Saksham Dhull
Software Engineer (Team Lead), AI Agents, Wisdom AI
Bengaluru, India
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I lead the AI Agents team at WisdomAI, where I build production AI agent systems and work on agent architecture, reliability, evaluation, and efficiency. Previously, I worked at Samsung Research HQ in South Korea on multimodal AI and 5G/6G systems, and later co-founded an AI startup. My work spans AI agents, LLM systems, distributed systems, and production ML infrastructure. I hold a B.Tech. in Computer Science from IIT Delhi.
Area of Expertise
Topics
Engineering Predictable Systems with Non-Deterministic AI
LLMs are non-deterministic, but production AI agents still need to feel predictable. If two users ask similar questions, or an agent works through the same kind of problem twice, the exact wording may change, but the decisions, actions, and overall outcome should stay reasonably consistent.
This talk looks at how to build that kind of functional consistency around non-deterministic models. I’ll cover where variability enters an agentic system, how it compounds through reasoning and tool use, and some practical ways to keep behaviour within predictable bounds using constrained execution, state management, validation, retries, tool design, and evaluation.
Designing Tools for Agents
Most APIs and tools are designed for and by the developers. AI agents don’t use them the way humans do. Small choices around tool granularity, naming, schemas, descriptions, outputs, and error handling can have surprisingly effects on how well an agent reasons and acts.
This talk looks at patterns that work and patterns that don’t when designing tools for AI agents. We’ll cover when to split or combine capabilities, how much logic should live inside a tool, how to return useful information without polluting context, how to design for failures and retries, and how to evaluate a given tool. The goal is to build tools that make agents reason, work and progress better.
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