WordloopAI-Native
How we build with and for AI — both inside the product and inside the development loop.
AI-Native
Wordloop is AI-native in two directions: the product runs on AI (transcription, recap, embedding), and the team builds with AI (agents write substantial code, read documentation programmatically, and contribute to reviews). Both directions demand a stance — on how models are integrated, how agents consume our interfaces, and how we keep a human on the hook for outcomes.
AI Engineering
Prompt engineering, evaluations, agent design, RAG, and context engineering — the disciplines that make AI features production-grade.
Agent-Native Systems
Making APIs and docs AI-consumable: MCP, llms.txt, structured metadata, and the interfaces that let agents work alongside humans.
Related reading: Hexagonal Architecture — the structural choice that, more than any other, determines how effectively an agent can contribute to a codebase.