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.
Where this was said
At 10:25 · 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.
Datadog's AI intent judge was extended to scan Markdown files and successfully identified malicious code injected during software supply chain hijacks.
The fastest path to Twitter growth isn't volume — it's forming sharp opinions about how the platform works and sharing them immediately. People cluster around those who understand the rules and say so out loud.
Sam had no coding knowledge, so he used ChatGPT voice mode to generate his entire codebase and copy-pasted it into Notepad. A friend later introduced him to Cursor, and he never looked back.
Copy days of Discord chat history, paste it into ChatGPT, and ask it to list recurring pain points. The ones that come up most often are your best product bets.
Sam's top advice: when prompting Cursor, tell it to architect code for 100,000 users from day one. The AI changes its approach, building scalable frameworks instead of brittle one-user code.
With AI coding tools like Cursor, Bhanu replicates an existing free tool for a new keyword in under 5 minutes. What used to be a multi-day build is now a lunch-break task.
Ahrefs, SiteGPT, Cal.com, PostHog, Datafast, Sibyl AI, Bento, Feather, Featurepace, Mintlify, Cloud Code, ChartMogul — Bhanu runs his entire business solo with these 12 tools.
PropGPT runs on React Native with TypeScript and Python for ML, Neon for the database, RevenueCat and Superwall for monetization. LLM costs are $20/month, data APIs $100/month, and after $10K in monthly marketing spend, margins sit at roughly 50%.
Automated food production cheaper than grocery shopping. Mining companies that own nothing but real estate. Kalanick believes these are near-certainties, not moonshots, and they dwarf anything digital AI has done to enterprise software.
Meraki couldn't beat Cisco on reputation in 2009. So they stopped trying to pitch and started shipping. Attend a webinar, get a free access point. Once mid-market IT teams experienced cloud-managed networking, no argument was needed — the product sold itself.
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