Teradata Possible 2025 in LA, 7-layer technical architecture of agentic AI and more

Hey everyone,

I’m heading to Los Angeles for Teradata Possible 2025 and will be on site for the full program. 

I’ll cover the keynotes, big product news, live demos, and I’ll record interviews with Teradata leaders and customers for The Ravit Show. The event runs October 6 to 8 at JW Marriott L.A. LIVE.

Top 8 Reasons To Join Possible

1. Big keynotes with a clear view of where Teradata is taking AI and data

2. Real customer stories that show outcomes, not slides

3. Product deep dives across VantageCloud, ClearScape Analytics, and AI Unlimited

4. Live demos you can try yourself and take back to your team

5. Small-group roundtables and exec access to talk roadmaps

6. Training and certifications to level up fast

7. A strong community and partner ecosystem in one place

8. My on-the-ground highlights and interviews you can follow live

What you can do on site

• Learn from 30+ sessions and 15+ AI tracks with practical customer stories

• Go hands on with ClearScape Analytics, VantageCloud, and AI Unlimited

• Join small-group roundtables for real conversations and takeaways

• Meet Teradata executives to talk challenges and roadmaps

• Connect with 300+ leaders, 50+ speakers, and top partners

• Get a good mix of learning, demos, and networking across the Expo and evening events

Follow my coverage
I’ll share daily highlights, quick clips, and sit-down interviews from the floor. If your team is attending, reply and let’s meet on site.

Register with a discount
Use my link in the description to save on your pass. I’ll see you in LA. ANINF25LA — the first 50 people who register with it get 50% off. 

Stay tuned for the updates.

7-layer technical architecture of agentic AI

Everyone is talking about AI agents, but very few people actually break down the technical architecture that makes them work.

To make sense of it, I put together the 7-layer technical architecture of agentic AI systems. Think of it as a stack where each layer builds on top of the other, from the raw infrastructure all the way to the applications we interact with.

1. Infrastructure and Execution Environment
This is the foundation. It includes APIs, GPUs, TPUs, orchestration engines like Airflow or Prefect, monitoring tools like Prometheus, and cloud storage systems such as S3 or GCS. Without this base, nothing else runs.

2. Agent Communication and Networking
Once you have infrastructure, agents need to talk to each other and to the environment. This layer covers frameworks for multi-agent systems, memory management (short-term and long-term), communication protocols, embedding stores like Pinecone, and action APIs.

3. Protocol and Interoperability
This is where standardization comes in. Protocols like Agent-to-Agent (A2A), Model Context Protocol (MCP), Agent Negotiation Protocol (ANP), and open gateways allow different agents and tools to interact in a consistent way. Without this layer, you end up with isolated systems that cannot coordinate.

4. Tool Orchestration and Enrichment
Agents are powerful because they can use tools. This layer enables retrieval-augmented generation, vector databases such as Chroma or FAISS, function calling through LangChain or OpenAI tools, web browsing modules, and plugin frameworks. It is what allows agents to enrich their reasoning with external knowledge and execution capabilities.

5. Cognitive Processing and Reasoning
This is the brain of the system. Agents need planning engines, decision-making modules, error handling, self-improvement loops, guardrails, and ethical AI mechanisms. Without reasoning, an agent is just a connector of inputs and outputs.

6. Memory Architecture and Context Modeling
Intelligent behavior requires memory. This layer includes short-term and long-term memory, identity and preference modules, emotional context, behavioral modeling, and goal trackers. Memory is what allows agents to adapt and become more effective over time.

7. Intelligent Agent Application
Finally, this is where it all comes together. Applications include personal assistants, content creation tools, e-commerce agents, workflow automation, research assistants, and compliance agents. These are the systems that people and businesses actually interact with, built on top of the layers below.

When you put these seven layers together, you can see agentic AI not as a single tool but as an entire ecosystem. Each layer is necessary, and skipping one often leads to fragile or incomplete solutions.

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Best,

Ravit Jain

Founder & Host of The Ravit Show