Unfortunately, no one cares 😭
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we’ll remind you
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Scabies has spread all over my child's body I am worried about my baby girl😭
https://t.co/FLk3iM7URh
Multi-agent systems are slow because most people still build them like a straight line.
Step one waits for step two.
Step two waits for step three.
Even when half the work has no reason to wait.
That is the whole problem graph engineering fixes.
If one agent needs to summarize a document and another needs to check the weather, those are not two steps in a chain. They are two independent nodes.
The test is simple:
Does the next task actually need the previous task’s output?
If yes, keep the edge.
If no, run it in parallel.
That one question can turn a 40-step agent from five minutes into fifteen seconds without changing the model at all.
The bottleneck was never intelligence.
It was the shape of the workflow.
A good orchestrator does not do the work.
It draws the graph: which nodes run alone, which nodes wait, which outputs get merged, and where the final decision happens.
That is the shift.
You stop writing one agent that does everything.
You start designing the dependency structure the agents move through.
Allah
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Allah
♥️ I LOVE ALLAH♥️
#خاتم_النبیین_محمدﷺ#درود_وقرآن
ONE OF CLAUDE'S DEVELOPERS TOLD ME:
"YOU'RE USING AI AT 5%."
I expected some crazy setup.
It was just a folder with text files.
Then he opened the graph.
Thousands of notes. Everything connected.
"I didn't link any of this. Claude did."
Then he typed:
where am i contradicting myself?
10 seconds later it returned old notes, dates, and quoted his own words back to him.
He laughed:
"No friend will ever tell you this. But this thing will."
That changed how I think about AI.
Most people use it like a chatbot.
A few use it like a mirror.
Allah
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Allah
Allah
Allah
Allah
Allah
Allah
Allah
Allah
♥️ I LOVE ALLAH♥️