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Sunil Gattupalle

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Sunil Gattupalle

AI Engineering Architect

at
Harness

Sunil is an Engineering Architect focused on building production-grade AI and data platforms at scale. With over 20 years of experience across companies like Harness, Traceable AI, Cisco (AppDynamics), Aruba, and Juniper, his work spans distributed systems, knowledge graphs, API security, and real-time analytics. He currently leads enterprise Data and AI Platform initiatives at Harness, including knowledge graph–driven RAG systems and agentic AI workflows. He has contributed to multiple U.S. patents and writes about bridging traditional systems engineering with modern AI architectures.

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Sunil Gattupalle

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Harness AI

When the Model Decides Instead of Writes

Auditable Agent Judgment: Jev's Decision Primitive at Harness

Sunil Gattupalle
Shubham Jindal
+ more
September 21, 2026
12 minutes to read
Read the article
When the Model Decides Instead of Writes

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Sunil Gattupalle

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Engineering Blog
Technical
Operations

Engineering

What a Context Graph Actually Is, and How to Build One

Context graphs help AI agents reason through work by modeling how processes happen across your organization. This guide breaks down what they are, how they differ from knowledge graphs, core architecture patterns, and key steps for building one.

May 18, 2026
15 minutes to read
What a Context Graph Actually Is, and How to Build One

Engineering

When the Model Decides Instead of Writes

Auditable Agent Judgment: Jev's Decision Primitive at Harness

September 21, 2026
12 minutes to read
When the Model Decides Instead of Writes

Engineering

What a Context Graph Actually Is, and How to Build One

Context graphs help AI agents reason through work by modeling how processes happen across your organization. This guide breaks down what they are, how they differ from knowledge graphs, core architecture patterns, and key steps for building one.

May 18, 2026
15 minutes to read
What a Context Graph Actually Is, and How to Build One

Engineering

The Agent Loop Is the New OS: Design Philosophy of the Harness MCP Server

Well-designed agent infrastructure isn't about building smarter tools. It's about building fewer, more composable ones that keep the context window free for reasoning.

April 23, 2026
14 minutes to read
The Agent Loop Is the New OS: Design Philosophy of the Harness MCP Server

Engineering

How Harness Grounds AI Agents in a Knowledge Graph for Deterministic Answers

Learn how Harness grounds AI agents in a schema-driven Knowledge Graph to deliver deterministic, efficient answers across CI/CD, security, and cloud cost modules.

April 7, 2026
4 minutes to read
How Harness Grounds AI Agents in a Knowledge Graph for Deterministic Answers

Engineering

Architecting MCP for AI Agents: Lessons from Our Redesign

The Harness MCP v2 Server covers 125+ resource types across 30 toolsets with 11 tools and 26 prompt templates. It supports Cursor, Claude Code, and any MCP-compatible client.

March 19, 2026
13 minutes to read
Architecting MCP for AI Agents: Lessons from Our Redesign

Engineering

Knowledge Graph + RAG: A Unified Approach to DevOps Intelligence

Learn how Harness uses a software delivery knowledge graph, a semantic layer, and RAG together to give DevOps teams deeply contextual, trustworthy AI automation that goes far beyond “chat over docs.”

December 17, 2025
3 minutes to read
Knowledge Graph + RAG: A Unified Approach to DevOps Intelligence

Technical

Introducing Harness AgentTrace: An Observability and Guardrail Framework for AI Agents

Harness AgentTrace unifies AI observability, evaluation, and guardrails to detect failures, improve quality, and secure AI agents in production.

July 21, 2026
10 minutes to read
Introducing Harness AgentTrace: An Observability and Guardrail Framework for AI Agents

Technical

Why AI Agent Data Quality Starts With Infrastructure, Not Prompts

Correctness, groundedness, safety, efficiency — every dimension of agent quality traces back to the same thing: structured access to well-modeled data.

April 13, 2026
10 minutes to read
Why AI Agent Data Quality Starts With Infrastructure, Not Prompts
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