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Speaker

Nimrod Hauser

Nimrod Hauser

Building Agentic Developer Tools @ Baz

Kfar Saba, Israel

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Nimrod is a Principal Engineer at Baz, building AI-powered code review agents. A “jack of all trades” across backend, data engineering, and data science, he has worked at the intersection of software and data throughout his career. He began as a data analyst in the military, helped lay the foundations of Salesforce’s Einstein platform, and later became the first data scientist at cybersecurity startup BlueVoyant. He went on to lead data and architecture at Solidus Labs in the crypto-regulation space before joining Baz. Nimrod thrives on building systems from scratch and turning ideas into scalable products.

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Area of Expertise

  • Business & Management
  • Information & Communications Technology

Topics

  • Data Science
  • Data Engineering
  • Databases
  • All things data
  • Big Data Analytics
  • Data Platform
  • Big Data
  • Database
  • Data analysis
  • Data Analytics
  • Data Governance
  • Data Visualization
  • Data Management
  • Data Warehousing
  • Data Science & AI
  • Data Architecture
  • AWS Data & AI
  • Big Data Machine Learning AI and Analytics
  • Analytics and Big Data
  • Developer Tools
  • Software Deveopment
  • Backend Development
  • Software Development
  • Crypto
  • crypto trading
  • blockchain
  • Natural Language Processing (NLP)
  • Machine Leaning
  • Machine Learning & AI
  • Machine Learning and AI
  • Machine Learning Engineering
  • PostgreSQL
  • SQL
  • functional programming
  • Software Design
  • Software testing
  • software architecure
  • Software Engineering Management
  • Software Engineering

Sessions

Building a Retrievable Codebase Memory Model

Accurately modeling module relationships in a codebase is crucial for transitioning manual development tasks into agentic workflows. This session presents research on leveraging graph-based representations of source code to create structured, persistent memory of codebases for developer-agents.

We will examine the value of systematic extraction and parsing of code relationships using Abstract Syntax Trees (ASTs) for extracting relational metadata, as-well as pandas-based data aggregation methods for managing large-scale relational data. Further, we discuss how graph theory techniques including centrality measures and clustering (implemented with NetworkX) can be employed to identify critical software modules and dependencies.

This session references and builds upon previous research, including RepoAgent (arXiv:2402.16667), ContextModule (arXiv:2412.08063), and open-source projects such as Potpie and Blarify, highlighting differences, strengths, and areas for improvement.

Last, we'll explore the integration of the memory model with an agentic architecture focusing on fine-tuning and parameter stabilization for consistent module summarization to improve agent-to-agent communication.

Nimrod Hauser

Building Agentic Developer Tools @ Baz

Kfar Saba, Israel

Links

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