Dashboard

The real user prompts we captured this ad appearing on inside ChatGPT.

  • best embedding models for agent memory retrieval 2026

  • Building a RAG system with agent tools

  • how do i add persistent memory to a langchain agent without losing past context

  • how do i set up ragas to evaluate hallucinations on a production retrieval pipeline

  • how do you actually build a ground-truth eval dataset for a RAG pipeline when you don't have labeled data yet, is ragas good enough or should i use langsmith datasets

  • how to build episodic memory for an llm agent from scratch

  • LangChain vs open source tools for integrations

  • milvus vs pinecone for billion vector scale performance benchmark

  • my ai agent forgets everything between sessions how do i give it long term memory

  • redis or elasticsearch for ai agent context retrieval pipeline

  • redis vs oracle for caching ai agent conversation context

  • scale ai vs appen vs toloka which is actually better for fine-tuning data quality in 2026

Why does this ad win these prompts?

The prompts are the clue. The answer is the audience it is really aimed at, and the context hint quietly placing it here.

Seen 17× across our captures

We capture sponsored ads inside ChatGPT by probing it with realistic consumer prompts and recording the creative + the triggering prompt. Explore the full ad library.

Something missing, or want to work together?

Questions about the data, a brand you expected to see, partnerships, or access to the intelligence layer. We read every message.

Contact us →