AI Agent- How to set up research agent

Are you tired of spending hours researching and gathering information for your projects? Do you wish there was a way to automate the research process and save time? Well, with the advancements in artificial intelligence (AI), you can now rely on AI agents to do the research for you. In this article, we will explore the power of AI agents and how they can assist you in conducting research 24/7 without any hallucination. Let's dive in!

The Potential of AI Agents in Research

AI agents, specifically the GPT (Generative Pre-trained Transformer) model, have shown remarkable capabilities in generating content. Imagine having an AI agent that can write a Twitter thread about how famous people get rich and automatically gain 100K followers in just one year. This use case highlights the potential of AI agents in generating valuable content.

In the initial version, the AI agent followed a linear workflow, where it would search online for relevant information, scrape websites, and create a Twitter thread. However, the real research process is not linear but iterative, with new topics and information emerging as we delve deeper into our research.

The Role of AI Agents in Research

AI agents play a crucial role in the research process. They have the ability to plan, execute, and reprioritize tasks to achieve specific goals. A typical AI agent consists of three components: a large language model as the generation engine, a memory to store context, and a list of tools to execute tasks.

However, not all AI agents deliver good results. Two main reasons contribute to this. Firstly, the quality of task execution is essential. AI agents need to be able to complete tasks effectively. Secondly, the ability to reprioritize tasks is crucial. AI agents should be able to make judgment calls on when to continue researching or when to consider a task complete.

The Need for Specialized Agents

To overcome the challenges faced by general AI agents, specialized agents are being developed for specific tasks. Unlike general agents like ChatGPT or GPT-3, specialized agents focus on executing specific tasks effectively. These agents ensure that the tools used for specific tasks are executed well, leading to better results. Additionally, providing a well-defined system prompt can help agents make the right decisions.

Research is a fundamental use case that goes beyond creating Twitter threads. It serves as building blocks in various business workflows. For example, a whole workflow can be triggered from receiving an email. A large language model can extract information, which can then be fed into a research agent to understand the potential of a company. The leads list can be prioritized in Google Sheets or Airtable. Research agents can also integrate with other systems, such as extracting key information for writing a blog.

Deploying and Testing the Research Agent

To utilize the power of the AI research agent, you can create a web app using Streamlit, a Python library for creating web apps. The app allows you to input your research goal and query, and the agent will search for relevant information and return a list of links and relevant articles.

Alternatively, you can deploy the research agent as a web service using platforms like Make.com. This integration allows you to embed the agent in your business workflow and integrate it with other systems. The agent can be called through an API endpoint and used for lead scoring, background research, and more.

To test the agent, you can run it locally or deploy it to the cloud. FastAPI, a Python framework, can be used to turn the app into an API endpoint. You can then test the API endpoint using a test server and make post requests to get the desired results.

Integrating the Research Agent into Your Business Workflow

Once the agent is deployed, you can embed it in your business workflow using platforms like Make.com. You can create a scenario or workflow that triggers the agent when you receive an inquiry email. The agent can extract core information about the company and people mentioned in the email and perform background research. The information can then be exported to Google Sheets or Airtable for further analysis.

Conclusion

The AI research agent is a powerful tool for conducting research, extracting key information, and integrating it into your business workflow. By leveraging AI technology, you can save time and gain valuable insights for various use cases. With specialized agents and well-defined prompts, the research process can be streamlined and optimized. Embrace the potential of AI agents and let them do the research for you 24/7 without any hallucination!

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