Prompt engineering got us here. But what's taking AI agents further?

You're just on time! In this Tech Explained episode, Veerashri Patil, Associate Director at Nitor Infotech, takes you beyond prompt engineering, exploring why the context you give AI matters more than the instructions themselves, and what that means for the future of AI agents.

In this Tech Explained episode, we explore the emerging concept of the Agent-Computer Interface (ACI) and why the future of AI isn't just about better prompts; it's about better context.

When an AI agent reviews a pull request, it doesn't just need the code. It needs requirements, dependencies, recent changes, and team relationships that are structured, connected, and governed. That's context engineering. 

📌 In this video, you'll learn: 

• What the Agent-Computer Interface (ACI) is and why it matters 
• Why prompt engineering alone has its limits 
• How context engineering shapes better AI decisions 
• What an SDLC context graph looks like in practice 
• Why a smaller model with strong context can outperform a frontier model with weak context 

Whether you're an AI practitioner, software engineer, or tech enthusiast, this one will shift how you think about building with AI agents.

🎧 Check out our last Tech Explained audiocast: https://youtu.be/ZERc41bsYUQ?si=IfKFhn4_4fqMYdDJ

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