When it comes to AI Memory, everyone's arguing "RAG vs. grep" like it's a religious war. It's not. It's just a cost curve. I've gotten this question so many times that I thought I'd just share my thoughts. So here goes:
Vector search wins when your corpus is massive, messy, and unstructured. Thousands of docs, no clean boundaries, meaning matters more than exact words.
Filesystem plus grep wins when your corpus is structured and actually yours. A folder of markdown files you can open, read, and audit line by line. No infra required.
Anthropic already ran this experiment in production. Claude Code dropped its RAG pipeline for plain agentic search (grep, glob, read) and it outperformed the vector pipeline on real work. Not close.
But the benchmark wars are missing the actual point. It was never about picking one. It's about knowing what each layer is for.
Markdown is your source of truth. Portable, human readable, greppable, not locked to one provider. Memory you can actually own and move.
Vector search is an accelerant on top of that truth. A fast index for when the haystack gets too big for exact match to keep up.
Use either one alone and it breaks down:
- Markdown alone stalls at scale and struggles with paraphrasing or fuzzy recall
- Vectors alone turn your memory into a black box you can't read, audit, or export
The next step for memory infrastructure isn't picking a side. It's the filesystem as the ledger and RAG as the index on top of it, so memory stays legible and portable, and still fast when it needs to be.
This is the exact direction we're building with AI Context Flow: markdown as the portable, ownable source of truth, with retrieval layered on top instead of replacing it.
If your memory only exists as embeddings inside someone else's vector DB, that's not memory. That's a lease.
Which team are you on?
CubeOne AI
AI Context Flow
@ericquans thank you!
AI Context Flow
@elinarebinset15 glad you find it interesting! I hope you also find it useful day to day when you use it :)
Does it work the other way around? Can it be integrated into our AI product (AI for travel planning) so that when a user logs in, our AI receives information about them and can offer a personalized experience?
AI Context Flow
@mykyta_semenov_ actually this is on the roadmap. Two possibilities here:
- Your agent accepts MCP connectivity. We are launching our MCP servers next month!
- You integrate our Login SDK (sign in with your context), this will be launched in a few months.
@hira_siddiqui1 Then I’m your potential client — we’re just finishing our project. Let’s stay in touch on LinkedIn.
AI Context Flow
@mykyta_semenov_ connected on linkedin and followed you on X!
Video Roll
This is a fantastic browser extension. I just tested it, and it significantly improves the quality and speed of my Prompts.
AI Context Flow
@gxy5202 so glad you found it helpful! would love to know your feedback once you use it for several days!
We are also giving one year free subscription to PH launch day supporters!
Okay, this is actually clever. Cutting repetition in AI chats was overdue. What’s the messiest real-world use case you saw this solve that made you say ‘yeah this had to exist’?
Theysaid
Okay, you've literally described my daily struggle. I switch between ChatGPT, Claude, and Gemini constantly, and I waste so much time copying my project context, brand guidelines, and tech stack from one chat to another. The mental tax of re-explaining everything is real. This extension feels like it was built specifically for me.
AI Context Flow
@chrishicken love that you are finding this useful! Would love to have you as our regular user. We are also giving 1 year free subscriptions for our product hunt launch day users!
Theysaid
@hira_siddiqui1 That's really amazing
AdBlocker for YouTube
Congrats on the launch! Love the idea of making AI tools finally talk to each other. Best of luck on Product Hunt today! 🙌
AI Context Flow
@armen_stepanyan thank you!