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Mark StrattonApr 17, 20253 min read

Agentic Computing: How GenAI Is Reshaping Software From the Inside Out

A new architectural paradigm where intelligent agents collaborate, adapt, and replace code with composition.

Every once in a while, something big shifts in how we build software. Not the kind of shift that changes a framework or favorite tool, but one that reorients how we think entirely. Agentic Computing is doing exactly that and GenAI is the spark igniting it. If GenAI gives us intelligence on demand, agentic computing is how we turn that intelligence into dynamic, adaptable systems.

Agentic Computing is a new architectural paradigm – a system-level design pattern where intelligent agents work together autonomously to solve problems, adapt to context, and compose dynamic workflows. GenAI supercharges this shift, enabling agents to reason, interpret, and act in ways that once required human input.

Let me unpack it.

From Teams to Agents

For years, we’ve scaled software development through people – smart teams using microservices to break things down and keep things moving. But scaling people has limits. Coordination becomes complex. Consistency gets harder. Innovation slows.

Agentic computing doesn’t replace teams, but it does something wild: it extends what a team can do by introducing smart, autonomous agents that handle tasks, collaborate across systems, and even adapt as conditions change. It shifts coordination from people to software, augmenting and accelerating what teams are capable of. Think of these agents as digital coworkers – ones that never sleep and get smarter with time.

And here’s where GenAI becomes the spark.

What Makes It GenAI

These agents aren’t just rules and scripts. They reason. They interpret. They summarize. They decide. A GenAI-powered agent can:

  • Read a website and extract qualified sales leads.
  • Detect energy inefficiencies across complex datasets.
  • Talk to users and trigger actions without a dev in the loop.

We’re now seeing GenAI stitched into workflows alongside APIs, traditional code, and external tools. This isn’t “just AI.” It’s GenAI in the stack, making software more exploratory, more adaptable, and, dare I say it, more fun to build.

Agentic Computing GenAI Agent diagram

A Story: From Search to Strategy

Let’s say I want to generate leads – not just any leads, but opportunities in distressed debt. The kind of intel that, traditionally, gets passed around in tight-knit circles, backchannel referrals, or pricey lead lists everyone gets at the same time.

The old approach? Buy expensive lead lists from aggregators, the same ones everyone else is buying. Manually scan through them, try to score relevance, enrich the data, and push it into a CRM. It’s slow, repetitive, and you’re still late to the game, chasing deals that others already see.

Agentic approach? Chain GenAI-powered agents to:

  • Continuously search the web for telltale signals of financial distress.
  • Read and interpret company announcements, regulatory notices, local news.
  • Summarize the opportunity and assess relevance.
  • Enrich with firmographic context and contact info.
  • Push the lead into CRM or alert the right person.

Agentic Computing Lead Management Cycle diagram

Now I’m not chasing the market – I’m finding leads before others even know they exist. That’s the competitive nuance. That’s what changes the game.

And here’s the kicker: I didn’t build a product. I composed a system. A living pipeline. Intelligent, agentic, always evolving.

The New Stack Is Agentic

You’ll still need good engineering. You’ll still care about data, APIs, logic. But increasingly, you’ll design flows of intelligence – chaining agents that:

  • Access and transform data
  • Call models or systems
  • Make autonomous decisions
  • Return outputs that trigger the next agent

It’s a new skill. And it’s a new creative space.

Why I’m Writing This

Because I’ve seen this pattern emerge firsthand. Because I think the people who embrace this early will have a serious advantage – not just technically, but strategically.

This isn’t about replacing developers. It’s about unlocking a new generation of composability, speed, and reuse. We’re building faster, with less, and discovering more.

Here at DevIQ we have successfully completed a number of GenAI projects. Feel free to reach out if you need help with yours.

Final Thought

Agentic computing is more than a pattern. It’s a new way to build. One where GenAI isn’t bolted on, but baked in. One where your software learns. One where your next feature might not be coded – it might be composed.

Start now. This gets more fun by the day.

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Mark Stratton

Mark helps enterprises bring new ideas to market through smart, scalable software strategies. He’s passionate about aligning business goals with practical solutions that drive revenue – when he’s not chasing fresh powder, sipping a hazy IPA, or hiking mountain trails.

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