Summary
According to a post on X by @DataScienceDojo, the Agentic AI Conference, held online on November 9–10, has added a panel titled "How Do Agents Work, and How Should They Work?" The panel features Luis Serrano (Serrano Academy), Chris McCormick (InnerWorkings AI), Jay Alammar (Cohere) and Joshua Starmer (StatQuest). According to the post, the speakers plan to walk through the model, context, tools and results loop, and discuss where retrieval, memory and planning help or break. The snippet is cut off before the full description of the session.
AI-assisted summary based on the listed source.
What happened
New panel: Luis Serrano (Serrano Academy), Chris McCormick (InnerWorkings AI), Jay Alammar (Cohere) and Joshua Starmer (StatQuest) will discuss "How Do Agents Work, and How Should They Work?" They plan to walk through the model, context, tools and results loop, where retrieval, memory and planning help or break,...
Why it matters
The session focuses on how retrieval, memory and planning behave inside AI agent systems, which is relevant to builders and teams working on agents. Those who want a clearer view of where these components work well and where they fail may find the panel useful. The source does not provide further detail, so the full agenda and speaker materials are the next things to check.
Signal Intelligence
Signal Strength 81%
Technical label WATCH
Public Interest 38
Category CREATOR TOOLS
Reader Depth TECHNICAL
Signal Strength reflects source quality, relevance, freshness and evidence. Public Interest helps organize discovery; it is not proof of truth.
Public Interest components
Recognizable Entity Score 0
Practical Impact Score 38
Novelty Interest Score 94
Consequence Score 10
Curiosity Score 52
Shareability Score 52
Why this is here
VQV surfaced this signal because it is recent, relevant to AI Search, connected to Scobleizer News Pulse (X).
