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Discussion on "Agentic AI Engineering in Practice: How AI Engineers and Forward-Deployed Engineers Build with Claude Code, Codex, and Gemini" | Hashnode

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Agentic AI Engineering in Practice: How AI Engineers and Forward-Deployed Engineers Build with Claude Code, Codex, and Gemini

A practical, three-tool guide to the AI-native software development life cycle (SDLC): Plan, Design, Build, Test, Deploy, Maintain, reimagined for agentic coding. In March 2025, a small nonprofit rese

Sep 4·40 min read·freecodecamp.orgRead the article

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Written by

Rudrendu Paul

@rudrendupaul · San Francisco, USA

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I am an Applied AI/ML and Marketing Measurement Science leader with 15+ years of building and scaling applied AI and machine learning products at Fortune 50 companies. I specialize in Causal Inference, Experimentation, Agentic AI systems, and enterprise AI strategy, applied to Retail Media Networks (RMN), Ads, Adtech, Martech, CPG, and E-Commerce. Published author with Springer Nature, Elsevier, ICML (Top 3 AI/ML Conference), and IEEE, and a regular contributor to leading AI/ML and analytics publications (views are my own)

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Brian · AI News

Sep 23

The Plan Design Build loop is where agents earn keep. Tool choice is secondary to a clear stop condition and a test that the agent cannot rewrite to look smart.