AI Agents are here: Let’s talk about it

The emergence of artificial intelligence (AI) agents in the last several months is shaking things up in the AI world.

While industry buzz has been focused on new technologies like generative AI, its biggest potential might be in how we use it to build new applications. Enter AI agents. 

The rise of AI agents and agentic reasoning is one of the most significant leaps in AI systems, and they’re reshaping the way we design and build programs.

We’re talking about smart software — intelligent, goal-driven systems that use tools, retain information, and work together. 

AI agents aren’t the chatbots you might be familiar with that generate a response to a prompt in one go. AI agents interpret instructions to determine how to get something done — end-to-end. 

They act independently: exploring data, executing operations, leveraging external tools, and adapting based on memory.

The big opportunity for exponential innovation lies in the ability to combine them in different ways to solve new problems. Specialized agents — geared at doing one task well — can be coordinated and work together to tackle new challenges. 

These intelligent systems are proving to be powerful and fast. They’re flexible and easier to build, evaluate, and update.

Start by asking yourself what you need your AI agent to accomplish. What’s the goal?

Choosing the right AI model for your system directly affects how well any agent performs specific tasks. The choice determines how the rest of the system behaves, from workflows and tool usage to memory capacity. 

While current AI generation models perform well, selecting the best fit depends on the agent’s needs — whether that’s language nuance, code execution, data analysis, or something else entirely. 

So, picking the best “brain” matters.

At their core, agents operate on workflows. 

Workflows determine how effective, organized, and fundamentally successful a system is at completing complex tasks. 

And without the right architecture, they’re just guessing.

As a real world example, let’s look at what AI research and development company Anthropic is doing to explore the limits and lessons of AI-agent-driven systems. They emphasize the importance of nimble architecture, rather than a linear pipeline. 

Using high‑level reasoning modules to coordinate lower‑level executors is the key. 

Leveraging “lead agents,” Anthropic uses orchestrator-workers to develop a strategy and delegate tasks to specialized agents or tools that work simultaneously. By keeping workflows modular, agents can be adapted, extended, or replaced without rearchitecting the whole system.

Tools turn static models into dynamic, reactive agents.

That’s where Anthropic’s Model Context Protocol (MCP) comes in. It’s like a universal adapter and instruction manual rolled into one. It boasts:

And it’s gaining momentum. MCP has already gained broad industry support and been adopted by OpenAI, Google DeepMind, Microsoft, and more.

Memory transforms reactive agents into proactive collaborators. But memory has to be built in.

Microsoft’s CTO Kevin Scott recently outlined efforts to summarize and index conversations and leap over the challenge of storing excessive data.

The goal is to access key information both quickly and over time.

Rather than reprocess entire conversation histories, Microsoft is trying to improve AI agent “memory” by storing “structured breadcrumbs.” This data enables fast information retrieval and relevance — modeling how humans access memories.

Pushing toward the second half of the year, we’re likely to see:

AI agents are in play. 

Developers can stitch agents together with minimal complexity. MCP is rapidly becoming the standard — analogous to USB‑C for AI agent-tool integration — backed by players like Microsoft, OpenAI, and Google. And AI agents are shifting from siloed tools to memory-enabled ecosystems working to solve problems together. 

The innovations of the last several months are secure and scalable. And the pace of innovation suggests agents will soon be autonomous collaborators, co-designers, and effective digital partners.