A research agent can pull from YouTube, web search, and public social content simultaneously, though platform access varies. YouTube and web search are most accessible; social platforms have restrictions that affect depth of retrieval.
Googling is reactive — you search when you remember to. A research agent is proactive — it monitors sources on a schedule, synthesizes across many of them simultaneously, and delivers intelligence before you even know you needed it.
Build a research agent with three inputs: sources to monitor, topics that define relevance, and the output format you want. Start with three to five sources, run it for a week, then refine before adding complexity.
A research agent monitors where your audience asks questions, cross-references what competitors are covering, and surfaces the gaps — topics with real demand and insufficient quality answers — as your next content opportunities.
A competitive intelligence agent monitors what other educators in your niche are publishing and launching, synthesizing the signal into a weekly report that surfaces trends, gaps, and positioning shifts — without hours of manual research.
A research agent applies the relevance rules you configure — which sources to monitor, which keywords signal importance, and what to exclude. The quality of what it delivers depends directly on how specifically you define what matters.
A morning intelligence agent scans your chosen sources overnight and delivers a formatted summary before you start your day — covering AI news, competitor moves, and niche trends in a 10-minute read.
A research agent automatically scans sources on a schedule and delivers a curated summary of what's relevant to you — replacing the daily scroll with a morning briefing that takes 10 minutes instead of 90.
Shift from teaching the output to teaching the judgment. If AI generates what your lesson used to teach, your lesson's new job is helping students evaluate and edit AI output — not replicate the manual process.
Write the original problem your course was built to solve, describe how it's changed in 2026, then ask Claude whether your course structure still addresses it — or whether the solution has drifted from the problem.