

Sign up: https://t.co/picZ92dmVN

[CodeScene @codescene]

Enabling AI coding assistants to understand the code health of both the existing codebase and the code they produce, so they can propose improvements, perform targeted refactorings, avoid introducing technical debt, and gain insight into design problems.

[CodeScene @codescene]

Today’s LLMs can pass coding tests with ease, but that only tells part of the story.

Join us for a webinar where we will go through groundbreaking research from @codility that redefines how we evaluate AI-generated code.

https://t.co/WEn3ZehZEo

[CodeScene @codescene]

Identifying high technical debt friction. Let's take MongoDB as an example.