This is already solved by the traditional workflow systems. For example, if the request is received as a form submission, a form processor is invoked to categorize the request and route the request accordingly based on the identified category.
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?
I think you missed the whole point. Processor does not have routing logic. It's only job is to parse the request (form, text, image etc) and categorize it enough so that the workflow can do the routing for next actions. Routing is done by traditional predetermined logic, using rules. The discussion here is about whether it helps to define that routing logic at runtime (on-the-fly), instead of having it coded in predetermined logic. My view is, it doesn't help.
AI-based tools are mostly about replacing the processor with something smarter, not the router.
Of course, sometimes it can be an advantage to not have to explicitly write the router, but the big benefit is the better processor for request->categorization, which with AI can even include clarification steps.
I edited my comment to add more of what the agent would be doing. Not sure if this reached you, but if you read the edited one, how would traditional workflow engine solve the particular problem with a free form raw content that could be anything, and requires using various tools to solve the problem?
There is always much path dependence in what becomes the business requirements, making the business requirements less than optimal to start with.
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.
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?