The Era of Throwing Frontier Models at Everything Is Over
The Economics of Agents: Why GPT-6 Luna and DeepSeek V4.1 Flash class models matter more than you think
Ndamulelo Nemakhavhani · AI · Cloud · Data
Systems worth understanding.
Field notes from building with artificial intelligence, cloud platforms, data systems, and the software connecting them.
Latest field note
MCP Gateway on Azure APIM: Lessons & Tips
Azure API Management service also known as APIM is a gateway that centralizes authentication and request routing for backend services, simplifying security and access control. In the age of LLMs, MCP Servers and Agents, It is a crucial component for managing access and ensuring safe access to the benefits of generative AI.
Read the essay →Recent writing
All 68 articlesWe have not accounted for the true costs of AI coding
It is time to face the true costs of AI coding. Reliable results require compute, supervision, review and maintenance that our productivity estimates often leave out.
What VS Code Remembers on Your Mac
VS Code stores configuration, extension state, workspace state, local file history, plugins, and logs across several locations on macOS. This post maps those directories, explains what they reveal, and separates local editor state from GitHub Copilot CLI and cloud data.
Discussing the Trust Planes of Autonomous AI Work
How to establish trust in autonomous AI systems through identity, secrets management, and continuous assurance.
Stop Prompting Your Agents to Behave: Use Sandboxing Instead
Prompts can shape what an AI agent tries to do. Sandboxing and capability controls determine what it can actually do.
Selected work
View all projects
Azure Batch Migration for Deduplication Workloads
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.
Language Models for Tshivenda and Bantu Languages
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.
Regulatory Document Intelligence
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.