The Future of Search: How Agentic AI Powered Search Engines Work

Tired of Google’s Wrong Answers? Learn How AI is Making Web Searches Smarter and better!

Picture this: you type a question into Google and instead of getting the right answer, you end up clicking through a bunch of irrelevant links. Frustrating, right? Search engines have definitely come a long way with tools like machine learning and natural language processing helping them deliver better results. But even with all these improvements, they still mostly sit back and wait for you to ask a question. They’re reactive, responding only when you feed them a query, and they don’t really understand what you might need long-term.

That’s where AI Agents come in. These smart, goal-driven systems are taking things up a notch—turning search engines from passive helpers into proactive assistants. Imagine a search engine that doesn’t just wait for you to ask but actually anticipates what you need, searches for relevant info on its own. These new AI Agents will make searching online faster and more efficient, without all the extra steps.

Understanding Agentic AI

AI Agents are sophisticated software programs that leverage artificial intelligence to perform tasks, answer questions, and interact with their environment effectively. These agents are designed with specific goals provided by humans, yet they independently determine the best methods to achieve these objectives.

AI Agents are composed of several key components:

• Perception/Learning: Gathers and processes information from the environment. Here the agent basically learns what to do and how to do it.
• Decision-Making: Analyzes all of the data it has to make informed decisions. The reasoning capabilities of agents can be leveraged here to optimize the decision-making process.
• Execution: Executes tasks based on the decisions made. The agent uses the tools it is equipped with to enhance its execution.
• Learning System: Enhances performance through trial and error, feedback, and reinforcement learning.
• Tools: Utilizes APIs, cloud applications, and data sources to achieve their goals.

AI agents are notable for their ability to independently plan—creating step-by-step strategies with milestones—and learn from past mistakes. Their memory capabilities range from handling immediate chat-based interactions to retaining and recalling long-term data. This independence and autonomy allow them to function as intelligent assistants, varying in complexity from simple chatbots to advanced AI systems capable of resolving intricate issues.

Key Characteristics

• Adaptation Across Domains: One of the remarkable qualities of AI Agents is their ability to be instructed to perform a wide range of tasks across different domains. This versatility allows them to be deployed in various contexts to address real business challenges effectively.
• Decision Making Capabilities: Agentic AI doesn’t just complete tasks—it makes decisions based on the data it processes. For example, when sorting through a large database, it doesn’t simply organize information; it intelligently analyses patterns, highlights key findings, and suggests next steps. This ability to evaluate and act makes it especially valuable in complex, dynamic situations.

This ability to adapt and make autonomous decisions is driven by the powerful architecture of transformers. The combination of advanced neural networks, multi-head attention mechanisms, and multi-layer perceptrons (MLPs) —along with other key components—equip AI agents with remarkable reasoning abilities. In some domains, this reasoning can closely mimic or even match that of humans.

Agentic AI's Role in AI-Powered Search Engines

Integration into Search Engines

One of the most exciting advancements in search engines today is the integration of Agentic AI, which has the ability to summarize search results and provide direct answers from multiple articles and sources. No more sifting through endless links or reading lengthy articles—AI agents do the heavy lifting by condensing and aggregating information. This means users get clear, accurate, and comprehensive answers straight from high-quality resources across the web.

Functionality Enhancements

Agentic AI also boosts data processing and real-time analysis capabilities within search engines, making them faster and more powerful. By analyzing vast amounts of data almost instantly, these AI systems can recognize patterns and extract meaningful insights much quicker than before. This allows search engines to better understand context, accurately interpret longer queries, and provide tailored responses by considering content from various articles in real-time. The result? More intelligent and targeted search results that adapt to users’ needs.

For example, if you're researching climate change and start with the query, “What are the main causes of climate change?”, an AI-powered search engine could immediately summarize the key factors like greenhouse gas emissions, deforestation, and industrial activities. It might even suggest recent studies or new data based on real-time content updates.

Companies like Google are already moving in this direction. Their project, Google MUM (Multitask Unified Model), aims to better understand complex topics, summarize lengthy content, offer direct answers, and even incorporate images and videos for a comprehensive response—all in one smooth experience. Additionally, Google's new AI Overview feature enhances this by providing concise, AI-generated summaries right in the search results, making it even easier for users to grasp key information quickly.

Comparison Between Traditional and Agentic Web Search

Traditional Web Search:

The traditional web searching experience is something we're all familiar with. You enter a search term or query into a search engine—let's use Google as an example. Google then returns a list of numerous websites and articles related to your search term. It's up to us to sift through each result to determine which ones are truly relevant to our needs.

For example,

If you search “What are LLM agents?”, you're dealing with an open-ended question. Understanding what LLM agents are might require reading multiple articles, as a single source often isn't sufficient. Many articles could contain redundant information, making the process even more time-consuming. It might take up to 30 minutes just to skim through the top 10 articles to gather a comprehensive understanding, nobody wants to do that in 2024.

