So What is the AI Advantage?
In a single phrase, the AI Advantage is “workflow automation”.
From a musician, programmer, film maker, someone that works on drug discovery, a teacher, a student or any one that has some kind of work flow in their job, everyone will be working with aspects of AI powered workflow automation very soon.
1. MCP (Model Context Protocol)
As mentioned before, MCP’s are a key standard that will allow non-technical users to be able to use natural language to interact with various systems.
An example that many of us in the business world can easily understand would be to see the Google Analytics MCP in action. Watch this short video to get an understanding of where we are headed https://www.youtube.com/watch?v=PT4wGPxWiRQ
Imagine MCPs for all the major platforms we interact with on a daily basis. Extending this even further, imagine an environment where you can interact with multiple systems via multiple MCPs via a single prompt or series of prompts.
2. Critical Thinking & Clear Communication Leveraging the LLM with Humans in the Loop
Taking an average work flow and average inputs will not result in an exceptional output. The need for human creativity will be even more acute and it will probably be copied by others even faster. Collectively, this is good for us as this will spur even more innovation and at speed.
Critical skills like conceptualizing the end to end work flow, thinking of value add at each step and deciding on the checks and balances at each step in the work flow will need clear communication and the ability to troubleshoot and QA what you have built.
An understanding of what is happening under the hood will help
If you work on the data side of things, hopefully, you will appreciate the overview of some of the key Machine Learning algorithms provided as that will allow you as the “human” to ask specific questions via the LLM of the data you wish to examine.
Over the course of the next few months, we will try and put some of these learnings into action ourselves and will share the results.
3. There are "Agents" and there are "ReAct" agents
A ReAct agent refers to a virtual agent that combines the power of "Reasoning" and "Acting". The "Reasoning" element of an agent takes a task and decomposes it into small tasks. The "Acting" agent then executes on the smaller tasks decided in the "Reasoning' phase.
The "Acting" phase is enabled via the agent determining the tool it must use - Scraping, use of a search engine, calling an API, running a calculation and so on.
As the human in the loop, you are able to observe both the "Reasoning" and the "Acting" phases and get an understanding of how and what the agent referred to in terms of data sources and how it arrived the output.