AI has had a revolutionary impact across society as a whole. People seeking knowledge and major international corporations alike have begun utilizing the power of AI on a daily basis. When it comes to tech companies, especially, AI has seen integration from everything from glasses to operating software. However, its most powerful utility is actually in auditing the very technology that helped create it. ‘AI Agents’, as they are now being called, are a sweeping trend that can analyze both front-end and back-end coding. So, with all this power, what exactly can these AI agents do?
One of the most useful functions is the data collection and integration. AI agents use a combination of Search API, Unlocker API, and several scrapers to locate and read large amounts of data in real time. Once they gain access, AI agents annotate and aggregate this data in a convenient database.
However, they do much more than just regular tasks. Agents like Harvey, Lindy, and Perplexity AI are hyper-specified. This means that they are configurable for a specific industry and tasks within those industries. Alternatively, if you want to manage your AI agents, there are AI agents to help you with that. AWS SageMaker, Azure Machine Learning, and Amazon Bedrock Agents are all major trusted platforms that make sure your AI agents are running at maximum efficiency.
However, the optimization of AI agents does not stop with a specific platform. Programs like CrewAI, LlamaIndex, and Haystack are of particular interest. With these platforms, you can build and orchestrate your own AI agents. This means that AI agents are not only suited for your particular industry, but also have the tasks suited for your particular company and specifications. Making the necessary adjustments is even easier with AI. Platforms like Weave.ai, Datadog, and Arize are all ways to monitor the performance of your AI agents. Moreover, they’ll even do debugging in real-time to make sure inefficient AI agent performance doesn’t hold your productivity back.
If you’re looking to take the process of making your own AI agents to the next level, there’s even support for that. Programs like Mem0, MemtGPT, and Weaviate all help with the creation of libraries for these AI agents to refer back to. Similarly, tool libraries allow you to extend the capabilities of your AI agents by using external tools and APIs. This is possible through OpenAI Tools, Zapier, Superagent, and many similar programs.
Lastly, if you’re interested in making your own agent, you’ll need a place to test changes before going ahead with them. This is where platforms like Modal, E2B, and CodeSandbox offer. This controlled environment is a small component, but crucial for avoiding costly mistakes with your AI agents. Combine this with storage programs like MongoDB, Supabase, and PostgreSQL, and you have a system to carry out tasks, create changes, test them, and to resupply themselves with productivity to continue the loop.
Ultimately, if you’re looking to get the most out of your AI agents, no area can be understated. From the pre-built options, custom-made, libraries, and databases, if you’re looking to boost your productivity, an AI agent is the advantage you’re looking for.
Source: Bright Data