• Timeless Patterns, Smarter Tools: AI agents may seem revolutionary, but they are built on timeless integration patterns like those in ESBs and ET

The Truth About AI Agents: Are They Really That New?

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2024-12-14 03:30:05

• Timeless Patterns, Smarter Tools: AI agents may seem revolutionary, but they are built on timeless integration patterns like those in ESBs and ETLs, enhanced with smarter capabilities like dynamic parsing and semantic routing.

• Evolving Roles and Teams: They unify application and data integration efforts, dissolving silos. Traditional roles like middleware specialists, ETL developers, and data scientists evolve into Agentic Workflow Engineers and Applied AI Specialists.

• Practical Adoption Guidance: Adopting AI agents requires rethinking team structures, starting small with AI-enhanced workflows, and focusing on reusable, scalable components to thrive in the era of agentic workflows.

In today’s tech landscape, AI agents are the latest buzzword. For a data scientist, they might feel like a fascinating new playground. For an engineer, they’re an intriguing challenge. For decision-makers, they trigger a bit of FOMO—“Shouldn’t we be using this too?” But if you’ve spent years in the middleware world, connecting systems and orchestrating workflows, you’ll recognize them for what they are: an integration flow with a few extra tricks.

This thought first struck me while watching the you.com CEO’s interview with the FII Institute on YouTube. When asked about AI’s limitations, he used the term plumbing, and it immediately took me back to the old integration days. Beneath the buzz and innovation, AI agents are still fundamentally rooted in the same timeless integration patterns—routing, transformation, and orchestration—that have driven systems for decades.