The Stack Overflow Podcast
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Your snips
[00:46] Agents Drive Massive API Growth
[01:37] MCP Is An Agent-Friendly API Protocol
[03:22] Wrap APIs For Agent Adoption
[05:28] Security And Impersonation Are Unsolved
[07:31] Prompts As The New Interface
[10:19] Build Agentic Infrastructure Now
[11:23] Enterprises Are Betting On LLMs โ With Caution
[13:31] Put Guardrails In The Platform
[17:42] Observability Needs To Include Decisions
[20:43] Cut Token Costs At The API Layer
[22:53] Automate Busy Work Before Competitors Do
[24:17] Work Evolves; Security Demands Surge
What I learned from ๐ฃ๐ผ๐ฑ๐ฐ๐ฎ๐๐ Today ๐๏ธ
I just finished listening to:
๐ฃ๐ผ๐ฑ๐ฐ๐ฎ๐๐: The Stack Overflow Podcast with Marco Palladino
๐๐ฝ๐ถ๐๐ผ๐ฑ๐ฒ: As your AI gets smarter, so must your API
๐๐ฒ๐ ๐ง๐ฎ๐ธ๐ฒ๐ฎ๐๐ฎ๐
Before you rush to build the next AI agent, ask yourself: which of your business processes can actually be automated? Your competitor is already asking the same question. The organizations that win won't just use AIโthey'll systematically audit their workflows and redirect human talent to high-value problems while agents handle the busy work.
๐ช๐ต๐ ๐๐ ๐ ๐ฎ๐๐๐ฒ๐ฟ๐
In finance and data science, we're drowning in repetitive tasks: report generation, data validation, compliance checks. AI can handle these at scale. The real competitive advantage comes from reallocating your analysts and engineers to strategic modeling, risk assessment, and product innovationโnot from having them do what a well-designed agent could automate.
๐ฅ๐ฒ๐ณ๐น๐ฒ๐ฐ๐๐ถ๐ผ๐ป ๐ง
This episode reminded me that AI adoption isn't about replacing jobsโit's about evolving them. I've spent too much time debating which AI tool to use and not enough time mapping out which processes in my own workflow are ripe for automation. The productivity gains aren't coming from fancier models. They're coming from being honest about where human expertise adds value and where it doesn't.
To get the full insight, check out the podcast!
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