@gippp69 This is one of those lessons that sounds obvious until you see the token bill.
People keep adding agents because they can, when a simple tool loop wouldโve done the job. Start simple, measure where it breaks, then add complexity.
@David_TornAI The underrated part is being able to work from your own sources instead of relying on whatever the model already knows.
That turns NotebookLM from a summarizer into a pretty serious research workflow.
@yuaan1in@NuphosAI This is the direction AI-native DevOps should be heading.
Giving an agent AWS access is one thing. Giving humans and agents a shared place to investigate, act, and build context together is a much bigger shift.
@Guronnimo@the_real_ori Going from DR 0 to 27 in just 4 weeks is wild.
This is the kind of compounding that makes early SEO worth paying attention to. Small wins stack up fast when the distribution engine is actually working.
@techluisenzo This is actually a pretty interesting use case for Claude.
The big win isnโt just generating videos. Itโs connecting the research, scripting, production and publishing into one repeatable system.
Thatโs where AI-powered channels get interesting.