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Foundations

How to Design Evaluators That Catch What Actually Breaks

The practical guide to code-based checks, LLM judges, and rubrics for real-world AI apps

Mar 3 • Paolo Perrone

Generate Synthetic Datasets for AI Evals

5 strategies from cold start to 450 diverse inputs in minutes

Feb 24 • Paul Iusztin

No Evals Dataset? Here's How to Build One from Scratch

Build evaluators to signal problems that users actually care about. Step-by-step guide.

Feb 17 • Paul Iusztin

Integrating AI Evals Into Your AI App

The holistic guide: From optimization to production monitoring

Feb 10 • Paul Iusztin

How to Design Python AI Projects That Don't Fall Apart

A framework-agnostic approach to modular agents, workflows, and LLM apps using the pragmatic clean architecture design.

Jan 13 • Paul Iusztin

The AI Agents Roadmap Nobody Is Teaching You

9 lessons: from workflows to planning and multimodal AI agents. From scratch. Framework free.

Dec 16, 2025 • Paul Iusztin

Stop Converting Documents to Text. You're Doing It Wrong.

How to work with multimodal agents: images, PDFs, audio, and... text.

Dec 9, 2025 • Paul Iusztin

How Does Memory for AI Agents Work?

The 4 memory types every AI agent needs

Dec 2, 2025 • Paul Iusztin

The Underrated Science of LLM Samplers

The secret sauce for balancing diversity, quality and precision

Nov 25, 2025 • Shmulik Cohen

Building Production ReAct Agents From Scratch Is Simple

I read LangGraph's implementation so that you can build your own, as AI frameworks just bloat your code.

Nov 18, 2025 • Paul Iusztin

You're Not Building Agents: Learn the Fundamentals From Scratch

Why planning is the missing piece between tool loops and true AI agents.

Nov 11, 2025 • Paul Iusztin

Tool Calling From Scratch to Production: The Complete Guide

Master the fundamentals through a deep research agent to learn to properly implement, use, and debug tools in any AI system.

Oct 28, 2025 • Paul Iusztin

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