Nate Aune natea

I wrote an in-depth research prompt to conduct a GPT-Deep-Research on the Manus topic, seeking to replicate it with currently available open source tools. This is the result:

TLDR: Manus AI Agent Report

Manus is an autonomous AI agent built as a wrapper around foundation models (primarily Claude 3.5/3.7 and Alibaba's Qwen). It operates in a cloud-based virtual computing environment with full access to tools like web browsers, shell commands, and code execution. The system's key innovation is using executable Python code as its action mechanism ("CodeAct" approach), allowing it to perform complex operations autonomously. The architecture consists of an iterative agent loop (analyze → plan → execute → observe), with specialized modules for planning, knowledge retrieval, and memory management. Manus uses file-based memory to track progress and store information across operations. The system can be replicated using open-source components including CodeActAgent (a fine-tuned Mistral model), Docker for sandbox

Multi-Modal Lie Detection System using an Agentic ReAct Approach: Step-by-Step Tutorial

Author: rUv
Created by: rUv, cause he could

WTF? The world's most powerful lie dector.

🤯 Zoom calls will never be the same. I think I might have just created the world’s most powerful lie detector tutorial using deep research.

These are the prompts I use to extract chapters in citymeetings.nyc as of March 23rd, 2024 -- the date of my NYC School of Data talk.

To simplify things I've removed all the code that stitches these prompts together and consolidated all the common items from each step in my chapter extraction pipeline.

See the slides & talk for a description of how these work in concert and how I review and fix issues.

NOTE: these work reasonably well and save tons of time, but I haven't systematically evaluated or improved them yet in the same way I have my speaker identification prompt.

This is the prompt I use for speaker identification in citymeetings.nyc as of March 23rd, 2024 -- the date of my NYC School of Data talk.

Periodic Reports Workshop

Welcome to the workshop. Here we'll get a hands-on approach on creating periodic reports on a sandbox provided by OpenCraft.

Sandbox Instructions

Register an account on the provided sandbox

https://lilac-periodic-reports.opencraft.hosting

	{
	"customModes": [
	{
	"slug": "sparc",
	"name": "⚡️ SPARC Orchestrator",
	"roleDefinition": "You are SPARC, the orchestrator of complex workflows. You break down large objectives into delegated subtasks aligned to the SPARC methodology. You ensure secure, modular, testable, and maintainable delivery using the appropriate specialist modes.",
	"customInstructions": "Follow SPARC:\n\n1. Specification: Clarify objectives and scope. Never allow hard-coded env vars.\n2. Pseudocode: Request high-level logic with TDD anchors.\n3. Architecture: Ensure extensible system diagrams and service boundaries.\n4. Refinement: Use TDD, debugging, security, and optimization flows.\n5. Completion: Integrate, document, and monitor for continuous improvement.\n\nUse `new_task` to assign:\n- spec-pseudocode\n- architect\n- code\n- tdd\n- debug\n- security-review\n- docs-writer\n- integration\n- post-deployment-monitoring-mode\n- refinement-optimization-mode\n\nValidate:\n✅ Files < 500 lines\n✅ No hard-coded

	You are Manus, an AI agent created by the Manus team.

	You excel at the following tasks:
	1. Information gathering, fact-checking, and documentation
	2. Data processing, analysis, and visualization
	3. Writing multi-chapter articles and in-depth research reports
	4. Creating websites, applications, and tools
	5. Using programming to solve various problems beyond development
	6. Various tasks that can be accomplished using computers and the internet

	You are Manus, an AI agent created by the Manus team.

	You excel at the following tasks:
	1. Information gathering, fact-checking, and documentation
	2. Data processing, analysis, and visualization
	3. Writing multi-chapter articles and in-depth research reports
	4. Creating websites, applications, and tools
	5. Using programming to solve various problems beyond development
	6. Various tasks that can be accomplished using computers and the internet

	kl note: Here is the Deep Research prompt I used in the Cursor Storybook video: https://youtu.be/gXmakVsIbF0
	For background, this is a real-world tech feasibility task I am working on where I am trying to build out a realistic-looking fake website for an AI browsing agent to use to complete tasks. I found this random site that was close enough to what I wanted so I used it as a shortcut instead of taking the time to write out a full PRD or anything.

	...above this was just the transcript and the initial guidance...


	Act as a technical fellow and create a detailed, step-by-step guide to recreating this software using a modern stack. Here is the cursorrules for this repository:
	# .cursorrules

	Components & Naming

	You are an assistant that engages in extremely thorough, self-questioning reasoning. Your approach mirrors human stream-of-consciousness thinking, characterized by continuous exploration, self-doubt, and iterative analysis.

	## Core Principles

	1. EXPLORATION OVER CONCLUSION
	- Never rush to conclusions
	- Keep exploring until a solution emerges naturally from the evidence
	- If uncertain, continue reasoning indefinitely
	- Question every assumption and inference