Hey makers!

Lately, I ve been looking closely at how independent builders and small teams are managing AI knowledge bases. It feels like the default "industry standard" is to immediately reach for a complex RAG pipeline and a heavy, paid Vector Database.

But I'm starting to wonder if we are over-engineering this for 90% of standard use cases.

Vector DBs are incredibly powerful for massive scale, but for smaller or non-massive datasets, they can be expensive, complex to query, and act as complete black boxes. If a search returns a weird chunk, diagnosing it is often a nightmare.

Product Hunt is home to amazing products across every category.

Today, we wanted to look at AI creative tools from a slightly different angle not just features, but the real-world marketing activity behind them.

Me First

ChatGPT & Cursor

Hi Founders,

I excited to share that I have built ArchitectGBT - Find Your Perfect AI Model and now its BETA live. ArchitectGBT is an AI-powered tool that takes the guesswork out of LLM selection.

Describe your project in natural language Get instant recommendations ranked by speed, cost, and accuracy for your specific use case.

Hey, I've been building Doppler, the search console for AI platforms like ChatGPT and Perplexity.

As the title says if you post your product I'll run it through my tool and give you an analysis of how it performs on both ChatGPT & Perplexity as well as some tips to improve your visibility from AI engines so you can get more traffic from it!

AI search is particularly efficient for B2B SMBs / B2C as AI apps will give tailored product recommendations based on the user's context, that's why it's worth optimizing for.

I was recently talking with a group of founders, and we went around sharing tools we're using now. Posting my notes for our community here - would love to know what else people are using!

Voice AI toolkit:

- Vapi

On their livestream today, OpenAI just released a bunch of new tools for reliably building and using AI agents. From what I can tell, this is what's new-

New APIs:

• Responses API - a new multi-modal API that builds on chat completions to allow for the next-generation of tool calling, starting with the new tools announced today.

Thanks to supabase I was able to get my project up and running in record time. I use oauth, edge functions, storage, database ofcourse, queues:pgmq and pgvector.

Please check out the project at https://github.com/vpuna/vpuna-a...

It's a semantic search platform for structured and unstructured data , with MCP support and more

Hi all! I m working on an idea that came out of my own frustration:

There are SO many AI tools right now for writing, meetings, code, design, finance but it s getting overwhelming.

Even though I m deep in the AI world, I still find myself Googling things like: Best AI tools for solo founders ; Free AI video editing apps ; Is this tool even legit?

So here s the vision:

There are so many new AI agent platforms ( @Wordware @Lindy @CrewAI @zapier and so on) that I'm finding myself curious how everyone is using them.

What AI agents are you using in production? What do they do? Are they working and reliable? What would make them better? Are they replacing roles? Augmenting existing ones?

One of the biggest pain points in AI chatbots has been their forgetfulness having to repeat the same context over and over again. AI memory aims to solve this by allowing models like ChatGPT and the newly launched Gemini to retain past interactions.

But how well do these memory features work? Which AI ChatGPT or Gemini handles memory better? And more importantly, does AI memory provide more value in personal use or enterprise settings?