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Practical architecture and development decisions for software that people can use, maintain, and adapt.
89 articles · Page 7 of 8
GGML and llama.cpp Join Hugging Face: What It Means for Local AI
GGML creator Georgi Gerganov joins Hugging Face to secure the future of local AI inference. A landmark open-source move.
Agentic AI Architecture Patterns
A guide to agentic AI patterns: ReAct loops, tool-use protocols, multi-step planning, memory, and multi-agent coordination in production.
Mixture of Experts: Sparse AI Architectures
MoE architectures explained: gating mechanisms, expert routing, load balancing, and why sparse models deliver frontier AI at fraction cost.
MiniMax M2.5: Frontier Coding for Less
Chinese startup MiniMax matches Claude Opus 4.6 on SWE-bench while charging roughly one-tenth the price per token.
Building Software That Survives the AI Wave
The SaaSpocalypse is real for some software, overblown for others. Here's what AI can't replicate and how to build for it.
GPT-5.3-Codex: OpenAI's Agentic Code Model
OpenAI releases GPT-5.3-Codex with 77.3% on Terminal-Bench 2.0, an agentic coding model partially used in its own creation.
Foundations of Transformer Reasoning
A technical deep-dive into transformer architectures, attention mechanisms, scaling laws, and emerging techniques for reliable AI reasoning.
Taxonomy of AI: From ML to World Models
A map of AI systems — machine learning, deep learning, LLMs, multimodal models, and world models — with clear definitions and comparisons.
Technical Debt: The Product Velocity Killer
Technical debt compounds silently until it dominates your roadmap. Learn to measure, communicate, and systematically reduce it.
Prompt Engineering Patterns for Production Systems
Learn 7 battle-tested prompt engineering patterns that reduce failures and improve reliability in production AI systems. Includes code examples.
Understanding Tokens and LLM Inference
Discover how LLMs process text through tokenization and inference. Essential knowledge for optimizing AI costs and prompt performance.
Designing RAG Pipelines for Production
Architecture patterns and implementation considerations for building retrieval-augmented generation systems that work reliably at scale.