About Belgavi.AI Lab

A personal technical reference built by Sandeep Belgavi Ashok Kumar, a software architect working at the intersection of scalable distributed systems and modern AI. Views are my own and do not represent any employer, past or present.

What this site is

Belgavi.AI Lab collects deep technical material in two complementary forms: written explanations that aim for concrete numbers and working examples over marketing claims, and interactive single-file labs that run in a browser with no install, no build step, and no JavaScript framework dependency.

Topics span LLM internals, agent protocols (MCP, A2A, ADK, AP2), Apache Cassandra, distributed consensus, system design, networking, security, observability, and the realtime media stack (WebRTC, HLS, DASH).

Who writes it

Sandeep Belgavi sets the editorial direction and maintains this site. Articles, illustrations and labs may be produced with AI assistance. Automated checks cover selected links, metadata and lab behavior; they do not independently verify every technical statement. A page describes specific tests or measurements when evidence is available. Illustrative examples and synthetic labs should not be treated as production benchmarks. Corrections are welcome through the contact page.

If you find an error, a correction is genuinely welcome and will be fixed — see the contact page.

Why it exists

Most explanations of these systems stop at the level of a diagram. The intent here is to go one level lower: show the arithmetic, show the failure mode, show the mechanism running. The labs exist because some ideas — attention head behaviour, consensus under partition, quantization error — are far easier to understand when you can move a slider and watch the numbers change.

Contact

Questions, corrections, collaboration, or speaking: get in touch. Typical response time is 2-3 business days.