i've never had situations where i prompt and had to go out for coffee or a walk or drive. one shotting - your first prompt. perhaps.
but like a person - when the possibility of going off in the wron g direction is so high, i've always had 1 - 2 line prompts, small iterations much more appealing. The only times i've had to rollback would be when i run out of credits, and a new model cant deal with the half baked context, errors, refactoring.
Rye allows you to even enter shipping info and pay for the product. But I can't help but feel it hasn't got the traction it deserves.
1) Are there plans to allow Devs to do the same?
2) why wouldn't you open the limit beyond 1000 free as long as you are making a rev share
3) does this pick from Shopify products/stores?
Imo the agentic loop isn't really closed unless you allow agents to pay and paywalls today aren't agent friendly. Tokenized cards, 16 digital cards. Perhaps but this involves high trust from users. Which means you are left with guiding users to the link and hoping they buy the product.
4) partnering with merchants where cards are already tokenized maybe your best converting potential customer base. But it's easy to do evil here, or loose trust without guardrails.
5) I would come up with a process to incentivize adding products to the ecosystem. However tiny the reward.
Lot of opportunity. Nice pitch. Good luck!
Would try this out of you can increase the 1k limit to something that is a win:win
Rye is an awesome company! They're in the universal checkout space now, stay tuned for a Rye + Channel3 demo in the next week :) We think the combo of product discovery with Channel3 and universal checkout is the future of commerce. To answer your questions:
1. Channel3 doesn't support shipping/payments, but there are a lot of great companies that do, so Channel3 + universal checkout is a full-fledged e-comm site.
2. We hope our pricing ($7/1000 req) is low enough that any reasonably-converting store won't need to worry about it. Average e-commerce order value is $180, so at 5% commissions you need <1 sale per 1000 queries. We're cheaper than any alternative, and, with rev share, we pay you to use us! (+ vector store is expensive :) )
3. We do have shopify stores on our platform
4. An interesting idea! We're excited to see how agentic commerce evolves, and for now we're just trying to build the best discovery solution out there.
As a consumer I'm asking myself why not just make an extension. I can see myself trying and picking 2 or more browser addons to to turbo charge + chat with any page.
From a founder hat, I can see why the code base is a moat, hard problem. I hope the effort is worth the cost.
Yes, in the long run, owning the underlying codebase would allow us to have more control and provide better user experience. (Very similar to cursor forking vscode)
Your first 2 examples on your readme involve single agents. These are a waste of time. We don't need yet another llm api call wrapper. An agentic system with just 1 tool / agent is pointless.
Thankfully your third example half way down does have an eg with 3 agents. May have helped to have a judge/architect agent.
Not clear about the infra required or used.
Would help to have helper functions to get and set session state/memory. Being able to bootstrap from json could be a good feature.
Would help to have diff agents with diff llms to show that you have thought things through.
Why should spawning 1000's of agents even be in your benchmark. Since when did we start counting variables. Maybe saying each agent would take X memory/ram would suffice - because everything is subjective, can't be generalized.
Consider a rest api that can do what the examples did via curl?
Would have been good if the familiar navbar would have been retained. Btw /show gave 404. Trivial to support those urls. The filters were too tough to find.
but like a person - when the possibility of going off in the wron g direction is so high, i've always had 1 - 2 line prompts, small iterations much more appealing. The only times i've had to rollback would be when i run out of credits, and a new model cant deal with the half baked context, errors, refactoring.
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