The world of AI is experiencing a fascinating shift and it’s all about autonomy.

What started as prompt engineering, retrieval augmented generation (RAG), model context protocal (MCP), where we had to constantly feed an AI with individual instructions to get anything done, is quickly becoming a thing of the past. We are now entering the era of AI Agents.

With just a set of initial, high-level instructions, these agents are capable of running in the background, making decisions, and getting complex jobs done, all on their own.

Orchestrating the Future

For me, witnessing this revolution is absolutely captivating. We’re moving from giving single prompts to being able to orchestrate multiple agents for various tasks. Imagine setting up a mini-team of specialized AIs, each handling a different part of a project!

These agents are poised to become our new teammates, new peers, or whatever we want to call them to give this technological leap a personal, human-centric touch. They won’t just execute; they will contribute, run, and complete objectives with minimal hand-holding.

The Security Question: Thinking from Day One

However, this rise in autonomy brings a critical conversation to the forefront: Security for AI Agents.

When I talk to people about this, a common thread of hesitancy emerges, often centered on whether these solutions are safe enough. This concern is frequently tied to the supply chain security of the software packages and frameworks we use to code and build these agents. It’s a completely valid point. After all, if our underlying tools aren’t secure, neither are the agents we build with them.

Security cannot be an afterthought; it needs to be embedded into our thinking from day one. Agentic AI security is certainly going to evolve rapidly, addressing these concerns with new standards and practices. I am incredibly curious to see how the industry tackles this and how secure, autonomous teams become the norm.