Aparna Dhinakaran
Aparna Dhinakaran is the Co-Founder and Chief Product Officer at Arize AI, a pioneer and early leader in AI & Agent observability and evaluation. A frequent speaker at top conferences and thought leader in the space, Dhinakaran was recently named to the Forbes 30 Under 30. Before Arize, Dhinakaran was an ML engineer and leader at Uber, Apple, and TubeMogul (acquired by Adobe). During her time at Uber, she built several core ML Infrastructure platforms, including Michealangelo. She has a bachelor’s from Berkeley's Electrical Engineering and Computer Science program, where she published research with Berkeley's AI Research group. She is on a leave of absence from the Computer Vision Ph.D. program at Cornell University.
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Agent EngineeringArize Skills: Coding Agent Workflows for Traces, Evals, and Instrumentation
Two weeks ago we launched Alyx 2.0, the AI engineering agent inside Arize AX. Last week we launched the AX CLI, which made your trace data headless and… Aparna Dhinakaran Chris Cooning March 10, 2026 3 min read -
Agent EngineeringFrom UI to Terminal: Bringing Alyx’s Superpowers Into Your Coding Agent
Last week we launched Alyx 2.0, the in-app AI engineering agent for Arize AX. Alyx replaced clicking through the UI with natural language intent. The AX CLI takes… Aparna Dhinakaran Chris Cooning March 4, 2026 2 min read -
Agent EngineeringHierarchical Memory Management In Agent Harnesses
We’ve worked with thousands of customers building AI agents, and we’ve also spent the last two years building our own agent, Alyx, an in-product assistant for Arize AX.… Jason Lopatecki Aparna Dhinakaran Laurie Voss Aman Khan Chris Cooning January 29, 2026 10 min read -
AI EvaluationTesting Binary vs Score Evals on the Latest Models
Thanks to Hamel Husain and Eugene Yan for reviewing this piece Evals are becoming the predominant approach for how AI engineers systematically evaluate the quality of the LLM… Aparna Dhinakaran Sri Chavali September 24, 2025 10 min read -
Agent EngineeringOrchestrator-Worker Agents: A Practical Comparison of Common Agent Frameworks
— Technical deep dive inspired by Anthropic’s “Building Effective Agents” In this piece, we’ll take a close look at the orchestrator–worker agent workflow. We’ll unpack its challenges and… Sanjana Yeddula Aparna Dhinakaran Sri Chavali September 9, 2025 11 min read -
LLM As A JudgeEvidence-Based Prompting Strategies for LLM-as-a-Judge: Explanations and Chain-of-Thought
When LLMs are used as evaluators, two design choices often determine the quality and usefulness of their judgments: whether to require explanations for decisions, and whether to use… Sri Chavali Elizabeth Hutton Aparna Dhinakaran August 20, 2025 8 min read -
AgentsPrompt Learning: Using English Feedback to Optimize LLM Systems
Applications of reinforcement learning (RL) in AI model building has been a growing topic over the past few months. From Deepseek models incorporating RL mechanics into their training… Jason Lopatecki Aparna Dhinakaran Priyan Jindal Aman Khan July 18, 2025 15 min read -
Agent EngineeringSelf-Improving Agents: Automating LLM Performance Optimization using Arize and NVIDIA NeMo
Enterprises face a critical challenge in keeping their LLM models accurate and reliable over time. Traditional model improvement approaches are slow, manual, and reactive, making it difficult to… Aparna Dhinakaran March 18, 2025 3 min read -
Agent EvaluationArize AI Raises $70M Series C to Build the Gold Standard for AI Evaluation & Observability
In 2020, we founded Arize with a clear mission: to give teams the tools they need to understand, troubleshoot, and improve AI performance in the real world. Our… Jason Lopatecki Aparna Dhinakaran February 20, 2025 6 min read -
LLM Evalso1-preview Time Series Evaluations
Time series anomaly detection is one of the most challenging tasks we tackle at Arize. Using large language models (LLMs) for time series analysis, especially in our AI… Aparna Dhinakaran November 8, 2024 5 min read
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Arize gives AI teams observability and evals to understand and improve agent performance.
