Large language models are rapidly moving beyond the chat window, and two recent videos illustrate just how far their capabilities now reach. In a new OpenAI YouTube video, "Build custom site annotations with ChatGPT," developers are shown how to add annotation controls and suggested prompts directly to a website. Paired with WebMCP, these features let users edit scenes and enrich expense records using context their ChatGPT agent already understands, turning passive pages into interactive, AI-assisted workspaces.
H2O.ai takes a broader view in "LLM Applications: Conversational AI, Document Intelligence & Text-to-SQL," arguing that language models are far more than conversational tools. The same underlying technology can read contracts and invoices to pull out structured data, translate plain-language questions into working SQL queries, and sustain multi-turn dialogue that remembers context, follows up on intent, and escalates when it reaches its limits.
Together, these posts point to a common theme: LLMs are becoming practical infrastructure. OpenAI's demonstration focuses on embedding agentic assistance into everyday web interfaces, while H2O.ai maps the wider landscape of document intelligence and database access. For builders and businesses alike, the message is clear—the value of language models lies not only in conversation, but in their ability to act on context, extract
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