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Don't do RAG - One counter intuitive thing I learnt past few weeks - Load whole knowledge base into prompt is actually fast, cheap & more accurate than normal RAG pipeline I was building an MCP for reading external doc, I was able to generate right code example by...

82,818 Aufrufe • vor 1 Jahr •via X (Twitter)

10 Kommentare

Profilbild von Mark Fer
Mark Fervor 1 Jahr

What if you want to dive into thousands of sales calls, marketing content, etc?

Profilbild von Breadcrumb
Breadcrumbvor 1 Jahr

Looking to automate reporting? Use AI agents to turn spreadsheets to reports in minutes without any coding.

Profilbild von Imiël Visser
Imiël Visservor 1 Jahr

Gemini has 1M context window vs Claude 200k... 50 pages is nothing, but what is the cost vs RAG for volume processing?

Profilbild von Brandon Culver
Brandon Culvervor 1 Jahr

No offense, but RAG isn't for 50 pages, it's for 500k pages

Profilbild von josh
joshvor 1 Jahr

Have you tried using Figma MCP? I’m curious if it’s possible to load prebuilt components that the AI can use during the build.

Profilbild von AJ
AJvor 1 Jahr

this is a good stuff. I am thinking of is cursor is able to read npm packages well or not because with not so known packages its' did a really bad job manybe we can connect something like this to a package wdyt?

Profilbild von Ajay Jagota 🔑🏃‍♂️
Ajay Jagota 🔑🏃‍♂️vor 1 Jahr

This is brilliant TY 🙏 Love how context drives the performance and you can track it in helicone 👏

Profilbild von Sam Sung
Sam Sungvor 1 Jahr

Do you think this is the way to go for giving “memory” to AI? I’m working on a chatbot that I want to give memory, but worried that as conversations get longer (and users have more conversations) that the cost of processing it all will be too much (currently used Claude 3.5 sonnet with caching, but still it gets expensive - like 50 cents for a single, long conversation). I’ve been wondering how I can figure out this memory issue - RAG? Create summaries with cheaper models?

Profilbild von Kris
Krisvor 1 Jahr

We are working on big 1GB+ pdf DB. I think OCR once. Summarize to 50 pages. Send that plus relevant files to Gemini to answer in super context? Wanna join our Discord?

Profilbild von Boring traveler
Boring travelervor 1 Jahr

How about in local?

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