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ADK Go Graph Workflow integrates with Google Research Harness²

By PulseAugur Editorial · [1 sources] ·

This article details the integration of the ADK Go Graph Workflow with Google Research's Harness² framework, focusing on Phase 4 and Phase 5 developments. The integration aims to create a standardized bridge, the BenchmarkAdapter, to enable Harness²'s recursive optimization engine to work with the Go Agent. Key design philosophies, including the "Zero-Leakage Barrier" to prevent memorization of answers and "Behavioral Trajectory Contrast" using OpenTelemetry Spans, are explained to ensure the agent's real-world performance and prevent overfitting to benchmarks. AI

IMPACT This integration could lead to more robust and generalizable AI agents by preventing overfitting and improving evaluation methodologies.

RANK_REASON The article details technical integration and design philosophies for an AI agent framework, aligning with research and development in the field. [lever_c_demoted from research: ic=1 ai=1.0]

Read on dev.to — LLM tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

ADK Go Graph Workflow integrates with Google Research Harness²

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The article details technical integration and design philosophies for an AI agent framework, aligning with research and development in the field. [lever_c_demoted from research: ic=1 ai=1.0]
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High
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9 days old
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COVERAGE [1]

  1. dev.to — LLM tag TIER_1 English(EN) · Evan Lin ·

    [Agent Platform in Action (8)] When ADK Go Graph Workflow Meets Google Research Harness (Part 2): Integrating Phase 4 Eval Datas

    <p><a class="article-body-image-wrapper" href="https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.us-east-2.amazonaws.com%2Fuploads%2Farticles%2Fyxdjol1nvvsed1qzztso.png"><img alt="Harness² Part 2:…

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