Developers have always cared about security. The problem is the security team's ask: fix 1,000 scanner tickets, none of them relevant to what you're actually building. Security teams that generate noise lose all credibility with the engineers they depend on.
Where this was said
At 15:55 · chapter starts 14:20
De la Garza shares a telling anecdote: a family member at a large American corporation described AI tools reducing the need for manual code writing, prompting the company to redeploy engineers to the security team. The talent that security teams could never afford — or couldn't attract over software engineering salaries — is suddenly available. Escobar confirms that at Datadog, security engineers are now paid on par with software engineers, treating the roles as functionally equivalent [1] — Joel de la Garza "Security engineers at Datadog are paid the same as software engineers. AI is redistributing engineering talent — as demand for tier-1 coder…" 14:00 . De la Garza frames this as the culmination of a thesis he's held for a decade: that security engineers would eventually become 'real engineers.' The DevEx team at Datadog is even co-investing in the same agent monitoring tooling as the security team, because the data they each need overlaps significantly. The silos are dissolving.
Datadog pays its security engineers on par with software engineers, reflecting a broader convergence of the two roles in modern tech companies.
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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