u/AdEfficient8374

Is anyone experiencing issues with the chat widget?
I connected my knowledge base and created an All-in-One widget, but when I try to test it, it does not work. I am not sure what the issue is.

The order in which messages appear is also reversed. Instead of recent messages appearing at the bottom, they appear at the top of the chat window. And I do not get any valuable response from the bot, even though my knowledge base is connected.

Any help?

Saw this data from Promptwatch, and it's worth a look if you're paying attention to AI search traffic.

Reddit held a steady ~3.8% share of ChatGPT Search citations from July 18 to August 7. On August 14, that share fell to under 1% and hasn't recovered; the Aug 14-17 average is sitting at 0.5%. That's an 86% drop, and it happened almost overnight.

The interesting part: it's not a slow bleed like what's happening in Google AI Overviews and AI Mode (down 11% and 30% respectively over the same stretch, but gradually). This is a step change, and it lines up with a query fanout update ChatGPT made on August 8.

Two things I'd want to know before drawing conclusions: whether this is an actual shift in ChatGPT's source-selection logic, or a data collection artifact on Promptwatch's end. They flag that possibility themselves. Second, whether the drop is broad across Reddit or concentrated in specific subreddits/topics, that tells you if OpenAI deprioritized Reddit as a source category or just changed how it weights certain kinds of threads.

If you're doing anything GEO-adjacent, this is the kind of shift that can quietly tank referral traffic you didn't even know you were getting from AI citations. Worth checking your own analytics for a dip starting around Aug 14.

For AI-Powered Shopping Companion startup, I built an AI assistant that has full access to my purchase history and answers questions in plain language.

Most common questions I actually ask:

• "What did I spend the most on last month?"
• "Which store gives me the best prices on X?"
• "How has the price of eggs changed over the last 3 months?"
• "Am I spending more than usual this week?"

The interesting ones are the comparative questions: "Was that a good price?", because they require cross-referencing your history against the live price index in the same response.

What surprised me: I once asked it things I never anticipated, like "should I buy in bulk at Costco or stick to weekly shops?" It can actually answer that from the data.

What would you ask an AI that knew everything you'd ever bought?

After a few months of building in my spare time, I shipped r/CartLens and launched on Product Hunt and PeerPush. The idea was simple: snap a receipt or archive a shopping trip, and the app tells you if you overpaid compared to real prices at other stores nearby.

The hard parts nobody talks about:

• Thermal paper fades. Getting AI to read a crumpled, half-faded receipt reliably took way longer than I expected
• Normalizing product names across stores is a nightmare ("Organic Whole Milk 1L" vs "Whole Milk Organic 1000ml" are the same thing — teaching a model that at scale is non-trivial)
• Building a crowdsourced price index from scratch means your product is useless until you have data, but you can't get data until people use it — classic cold start problem

Happy to answer questions about the stack or any of the above. Built with React, Gemini 2.5, Supabase, and more pain than I anticipated. cartlens.co

Hey everyone,

I've been building CartLens for a while and today we finally went live on Product Hunt.

The idea is simple: you snap a photo of any receipt or product Image, and r/CartLens pulls out every item, price, and unit cost using AI. It then cross-references your purchases against a crowdsourced live price index to show you where you overpaid, by how much, and what the better price was.

There's also a built-in AI assistant you can actually have a conversation with — ask things like "what did I spend the most on last month?" or "which store gives me the best value?" and it answers based on your real purchase history.

What surprised me most building this: the pricing data that matters most — what things actually cost at a specific store on a specific day — doesn't exist anywhere publicly. Web scraping gets you listed prices, not what people actually pay. Every receipt scanned in CartLens is a verified, ground-truth data point. That's what powers the price index.

Would love your honest feedback. We're early and actively iterating.

Hey everyone,

I've been building CartLens for a while and today we finally went live on Product Hunt.

The idea is simple: you snap a photo of any receipt or product Image, and CartLens pulls out every item, price, and unit cost using AI. It then cross-references your purchases against a crowdsourced live price index to show you where you overpaid, by how much, and what the better price was.

There's also a built-in AI assistant you can actually have a conversation with — ask things like "what did I spend the most on last month?" or "which store gives me the best value?" and it answers based on your real purchase history.

What surprised me most building this: the pricing data that matters most — what things actually cost at a specific store on a specific day — doesn't exist anywhere publicly. Web scraping gets you listed prices, not what people actually pay. Every receipt scanned in CartLens is a verified, ground-truth data point. That's what powers the price index.

Would love your honest feedback. We're early and actively iterating.