Tags: system-design
All the articles with the tag "system-design".
Dense vs MoE - Choosing Between Dense Models and Mixture of Experts
Updated: at 10:59 AMDense vs MoE explained: how dense and Mixture of Experts models differ in compute, memory, latency and cost, and a practical rule for when to run each, including on local hardware.
AI Engineering - The Discipline of Building Production AI Systems
Published: at 09:00 AMAI Engineering bridges the gap between AI research and production systems. Learn the core principles, patterns, and practices that enable teams to build reliable, scalable AI applications that deliver real business value—not just impressive demos.
What Is Agentic Engineering - The Complete Guide to AI-First Software Development
Updated: at 08:59 AMWhat is agentic engineering? Understanding the discipline of building systems where AI agents work autonomously. Learn how agentic engineering differs from traditional development, why teams using it ship 5-10x faster, and how to get started with agentic engineering today.
The Chasm between Building an AI Agent and a Reliable One
Updated: at 03:21 PMUnderstanding the fundamental difference between building a demo AI agent and building a production-ready reliable one. Exploring the reliability chasm and how defensive architecture, pre-action checks, post-action verification, and proper turn transitions are essential for creating agents that work consistently in real-world scenarios.
AGI is an Engineering Problem
Updated: at 03:29 PMLLM models are plateauing, but true AGI isn't about scaling the next breakthrough model—it's about engineering the right context, memory, and workflow systems. AGI is fundamentally a systems engineering problem, not a model training problem.
What is Context Engineering? (The Evolution Beyond Prompt Engineering)
Updated: at 10:59 AMUnderstanding context engineering as the next evolution in AI system design, exploring its fundamental differences from prompt engineering and practical techniques for building robust AI agents.
Building Multi-Agent Research Systems - Lessons from Anthropic's Architecture
Updated: at 12:59 AMHow multi-agent research systems work and what it takes to build one: the orchestrator-worker pattern, prompting subagents, evaluation, token costs, and production pitfalls, drawing on Anthropic's published design.
Prompt Engineering- The Critical Skill for Building Reliable Agentic Workflows
Updated: at 11:29 AMAn exploration of why prompt engineering is essential for creating reliable AI agents - covering deterministic behavior in probabilistic systems, tool use precision, chain-of-thought integrity, and practical techniques for measuring effectiveness.
Single Agent vs Multi-Agent - Which AI Architecture Do You Need?
Updated: at 03:21 PMWhat is the difference between single agent vs multi-agent systems? Understanding single agent architecture versus multi-agent AI systems. Learn when to use each approach, compare their capabilities, and decide which architecture is best for your AI project.
Deterministic vs Probabilistic - What the Difference Means for AI Applications
Updated: at 03:21 PMDeterministic vs probabilistic explained: the same input always gives the same output in one, and only a likely output in the other. What that means for building, testing and designing AI applications, and when to combine both.