Part 4 of 5. If you publish an agent project today, you are caught between two forces. The interesting behaviour lives in the cloud - Foundry models, Foundry IQ retrieval, the Agent Service memo...

Large language models now write code straight from a prompt, but the specification in between is never checked, and a model asked to judge its own work brings the same blind spots to the review. We b...

Part 3 of 5. Most multi-agent demos have a quiet secret: the human's decisions change nothing. You approve an artifact, reject another, pick a direction at a fork - and the next agent runs with ...

On-Device LLMs Are Starved for Memory Intelligence The shift toward on-device language model inference is accelerating. Platforms like Microsoft's Foundry Local, Ollama, and llama.cpp now make it p...

Part 2 of 5. In Part 1 the loop ended at a verification gate. This post is about why that gate is not a confirmation dialog - it is the core mechanic, the reliability story, and the thing that l...

The first mistake we make with AI is not technical. It is linguistic. We say the model reads the prompt, then we build systems as if that sentence is true. It is not. The model does not consume t...

We are nine software engineering students at the Egyptian Chinese University in Cairo. When we got our project brief, we noticed a gap that bothered us: Python is the most widely used language in AI ...

Artificial Intelligence is rapidly evolving beyond traditional chatbots. Today, developers are building intelligent systems where multiple AI agents collaborate, retrieve knowledge, and solve problem...

Part 1 of 5 Building a multi-agent demo is the straightforward part. Building one where you can prove - live, with judges watching - that the agents reasoned, retrieved grounded context, called ...

The Challenge Microsoft Reactor invited three individuals to compete in a live coding battle: build something that shows what reasoning agents can do, in front of a streaming audience, in roughly t...