Decoding AI Magazine | Paul Iusztin | Substack

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Start Here: Your Map to Decoding AI

The AI Engineering Command Center

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Build your Second Brain AI assistant

Feb 6, 2025 • Paul Iusztin

Stop Building AI Agents

Jun 26, 2025 • Hugo Bowne-Anderson

Context Engineering: 2025’s #1 Skill in AI

Jul 22, 2025 • Paul Iusztin

From 0 to Pro AI Agents Roadmap

May 31, 2025 • Paul Iusztin

Decoding AI Magazine

Decoding AI Magazine

Join for content on designing, building, and shipping AI software that works. Learn AI engineering, end-to-end, from idea to production. Every Tuesday.

The latest from

Paul Iusztin

Start Here: Your Map to Decoding AI

Anca Ioana Muscalagiu

Your Agent's Reasoning Is Fine - Its Memory Isn't

Recent posts

Scaling to 120+ AI Agents Without Losing Control

How two-tier orchestration keeps multi-agent systems debuggable

Mar 5 • Lucian Lature

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

I Spent 9 Months Building an Agentic AI Engineering Course

Google is already recommending it alongside Coursera, DeepLearning.AI and Oxford.

Feb 26 • Paul Iusztin

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LLM Engineer's Handbook

Master the art of engineering Large Language Models from concept to production.

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Agentic AI Engineering Guide

A 6-day email course to reveal the 6 critical mistakes that silently destroy agentic systems.

Agentic AI Engineering

Become an Agentic AI Engineer with a production-ready portfolio.

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Access real-world guides. From the PoC purgatory to shipping AI products that work.

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

Case Studies

Scaling to 120+ AI Agents Without Losing Control

How two-tier orchestration keeps multi-agent systems debuggable

Mar 5 • Lucian Lature

Behind the Scenes of AI Observability in Production

What actually works after 6 months of trial and error

Feb 3 • Alejandro Aboy

Your Agent's Reasoning Is Fine - Its Memory Isn't

Using GraphRAG to build a Production Engineer agent that knows dependencies, incidents, and ownership.

Jan 20 • Anca Ioana Muscalagiu

From 100+ AI Tools to 4: My Prod Stack

How simplicity beats complexity in real AI systems

Dec 30, 2025 • Paul Iusztin

We Killed RAG, MCP, and Agentic Loops. Here's What Happened.

A brutally honest case study of building our vertical AI agent and shipping it to production.

Dec 23, 2025 • Paul Iusztin

Projects

Getting Agent Architecture Right

Designing real-world AI agents with MCP without burning your time, money, and SANITY.

Sep 6, 2025 • Anca Ioana Muscalagiu

Build with MCP Like a Real Engineer

Hands-on code for an enterprise AI PR Reviewer by unifying GitHub, Slack, and Asana through MCP.

Aug 30, 2025 • Anca Ioana Muscalagiu

Why MCP Breaks Old Enterprise AI Architectures

Build from scratch an AI PR reviewer integrated with GitHub, Slack and Asana that scales within your organization.

Aug 19, 2025 • Anca Ioana Muscalagiu

The King of Multi-Modal RAG: ColPali

Query your rich visual PDFs under a RAG web app

Jun 5, 2025 • Juan Ovalle

From 0 to Pro AI Agents Roadmap

Theory to API Deployments and LLMOps

May 31, 2025 • Paul Iusztin

Access real-world guides. From the PoC purgatory to shipping AI products that work.

Guests

Behind the Scenes of AI Observability in Production

What actually works after 6 months of trial and error

Feb 3 • Alejandro Aboy

The Realistic Guide to Mastering AI Agents in 2026

From zero to production in 6–9 months. What to learn, what to skip, and why most tutorials fail.

Jan 6 • Paolo Perrone

The Underrated Science of LLM Samplers

The secret sauce for balancing diversity, quality and precision

Nov 25, 2025 • Shmulik Cohen

Stop Launching AI Apps Without This Framework

A practical guide to building an eval-driven loop for your LLM app using synthetic data, before you have users.

Oct 30, 2025 • Hugo Bowne-Anderson

Building Reliable AI Agents with Durable Workflows

How to make agents resilient to any failure

Oct 23, 2025 • Peter Kraft and Paul Iusztin

Newsletter

I Spent 9 Months Building an Agentic AI Engineering Course

Google is already recommending it alongside Coursera, DeepLearning.AI and Oxford.

Feb 26 • Paul Iusztin

Thank You for Supporting Decoding AI

Roadmap updates and the new DAI chat.

Feb 19 • Paul Iusztin

The Realistic Guide to Mastering AI Agents in 2026

From zero to production in 6–9 months. What to learn, what to skip, and why most tutorials fail.

Jan 6 • Paolo Perrone

November Highlights: From Foundations To Production AI

AI Agents series finale. Controlling LLM output. Vertical AI agents & The Evals series.

Dec 18, 2025 • Paul Iusztin

Being too passive started to bother me

Finally, officializing the Decoding AI Magazine chat.

Nov 26, 2025 • Paul Iusztin

Access real-world guides. From the PoC purgatory to shipping AI products that work.

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