AI Agent "Manos" for Accelerated Research and Data Analysis
This video introduces Manos, an AI agent service designed to significantly speed up and automate market and data research tasks, which are often challenging for professionals. The presenter, Professor Lee Jong-bo, highlights how traditional AI often falls short in providing comprehensive and direct answers, requiring multiple follow-up queries. Manos aims to overcome these limitations, offering a solution that can perform research up to ten times faster and with greatly enhanced productivity.
What is Manos?
- Manos is presented as a leading AI agent known for its performance [0:31-1:04].
- It's credited with popularizing the term "vibe coding" [0:31-1:04].
- The service allows for the complete automation of manual workflows, leading to higher quality and faster results [1:01-1:35].
Key Features and Demonstration
The presenter demonstrates Manos by requesting a detailed investigation into the investment trends and valuations of major global AI startups over the last two years. The request also includes a comprehensive analysis of global funding trends.
Demonstration Steps:
- Task Input: The user inputs a detailed research request, specifying the scope and desired analysis [1:32-2:04].
- Mode Selection:
- Adaptive Mode: Chosen by the presenter for rich data requests, allowing for intelligent adaptation and parallel processing [2:33-3:07].
- Other modes include Autonomous Agent and Chat.
- Integration Options (MCP): Users can connect their existing data sources like Google Drive or GitHub for more optimized research [2:33-3:07].
- Speed vs. Quality: The user selects "Quality" to prioritize in-depth analysis [3:05-3:38].
- Execution: Manos begins by systematically searching academic and general sources, then utilizes a virtual browser to access and extract information from websites like TechCrunch and Crunchbase [3:36-4:09].
- Automated Research Process: Manos mimics human research by reading articles, extracting data, synthesizing information, and iteratively refining its search strategy [4:06-4:39].
- Wide Research Feature: For comprehensive investigations, Manos employs "Wide Research," which enables it to process multiple data points simultaneously. In the demonstration, it targets 20 AI startups for detailed investigation, covering:
- Company details (name, founding year, location, founder, business area)
- Recent funding and company valuation
- Key investors
- Market position
- Growth strategy [5:07-5:40, 5:37-6:12].
- Parallel Processing: Wide Research utilizes parallel processing, similar to running dozens or hundreds of sub-agents simultaneously, significantly reducing processing time [6:40-7:12].
- Completion Time: The initial 20-startup research took approximately 20 minutes and 25 seconds [7:42-8:16].
- Final Report: Manos generates a detailed report in an MD file format, including conclusions, implications, and references. It also provides data in CSV format, summarizing key metrics like funding, valuation, and market position [8:14-8:49].
Second Demonstration: AI Implementation Research
The presenter then requests a study on the quantitative impact of AI implementation across 50 companies in fields like marketing, finance, and healthcare, aiming to create a comprehensive list of relevant academic papers. This again involves a Wide Research process, followed by a consolidated report analyzing key research findings, comparative analysis by sector, academic trends, and implications.
Conclusion and Offer
- Manos is praised for its speed and the high quality of its results, suggesting a potential productivity increase of up to 100x [9:51-10:23].
- Giveaway: The presenter offers a chance to win a one-month Pro account (valued at $199 USD) by commenting on the video. Five winners will be selected [10:21-10:40].
Key Takeaways:
- Time Efficiency: Manos dramatically reduces research time compared to manual methods or standard AI tools.
- Automation: Automates complex, iterative research processes that typically require significant human effort.
- Scalability: Features like "Wide Research" enable parallel processing for handling large volumes of data.
- Comprehensive Analysis: Provides detailed reports with actionable insights and synthesized data.
- Productivity Boost: Offers a substantial improvement in work productivity for tasks involving research and data analysis.