Ndamulelo Nemakhavhani · AI · Cloud · Data
Field notes from building with artificial intelligence, cloud platforms, data systems, and the software connecting them.
Latest field note
Your UI is just one client now; your apps must now treat humans, LLMs, and peer agents as equal consumers.
Read the essay →Azure Monitor quietly shipped a native OTLP endpoint. Here's how to send traces, metrics, and logs to App Insights from a plain Python app — no vendor SDK, your instrumentation stays portable.
A journey inspired by the Artemis II mission—from a simple question about why we do not fall off a spherical Earth to the discovery that all energy ultimately reduces to light. Along the way, we explore gravity, the vacuum of space, engineered combustion, and the thermodynamic fate of every sound and vibration in the universe.
Corporate AI investment reached $252.3 billion in 2024 and is projected to hit $562 billion by 2026. Is this a bubble, or does it reflect a long-term valuation model that standard metrics fail to capture? This article examines the evidence from both sides.
We're all excited about AGI and its transformative promise. But what happens when the most capable AI systems remain expensive? We need to have an honest conversation about access, economics, and who actually benefits from artificial general intelligence.
Developers favor models that navigate real codebases over those that ace algorithm contests, revealing how software engineering is changing.
I led the redesign and migration of a VM-based deduplication solution to Azure Batch. Moving the workload to managed batch compute improved scalability and reduced annual client infrastructure costs by approximately $8,000.
I owned the research and training of masked language models for Tshivenda and other indigenous Bantu languages. The work expanded language-technology coverage for languages underserved by mainstream NLP systems.
I applied NLP and large language models to extract key information from regulatory documents. The workflow was designed to make review more structured, traceable, and less dependent on repetitive manual handling.
