Woyce
A plain-language guide to reasoning models — how they differ from standard LLMs, why they spend extra compute 'thinking' before answering, and when that tradeoff is worth it.
A practical look at whether long-context language models make retrieval-augmented generation obsolete, and when each approach actually makes sense.
A technical explainer on speech-to-speech voice AI — how it replaces the traditional three-stage voice pipeline with a single model, and what that changes for builders.
A practical guide to building evaluation suites for AI agents, covering task design, grading methods, metrics that matter, and the traps teams fall into.
A practical guide to what LLM observability means, why traditional monitoring breaks down for AI agents, and how to instrument, evaluate, and debug LLM-powered systems in production.
A practical breakdown of what it actually costs to self-host an open-weight LLM — hardware, utilization, and engineering time — compared to paying per token for an API.
A practical comparison of prompting, retrieval-augmented generation, and fine-tuning for customizing large language models, with guidance on when each approach actually pays off.
What synthetic data actually is, how it's generated, and why teams building AI agents increasingly rely on it instead of (or alongside) real-world data.
A practical breakdown of the EU AI Act's risk categories, obligations, and timeline for any company that sells or embeds AI-powered software into the European market.
A practical walkthrough of how India's Digital Personal Data Protection Act applies to AI systems, and what builders and businesses need to change.
What ISO 42001 actually requires, who needs it, and how it differs from security and privacy certifications like SOC 2 and ISO 27001.
A practical explainer on prompt injection attacks against LLM applications: how they work, why they're hard to fix, and what builders can do to reduce the risk.