Evaluating LLM outputs when you do not have a gold-standard test set
Practical strategies for validating LLM performance in resource-constrained environments where manual labeling or gold-standard datasets are unavailable.
1 August 2026
ML infrastructure engineer at a Lagos-based health-tech startup, focused on deploying LLMs on constrained hardware. Authored the open-source quantisation toolkit used by 40+ African AI teams.
Practical strategies for validating LLM performance in resource-constrained environments where manual labeling or gold-standard datasets are unavailable.
1 August 2026
Grounding prevents hallucination but naive grounding sacrifices the reasoning quality that makes LLMs useful. The architecture that achieves both — faithful to sources, intelligent in synthesis — requires careful design of how context is provided and constrained.
22 July 2026
Evaluating LLM outputs is harder than evaluating deterministic software outputs. The pipeline that works — one that catches regressions, measures what matters, and scales with the application — requires specific design choices from the beginning.
22 July 2026
Retrieval-augmented generation is straightforward in demos and fragile in production. The gaps are almost always in chunking, retrieval quality, and context assembly — not in the language model. Here is what the production version looks like.
22 July 2026
An LLM agent that calls external tools is a distributed system. Its reliability is bounded by every tool it calls, every timeout it can hit, and every error it must handle gracefully. Building reliable agents requires systems thinking, not just prompt engineering.
22 July 2026
Learn how to design an LLM-powered customer support bot that handles common queries autonomously while detecting frustration, complexity, and edge cases that warrant a smooth handoff to human agents. This guide covers intent classification, escalation triggers, context preservation, and the handoff UX that keeps customers calm.
19 July 2026
Synthetic data generated by LLMs can unblock model training when real labelled data is scarce, expensive, or sensitive — this guide walks through the practical techniques, quality controls, and pitfalls that matter in production
19 July 2026
LLM API costs can spiral quickly without deliberate instrumentation. This article covers the full stack of cost tracking — from per-request token accounting to team-level budget enforcement — with concrete code patterns you can deploy today
16 July 2026