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Agree, and for the delivery-riders side, you and some vlose people can start making the deliveries if possible.

I don't know what requires more skills: creating Bitcoin or avoiding getting identified after all these years.


"Just when I thought I was out, they pull me back in"



In my opinion, conferences are mostly high noise low signal. My boss went to an "AI conference" last month and all the learnings he shared were things I was advocating already:

- use claude code

- evals are critical

- don't use AI everywhere

I think the conferences are more "work vacations" than work. Maybe they're useful if you think about them this way.


The truth is that no one really knows.

My approach is to "ride the wave", don't resist, just try to use it as an advantage and if not possible, adapt and look where I can keep adding value to the world.

Currently I'm trying to get my own company started because that way I can iterate the product faster using AI and if it goes well I can slowly migrate from coder to manager. I've come to terms that my days as a pure coder are coming to an end but I've been coding for at least 15 years.


Wake me up at Opus 12


Would be nice to use as an interface to interact with Claude Code.


Nice, I'll take a look. I was thinking about building a benchmark similar to the one you described, but first focusing on the negotiation between the store and the product suppliers.

Does your software also handle this type of task?


Yes, the Shopify alternative is called Openfront[0]. Before that, I built Openship[1], an e-commerce OMS that connects Openfront (and other e-commerce platforms) to fulfillment channels like print on demand. There isn’t negotiation built in but you connect to something like Gelato[2] and when you get orders on Openfront, they are sent to Gelato to fulfill and once they ship them, tracking’s relayed back to Openfront through Openship.

0. https://github.com/openshiporg/openfront

1. https://github.com/openshiporg/openship

2. https://www.gelato.com


I was eagerly waiting for a chapter on semantic similarity as I was using Universal Sentence Encoder for paraphrase detection, then LLMs showed up before that chapter :).


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