MY CHILD IS DYING, PLEASE😭
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︎don’t forget me🥺
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please care
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︎:(
I beg you, I need food.
I kiss your hands
Help my poor child, she's dying
https://t.co/MT2Xd10Mhd
BEG YOU 😭💔
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I STILL NEED MILK 😭
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I STILL NEED MILK 😭
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I STILL NEED MILK 😭
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I STILL NEED MILK 😭
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https://t.co/Cqf0iqGIz9
$20,000,000 in test contracts as logistics giants officially replace warehouse workers with humanoid bots
Delivery titans like DPD, DHL, and FedEx have quietly placed over $20M in pilot orders for autonomous sorting units.
> These humanoid systems sort packages, scan barcodes, and handle fragile parcels continuously without taking a single break.
> Replacing human sorters reduces sorting line operational costs by up to 60% per facility.
> Logistics firms are burning cash on human labor shifts that can now be handled by automated hardware stacks.
Paying hourly wages to package handlers in 2026 is becoming a choice for companies that love wasting capital.
The entire logistics industry is swapping unionized labor for silent, non-stop machines.
Har Har Mahadev Bam Bam
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Har Har Mahadev.
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Jay Ho Devon ke Dev Mahadev
MOST PEOPLE BUILD AI AGENTS BACKWARDS.
They start with prompts, then add tools, memory, subagents, dashboards, and a graph nobody can debug.
Then they wonder why the agent is expensive, confused, and unreliable.
The better order is simple:
harness first
loop second
graph only when needed
A harness gives the model a workspace, tools, permissions, logs, and a definition of done.
A loop lets it try, fail, read feedback, repair, and stop.
A graph only makes sense when the workflow branches: approvals, parallel work, durable state, different routes, restart recovery.
A graph is not a smarter prompt.
A loop is not a production system.
A harness is not just a system prompt.
Most agents do not fail because the model is weak.
They fail because nobody defined what success means.