Inside Claude’s Head: Lessons from a Leaked System Prompt
Author(s): Mehdi Zare Originally published on Towards AI. By an ML Engineer who’s always learning, across software, finance, consulting, and marketing I recently got my hands on what looks like Claude’s real system prompt. These are the fundamental instructions that tell this …
Why Fine-Tuning is the Secret Sauce for ML Engineers in 2025
Author(s): Mehdi Zare Originally published on Towards AI. Why Fine-Tuning is the Secret Sauce for ML Engineers in 2025 I’ve worn many hats in my career — from writing code at a software startup, to crunching numbers in finance, advising clients as …
From Black‑Box to Crystal‑Clear: My Hands‑On Guide to LLM Observability
Author(s): Mehdi Zare Originally published on Towards AI. I still remember the first time I deployed a complex LangChain app and had no clue why it behaved so unpredictably. It felt like trying to debug a black box. Over time, I learned …
Memory Management Strategies and Tools for AI Chatbots and Agents
Author(s): Mehdi Zare Originally published on Towards AI. Building an AI chatbot that can hold a meaningful conversation over time isn’t just about choosing a powerful language model — it’s also about giving it a memory. As a data scientist transitioning into …
Evaluating Agentic LLM Applications: Metrics and Testing Strategies
Author(s): Mehdi Zare Originally published on Towards AI. Agentic LLM applications — think ChatGPT-like agents that plan steps, use tools, and make autonomous decisions — are powerful but notoriously hard to evaluate. Unlike a single-step LLM response, an agentic LLM might perform …
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