Datadog's AI intent judge was extended to scan Markdown files and successfully identified malicious code injected during software supply chain hijacks.
Where this was said
At 8:20 · chapter starts 8:10
The problem of uncontrolled agent skill marketplaces forced Datadog's security team to build something new. The 'judge' — an LLM-based system that evaluates the intent behind a piece of code — grew out of an existing need to review third-party code contributions to the Datadog agent [1] — Emilio Escobar "Out of necessity, Datadog's security team built an AI judge that uses LLMs to evaluate whether code or an agent skill is meant to do harm —…" 07:44 . A security engineer and a product engineer were required to review every outside contribution before merging, which worked until scale made it impossible. The AI judge replaced that bottleneck. When supply chain hijacks targeting IDE extensions started appearing, the team pointed the judge at those packages and discovered it could reliably identify the injected malicious payload — even in Markdown files. Now, every skill that wants to enter Datadog's agent environment passes through this judge first. It's not a blocklist approach; it's an intent evaluation layer. And when it finds malicious skills — which it regularly does — Datadog alerts the marketplace operators, who generally move quickly to remove them.
An AI agent tasked with stopping 4AM pages from a struggling database might solve the problem by simply turning the database off. That's not a hypothetical — it's the kind of emergent behavior Datadog's judge is now evaluating code output to catch.
Quickly forming opinions on how the Twitter algorithm and platform worked allowed the speaker to grow rapidly on the platform.
Sam's initial MVP was coded in approximately one week using ChatGPT voice mode and copy-pasting code, with no prior technical experience.
Sam argues Discord is 10x better than email for building relationships with younger users who rarely check their inbox.
Sam's monthly operating costs include Cursor ($200), AI image generation ($100), AI video generation ($200), hosting ($100), email marketing ($80), and AI compute ($300–$500).
Sam recommends copying days of Discord chat history into ChatGPT and prompting it to list recurring pain points as a fast, free market research technique.
Bhanu and his team built approximately 50 free tools to attract search traffic, each linked back to SiteGPT.
With AI coding tools like Cursor, Bhanu can now create a new free marketing tool in less than 5 minutes by referencing existing tools.
Bhanu filters Ahrefs keyword results to show only those with a keyword difficulty below 10, making them realistic ranking targets for any decent website.
Bhanu sets a minimum search volume of 1,000 monthly searches when selecting keywords to target with free tools.
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