Agentic Web Search

Now comes Agentic based Web Search, a transformative approach introduced shortly after the public release of LLMs, which is gradually reshaping the web search industry. While it operates similarly to traditional web searching, the real goodness lies in how it processes and presents the information. Let's continue with our previous example to illustrate this.

Example Continuation:

For the search term What are LLM agents?, the initial steps remain the same: Google will provide a list of related websites and articles. However, the agent will go one step ahead and thoroughly understand the content provided by these sources.

Here is where Agents shine:

• Exploration: Instead of manually sifting through each article, the Agent will visit all the relevant sources for you and retrieve what’s relevant for your query and what’s not.
• Content Generation: The Agent takes in all the information, makes sense of it, and then lays it out for you in a straightforward way. This approach saves your time and RAM. :)
• Summarization: When you're exploring What are LLM agents? , the Agent can efficiently review 10 articles and distill their content into a concise summary. This way, instead of spending 5-10 minutes on each article (adding up to over 50 minutes), you get a well-rounded summary that you can read in just 10-15 minutes.

By streamlining the research process, Agentic Web Search not only saves time but also enhances the quality of information you receive, making it easier to grasp complex topics quickly.

Here are a 2 examples of AI Powered Web Searching tools which you can use now for free:

1. Perplexity AI
2. GPT Search

The user experience with both of these tools is quite similar, as outlined in the workflows above. While there are hidden layers of complexity beneath the surface, these are primarily designed to enhance the accuracy and efficiency of the entire experience.

BYO (Build Your Own) AI-Powered Web Search

We created our own AI-powered web search, and here's how we did it—so you can build one tailored to your specific needs, too.

We used a tool called CrewAI. Here's a quick rundown:

CrewAI is designed to let AI agents work together like a well-coordinated team. Whether you're setting up a smart assistant, an automated customer service system, or a research team, CrewAI provides the framework for complex multi-agent interactions.

With CrewAI, we created a multi-agent system using two key tools: SerperDevTool and ScrapeWebsiteTool.

• SerperDevTool: This tool runs queries on Google’s search engine, returning a list of relevant websites.
• ScrapeWebsiteTool: Once SerperDevTool has identified the websites, this tool scrapes data from those sources.

Here's a simple example to illustrate how these tools work together:

For the query "What are LLM agents?", SerperDevTool searches Google and returns a list of websites, typically 10 by default. After that, ScrapeWebsiteTool extracts text from these sites.

Using CrewAI, we developed three agents:

1. Web Searcher: This agent browses the web to find relevant articles.
2. Summarizer: This agent condenses the content from the articles.
3. Answer Generator: This agent pulls together a coherent answer from the summarized content.

Each agent plays a crucial role in turning a simple query into a well-rounded answer, making the web search process efficient and user-friendly.

Here's an example we tested, and the results were surprisingly good.

Query:

Can you give me some really interesting and non-conventional facts about our universe?

Response:

Here are some intriguing and non-conventional facts about our universe:

1. Nearly 96% of the universe is made of dark matter (27%) and dark energy (68%), which are invisible and cannot be observed directly.
2. Every galaxy, including the Milky Way, contains a supermassive black hole at its center.
3. The universe is remarkably uniform with a temperature of 2.725°C, hinting at its fiery beginning during the Big Bang.
4. The expansion of the universe is accelerating due to dark energy, the nature of which remains a mystery.
5. There are more stars in the universe than grains of sand on all of Earth's beaches.
6. A day on Mercury lasts longer than its year.
7. Astronauts experience physical changes in space such as height increases due to spinal decompression.
8. The concept of the multiverse suggests our universe may be one of many, each with different laws of physics.
9. Astronomy has shown that some natural phenomena like tidal forces are deeply influenced by the moon.
10. Despite a vast number of potentially habitable planets, evidence for extraterrestrial life has yet to be found.

Building this system was surprisingly easy—it didn't even take us a full day. With tools and frameworks like CrewAI, setting up complex AI systems is becoming accessible to just about anyone. These frameworks are constantly improving, making it easier for individuals and businesses to harness AI capabilities without needing deep technical expertise. It's an exciting time to be part of this technological evolution, with more possibilities opening up every day.

You can check out the code here.

Conclusion

The rise of Agentic AI in search engines marks a transformative shift in how we access and interact with information online. By streamlining the search process and delivering concise, relevant answers, these AI systems are setting new standards for efficiency and accuracy in web searches. As technology continues to evolve, we can expect even more innovative tools that will further enhance our digital experiences. The future of search is not just about finding information—it's about understanding it, and Agentic AI is leading the way.

We build AI agents you can trust, because when AI makes things up, everything breaks down. With these agents, you free yourself from the basic busywork and also unlock meaningful experiences for your customers and employees. Let’s chat.