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2026

The Cognitive Engine: Choosing the Right Reasoning Loop

Part 1 of the Engineering the Agentic Stack series

Building production AI agents is no longer about prompt engineering—it's about system engineering. The difference between a demo that impresses and a product that delivers comes down to one critical decision: how your agent thinks.

This post introduces three reasoning loop architectures and shows you how to choose between them. I'll use a production-grade Market Analyst Agent as the running example, with code you can use today.

mHC: How DeepSeek Scaled Residual Connections Without Breaking Training

The success of modern deep learning rests on a deceptively simple idea: the residual connection. Yet after a decade of stacking layers deeper and deeper, researchers at DeepSeek asked a different question—what if we could scale width instead? Their answer, Manifold-Constrained Hyper-Connections (mHC), solves a fundamental instability problem that has blocked this path for years.

This article breaks down the evolution from basic residuals to mHC, explaining why each step was necessary and what makes DeepSeek's solution work at scale.

Enterprise RAG Challenge 3: Winning Approaches for Autonomous AI Agents

The Enterprise RAG Challenge 3 (ECR3) just concluded, and the results reveal powerful insights for building production-grade AI agents. Out of 524 teams and over 341,000 agent runs, only 0.4% achieved a perfect score—making this one of the most demanding benchmarks in the field. With the leaderboard and solution write-ups now public, I analyzed the winning approaches to distill the patterns that separated top performers from the rest.

This article breaks down what ECR3 is, what tasks were involved, and how the best teams solved them.

The Complete Guide to LLM Fine-Tuning in 2025: From Theory to Production

Fine-tuning has become the secret weapon for building specialized AI applications. While general-purpose models like GPT-4 and Claude excel at broad tasks, fine-tuning transforms them into laser-focused experts for your specific domain. This guide walks you through everything you need to know—from understanding when to fine-tune to deploying your custom model.