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
"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 3 common issues used to be solved by a manual with an FAQ page, or just you know, actually intuitive and usable software and hardware."
Having led customer support, this grossly misunderstands how people interact. People don't read. It's as simple as that. You can write something as clear as day in a FAQ, and they don't want to put in the effort. ~50% of the inbounds I receive are fully written out in plain language in an FAQ.
LLMs are perfect for this scenario. It puts the answer in clear english and will endlessly re-word the answer when clients followup.
This is disappointing. I've worked closely with Intercom for the past few years. I've run Fin implementations at multiple companies. I've found their product team incredibly strong & the product to be customer friendly. Salesforce... not so much.
imo - Fin's AI chat is the best on the backend of empowering teams to self-serve & integrate with Helpdesk. They don't require consultants.
I really hope they don't lose all of that in this acquisition.
Was a fascinating look into how different college experiences can be, how insular the venture ecosystem seems, and the gross efforts powerful people make to keep that power. I’d love to know how true to life the undergrad->tech power pipeline is.
I’ve never lived in CA, worked for a unicorn or big tech. Didn’t go to an Ivy. I took the route of state school to startups in second tier markets. I’d never heard of VC until a few years into career. Hard to fathom how different the Stanford experience is, as described.
I walked away from the book feeling jaded. It makes everything about career and company success feel dirty in a manner I’ve never experienced first hand.
Dave Matthews Band similarly cultivates the fan recordings.
https://antsmarching.org/ forum has hundreds, maybe thousands of show recordings. Often multiple for each night. They make their own official Soundboard releases that fans still purchase, but their stewardship of fan audio capture is commendable.
Reader Summary:
You are a walking existential crisis who oscillates between trying to save your soul with 13th-century Catholic theology and escaping reality via magic-system spreadsheets. Your reading list is essentially a debate between a Trappist monk and a Silicon Valley venture capitalist, and somehow, they're both currently losing to a talking cat in a death dungeon.
Information Diet:
Your media consumption suggests a high-low split. You balance dense, slow-burn philosophy (Josef Pieper) with high-octane, 'popcorn' entertainment (Dungeon Crawler Carl), intentionally using fiction as an escape from heavy systemic analysis.
Life Arc:
Your life trajectory appears to be a journey from 'Enchanted Orthodoxy' to 'Humanistic Meaning. You moved from preparing for the priesthood/ministry to a deconstruction of faith, eventually landing in a space of 'Conscious Leadership' and secular contemplative practice.
Unexpected favorite read of the year: Dungeon Crawler Carl. It’s popcorn fiction, but
Personal Growth: “15 Commitments of Conscious Leadership”. The encouragement to “feel all your feelings” is insanely difficult for me, but has sent me on a multi-month life arc to be more present to my body sensations.
Related: If you log your books in Goodreads, I built this web app to recommend future books based on reading history and reviews. Was fun for me and may resonate
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