Technology has always pushed the boundaries of what we thought possible. For some, like Swami Sivasubramanian, this journey started with limited access to a single computer in rural India, where every minute counted. This early experience fueled a passion for problem-solving and led to a career building foundational technologies like AWS, DynamoDB, SageMaker, and Bedrock. Now, as VP of Agentic AI at AWS, he's looking ahead to the next big shift: AI agents.
Key Takeaways
- AI agents are autonomous software systems that use AI to reason, plan, and adapt to achieve user goals.
- They can interact with digital environments like humans, lowering the barrier for complex tasks like application building.
- Not all AI is an agent; true agents can plan, code, use tools, synthesize results, and learn from failures.
- Three key milestones are needed for AI agents to become widespread: better software building tools, trust, and accessibility for everyone.
- Combining AI agents with automated reasoning can help build trust and ensure agents behave as expected.
- The ultimate goal is to enable anyone, regardless of coding skill, to build and use AI agents.
What Exactly Are AI Agents?
Think of AI agents as smart digital assistants that can take initiative. They're not just responding to commands; they're designed to reason, plan, and adapt to achieve goals you set for them. These agents can interact with the digital world, much like we do, turning your high-level objectives into concrete steps. They also get better over time, learning and improving their efficiency. We're already seeing them used in areas like software development, drug discovery, and farming. The exciting part is how they can handle complex tasks, like building applications, by simply understanding your goal rather than needing detailed instructions.
It's important to distinguish agents from simpler AI tools. For instance, asking an AI to propose experiments is a chatbot function. An AI agent, however, would go further: it would plan those experiments, write the necessary code, use the tools to set them up, analyze the results, and even learn from any mistakes. What might take a human a week to plan could be done by an agent in minutes, freeing you up to act more like a trusted advisor, guiding the agent's execution.
The Road Ahead: Milestones for AI Agents
While the potential is huge, AI agents still have some hurdles to clear before they become a regular part of our lives. There are three main milestones they need to hit:
- Building Better Tools for Builders: A lot of our world runs on software. For AI agents to become mainstream, they first need to be useful and interesting to the people who build software – developers. This means making it easier to build agents and rethinking how we design agent systems. Currently, developers spend a lot of time on technical details, like choosing the right servers. In the future, AI agents should handle these decisions, letting developers focus on the creative aspects of what they're building.
- Establishing Trust: For any AI agent to be useful, we need to trust it. We know agents aren't perfect and can make mistakes. However, even for simple tasks, we often need perfection. The good news is that agents operate within systems that have clear rules. Techniques like automated reasoning, which uses mathematical logic to verify if a system is behaving as expected, can help. This field, with roots going back to ancient Greece, can mathematically prove that an agent's actions are correct before they even happen. For example, at AWS, they've used this to ensure an agent called Amazon Q doesn't make invalid requests, creating a transparent feedback loop that corrects errors quickly.
- Enabling Anyone to Build Agents: AI agents can't change everything if only a small group of people can build them. The goal is to make agent creation accessible to everyone, not just coders. Imagine needing to summarise a TED talk in two minutes using only clips – a difficult task manually. Similarly, creating video recaps used to take weeks. By introducing agents that can understand video content (observation), generate scripts (reasoning), and work with experts (action), this process becomes much simpler. Frameworks are already making it easier for developers to build agents, but the interfaces need to become familiar to business users too. We need agents that are ready for the real world, and we need to create environments where they can learn and improve.
The Future is Agentic
If we get these milestones right, AI agents will become almost invisible, quietly helping us achieve incredible things. We'll likely see more companies starting up faster, with success based on ideas rather than technical barriers. Medical breakthroughs and discoveries could accelerate. The most exciting part is that this future, powered by AI agents, will ultimately be built by all of us. The question is: what will you build with your 10 minutes?