Obsidian-MBPM4
9c67d2fdec
Affected files: .obsidian/plugins/text-extractor/cache/0e1681cb976efab437314ee5b955bf19.json .obsidian/plugins/text-extractor/cache/8e7ba73749fd1e85200c90d920c18377.json .obsidian/plugins/text-extractor/cache/e3491f3656f5e7a8c562d164a907bfc6.json .obsidian/workspace.json 0 Journal/0 Daily/2025-07-21.md Attachments/Pasted image 20250721140924.png Attachments/Pasted image 20250721140942.png Attachments/Pasted image 20250721142129.png Temporary/AI Agents.md
1.4 KiB
1.4 KiB
title, created_date, updated_date, aliases, tags
| title | created_date | updated_date | aliases | tags |
|---|---|---|---|---|
| AI Agents | 2025-07-21 | 2025-07-21 |
AI Agents
He created an AI to do his job (his boss is hallucinating) - YouTube
Agents
!
!
- anything-llm
- crew-ai
- fine tuning vs RAG (RAG is metter?)
- langchain
Agent Roles
Google Ads Optimizer
- research assistant --> search the good keywords
- content strategist --> B2B or B2C
- manager: prompted.
!
- double checks output of the two agents before sending it to the google API. If there is a formatting error in the csv file or so it just asks the agents to restart.
React Example
- input figma (wireframe prototype): really nice application overview with all screens etc
- asked vision model to describe the different screens in detail (Pixtral 12B)
- Get Prompts (1-20) --> one super prompt file with all prompts inthere
- send to agents which execute stuff on cursor
- you need the agents because of the context length limit
Roles
- prompt manager: prompt analysis --> split prompt into multiple chunks which match best with the agent team and send them the prompt with a global context description
Cursor
- Combine with crewAI
Bikee Example
- Reverse Engineering crew --> creates a document which describes
- brute force routes
- Developer crew
Learnings
- use AI to make prompts
- combine