Understanding the importance of System Design

System design is one of the most important skill you can master while designing your AI applications or products.

5.5 years ago, when I was working on designing my ed-tech product, I was more involved in designing the funationality or flow but was also trying to understand the backend design flow and logic with my developer.

I took the same understanding while designing this AI Agent for one of our online courses which we are currently providing at IDALS.

Good AI products are more about systems than models.

While I was building the AI Customer Care agent, below is how I started thinking about the architecture with assistance of an LLM.

Step 1: Breaking down the problem

• User Interface - where users chat (Web UI)

• Router - decides what kind of question this is

• Knowledge Layer - fetches only verified information

• Safety Layer - Blocks hallucinations, problems or legal claims

• Escalation Layer - hands over to humans when needed

• Accuracy Layer - tracks intent, accuracy and failures

Each part does one job well.

Step 2: Controlling the flow rather than trust AI blindly

• First, the system classifies intent

• Then, it retrieves facts from trusted source

• Only after that, the AI is allowed to respond

• If the answer is risky then escalate to a human

This is how I tried to reduce hallucinations and build trust

Step 3: Observing the system like a product and not a demo

I added analytics to answers questions like:

• What users ask most

• Where AI fails

• Which intent needs human support

• Where improvements are needed

You need to observe in order to improve it.

Here, I not only focused on features but also designing guardrails.

Below is the image of the architecture I designed through Figma AI.

AI is definitely powerful but architecture is what makes it usable in the real world!

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