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Holy shit...Google just dropped CodeMender an autonomous AI agent that finds and fixes security bugs in code by itself. This isn’t a static analysis tool. It’s a self-reasoning system that patches vulnerabilities and rewrites insecure code before humans even find it. Let’s break it down ↓

Hasan Toor

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127,108 views • 8 months ago •via X (Twitter)

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Claude Code tip: create an agent that specialises in code review and security. Then add a new memory entry with a nickname for it so you can call it anytime. My code review and security agent is called Big Tony.

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Julian Goldie SEO

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IN 1986 MIT FILMED THE LECTURE WHERE CODE STOPPED BEING CODE AND BECAME DATA 43 minutes from Gerald Sussman, in the most legendary intro programming course ever recorded. -> The idea that lands: to a program, your code is just data it can read and rewrite. He builds a program that does real calculus -- not by crunching numbers, but by reading the math as a list and transforming it piece by piece. Then he shows the trick hiding under all of it: in this language, code and data are the same material. Forty years later that is exactly what an AI coding agent is -- a program that reads your code as data, rewrites it, and hands it back. Sussman drew the whole idea on a blackboard in 1986. Writing code was never the deepest skill -- understanding that code itself is data a program can manipulate is. This is where you learn it. Most people think AI writing code is brand new. The ones who watch this saw the blueprint 40 years ago. Bookmark & Watch it. This one's a legend ↓

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Olympix is officially in Live Beta! Olympix is a proactive DevSecOps tool that employs static analysis to empower smart contract developers to detect vulnerabilities in real-time. Developers can leverage Olympix to assist them in creating robust and secure code Try it here:

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OpenAI just released Codex Security, an AI agent that scans software projects to fix vulnerabilities while ignoring harmless bugs. Testing on 1.2mn commits found 792 critical flaws and dropped false alarms by 50%. Here is how the Codex Security agent works Initially, it scans your software project to learn how all the different pieces of code connect. It uses that knowledge to build a threat model, which acts as a custom map showing exactly where your software might be exposed to hackers. The agent then hunts for potential security holes based on that specific map. When it spots a possible flaw, it does not just send you a random alert. Instead, it creates a completely safe and isolated copy of your system known as a sandbox. The agent then actively tries to break into that sandboxed copy to prove if the security weakness is a real danger. If the agent successfully exploits its own test environment, it knows the bug is a genuine threat and not a false alarm. After confirming the danger, the agent writes a custom software patch to fix the broken code. It then tests that new patch to guarantee the fix does not accidentally break any other features in your software.

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AI has completely changed how code gets written. Models can now generate thousands of lines in minutes. That speed is exciting but it also creates a new problem... reviews are slow. Context is missing. Bugs slip through. The bottleneck isn’t writing code anymore, it’s understanding and shipping it safely. It’s why I’ve been looking closely at tools built AI-first for this stage of the workflow. One that stands out is Graphite Agent. It sits inside your PRs and does what reviews have always struggled with at scale: → Explains logic line-by-line → Surfaces and fixes bugs → Resolves failing checks in context All without leaving the review flow.

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23,400 views • 6 months ago

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