Autonomy/automation makes sense where error-prone repetitive human activity is involved. But rule definitions are not repetitive human tasks. They are defined once and run every time by automation. Why does one need to go for a probabilistic rule definition for a one-time manual task? I don't see huge gains here.
Or decide what the next step should be based on freeform text, images, etc.
Hardcoded rule based would have to try and attempt to match to certain keywords etc, but you see how that can start to go wrong?
Now, if the request is coming in as text or other media instead of a form input, then the workflow would call a relevant processor, to identify the category. Everything from that point runs same as before. The workflow itself doesn't change just because the input format has changed.
How does it determine next step from raw non structured content?
Let's imagine for example that it's a message from a potential customer to a business. The processor must decide whether to e.g. give product recommendations, product advice, process returns, use specific tools to fetch more data (e.g. business policies, product manuals, etc), or current pricing, best products matching what the customer might want etc.
If it's an AI agent it could be something like:
1. Customer sends message: "my product Y has X problem". (but the message could be anything from returns to figuring out most suitable product)
2. AI Agent uses "search_products" tool to find info about Y product in parallel with "send_response" to indicate what it's trying to do.
3. AI Agent uses "search_within_manual" tool to find if there are specific similar problems described.
4. AI Agent summarizes information found in manual, references the manual for download and shows snippet of content it based its answer on.
AI Agent itself is given various functions it can call like
1. search_products
2. search_business_policies
3. search_within_documents
4. send_response
5. forward_to_human
6. end_action
7. ... possibly others.
How would you do it in the traditional workflow engine sense?
Then over time their is a type of entropy with all business processes.
If we don't figure out dynamic systems to handle this it is hard to see how we get a giant productivity boost across the economy.
There is also the problem that what percentage of people even have exposure to the concepts of dynamic systems? When I was in college, I distinctly remember thinking dynamic systems, "chaos theory", was some kind of fractal hippy pseudoscientific fraud best to ignore.
I think of how often I hear the average person use language from probability theory but never from dynamic systems.
For instance, I might be looking for a product or something, it will use web search to gather all possible products, then evaluate all the products against my desired criteria, use some sort of scoring mechanism to order the products for me and then write an UI to display the products with their pros and cons specified, with products ranked using an algorithm.
Or I might ask it to find all permutations of flight destinations in March, I want somewhere sunny and use weighted scoring algorithm to rank the destinations by price, flight travel duration etc.. Then it writes code to use flights API, to get all permutations and does the ranking.
I used to have to go to things like airport websites, momondo, skyscanner, I don't have to do those things manually anymore, thanks to AI agents. I can just let it work and churn out destinations, travel plans according to a scoring criteria.
Worst mistakes it can make is, that is missed a really good deal, but this is something I could even more easily miss myself, or worst case it makes a mistake and parses the price/dates wrong, which I will find out when trying to book it, so I waste a bit of time, but similar and worse mistakes I do on my own as well. So overall I drastically reduce my search time for the perfect travel, and also time spent on my own mistakes or misunderstandings. And it will be able to go through permutations far faster and more reliably with infinite patience compared to myself.
