Comment by DoingSomeThings
7 hours ago
"Paying Fin $250k flat does nothing since it isn't going to actually know how to solve problems. The real challenge is the knowledge and context engineering and Fin doesn't help there"
You misunderstand the model. Fin does not have flat fee. They charge exclusively for resolutions. That's the entire value prop.
Correct that knowledge and context engineering are the key. Fin DOES help here. They have an entire backend suite to help you build out areas where Fin is failing. It shows you questions it couldn't resolve, looks at the answers your human team gave, and suggests updates to help articles to
You're correct this could all be build by a skilled engineer, but that's not the point. It's built for non-techincal users to use and implement. A person who rose through the support ranks and shows some technical competency can learn the system without any software knowledge.
The bulk of the work is context engineering which is done outside of Fin. Once you do the context engineering, it's very easy to duplicate Fin's features. Seriously. Just try it.
You don't need a fancy editor for "if this then do this". A simple text document is all you need. And if you do need a fancy editor, it's extremely easy to build it in 2026. Maybe 1-2 days.
I'm not a SaaS believer anymore.
Maybe you've done this yourself. I'm honestly jealous if solving customer support was as easy as your describe.
In my case, I've spent the past 12 months running implementations at multiple companies. I've engaged directly with smart engineering teams to assist. It was not that easy.
What you outlined might work for a simple ecom business. It probably does 95% of the job for a simple case where you're delivering information. But it will fail the second it needs to take action or deliver personalized information based on client's account data.
That leads to the exact issue people here complain about... an LLM that doesn't actually answer the question, can't solve the problem, and is worse than talking to a human
And why would Fin be better here? It's very easy to give your agent context on the customer.
In 2026, every time I've tried to build a custom tool to replace a SaaS, I've succeeded. The biggest problem with SaaS is that they build a one size fits all. When you build a custom tool, you control everything from data to UI and it works for your business.
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the bulk of the context engineering for users of these ai support platforms is done in the platform
and the amount of context needed to automate f500 is non trivial, plus you usually cant use reasoning because latency would blow up and you get escalated on
if this was so easy as you claim theres many millions for you to be made selling it to enterprises, but you wont
F500 is exactly the kind of scale where I fully expect support agents to be developed in house. They'll try Fin. Then one day, a single dev inside the company demos a custom agent that outperforms Fin and cost almost nothing.
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