Grounded Reasoning Systems for Cloud Architecture - Iman Makaremi

765 views · Jun 03, 2025 · 26:05 min · Watch on YouTube ↗

Takeaway

Cloud-architecture AI needs grounded multi-agent reasoning over both text requirements and graph topology, not just IaC generation.

Summary

Cat.io's Iman Makaremi presents a multi-agent AI copilot that reasons about cloud architecture rather than just automating it.
Three sub-problems: requirement understanding (text), architecture identification (graph data), and architecture recommendation against best practices.
Combines semantic (LLM over docs/requirements) and graph (cloud topology) context so agents can debate, justify and plan tradeoffs.
System mirrors how human architects negotiate constraints, resources, and timelines instead of just emitting Terraform.

agentscloud-architecturereasoning

Original description

As LLMs move into enterprise workflows, developers face a new kind of architecture challenge: how do you build reliable, interpretable systems powered by agents and reasoning?

This talk unpacks how we designed and implemented an AI orchestration framework for enterprise architecture — combining LangGraph for multi-agent workflows, Flyte for distributed execution, and AWS Bedrock for LLM inference using Claude 3. The product: an AI copilot for enterprise architects, deeply rooted in your tech stack context.

At the core of this system is a domain-specific **knowledge graph** that acts as long-term memory for the agents. It enables persistent, structured representations of architectural state, system dependencies, and business context — giving the agents the grounding they need to generate accurate recommendations, translate natural language into SQL or code, and maintain continuity across workflows.

We’ll also cover how we’ve integrated observability practices — including planned OpenTelemetry instrumentation — to trace and debug autonomous AI systems in production.

If you’re a developer or AI engineer thinking beyond the chatbot and looking to embed reasoning into complex system design and data tasks, this talk offers an end-to-end blueprint — from orchestration and grounding to production monitoring.