---
title: "Discussion on \"[Part 2] Building Correlic: Your AI Agent Made 70 System Calls Per Second. Here's How I Taught My System Which Ones Matter.\" | Hashnode"
description: "Discussion on \"[Part 2] Building Correlic: Your AI Agent Made 70 System Calls Per Second. Here's How I Taught My System Which Ones Matter.\". Four failed attempts at teaching a machine what matters — and the baseline system that finally got it right."
url: "https://hashnode.com/posts/part-2-building-correlic-your-ai-agent-made-70-system-calls-per-second-here-s-how-i-taught-my-system-which-ones-matter/69d7d80ffa7251682ecee170"
---

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# [\[Part 2\] Building Correlic: Your AI Agent Made 70 System Calls Per Second. Here's How I Taught My System Which Ones Matter.](https://correlic.hashnode.dev/part-2-building-correlic-your-ai-agent-made-70-system-calls-per-second-here-s-how-i-taught-my-system-which-ones-matter?utm_source=hashnode&utm_medium=feed)

Four failed attempts at teaching a machine what matters — and the baseline system that finally got it right.

Apr 9 · 15 min read · correlic.hashnode.dev  
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## Written by

[Correlic](https://hashnode.com/@correlic)

@correlic

  
[View profile](https://hashnode.com/@correlic)

Kernel-level security observability for AI coding agents

AI coding agents run on your machine with broad access to files, network, and system calls — but most developers have zero visibility into what they actually do. Correlic is building kernel-level security observability to change that. Using eBPF to trace every syscall, we detect anomalous behavior, correlate threat patterns, and give developers a real-time audit trail of AI agent activity. This blog documents the technical journey of building Correlic from the ground up — the engineering challenges, the failed approaches, and the breakthroughs in making AI agents transparent and accountable.

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