The Setup For the past few weeks we’ve been running a two-agent workflow: our main assistant (Hermes) plans, orchestrates, and verifies, while OpenCode — a provider-agnostic, open-source AI coding...
Most MLOps content assumes abundant infrastructure: unlimited GPU time, reliable 5G, uninterrupted power, and a team that can spin up Kubernetes clusters on demand. But what if your deployment targ...
The Benchmark Blind Spot A model scores 90% on MMLU. It reasons through physics problems, parses legal documents, and writes competent Python. You deploy it for a Kenyan agritech startup — and it ...
Introduction Over the past two months, we’ve built a solid foundation in AI agent engineering — from fundamentals and the ReAct pattern through memory systems, tool calling, and multi-agent orches...
The Mobile-First Context Africa leapfrogged the desktop era — the internet arrived via SIM cards, not broadband cables. Smartphone penetration is now climbing past 50% across the continent, but th...
Why Fine-Tune? A foundation model like Llama 3 70B or Mistral generates fluent English, French, and Arabic. Ask it to write in Swahili or translate a sentence to Yoruba, and quality drops off a cl...
When Industry Meets Intelligence In July 2026, Dangote Industries Limited announced plans to invest an additional $46 billion across its refining, cement, and fertiliser businesses between 2026 an...
Retrieval-Augmented Generation (RAG) is one of the most practical breakthroughs in applied LLM engineering. By grounding model outputs in retrieved documents rather than relying solely on parametri...
The balance of power in large language models shifted decisively in 2026. With Kimi K3 released as open weights, alongside GLM-5.2, Llama 4, Qwen 3, and DeepSeek V3, the era of proprietary-only fro...
Africa’s creative industries are experiencing a digital renaissance, and artificial intelligence is emerging as an unexpected but powerful collaborator. From Lagos to Nairobi, Johannesburg to Dar e...