I tested out having Claude do my taxes (I first painstakingly censored the docs). It came to within 1.5% of what my Accountant calculated. I intentionally just dumped the source docs into a folder and let it figure it out, no additional prompting.
1.5% is both terrifying from a Citrini scenario, but also not nearly close enough yet to replace my accountant. Like with everything the question will be how quickly it can add ~2 9s of accuracy - is that 2 years or 20
I think it's inconclusive. All we can know is generative video + social AI slop feed is the incorrect business to be in at this exact moment in time while Claude is running away with the SWE market.
"The wide majority of AI products evoke the feeling of being productive, but they haven’t moved the needle on driving value. The majority of publicized AI use is individuals self-indulgently “productivity-maxxing” on Twitter or in company Slack channels, with zero real impact."
Agree with much of this, though I think it's overly focused on the coding part. I keep seeing framing around "We used to have PMs write specific requirements which were handed to engineers to code". I've been working in tech for 15 years and haven't seen that in reality. Engineers had long been pulled into the requirement gathering phase while PMs focused on higher order Strategy docs. I've heard of places where this is true but hasn't been my experience.
This is very interesting. Over the long run with AI speeding up everything, whoever captures customer insight fastest will likely win so something like this needs to exist.
But where do the people answering the phone come from? Is that service provided or it's expected we setup the interview and then kickoff this tool?
So the agent returns a web voice interview link that can be shared with your users via email, discord, in-app or where-ever your users are. What would be ideal for you?
I think the problem is the shape of review processes. People higher up in the corporate food chain are needed to give approval on things. These people also have to manage enormous teams with their own complexities. Getting on their schedule is difficult, and giving you a decision isn't their top priority, slowing down time to market for everything.
So we will need to extract the decision making responsibility from people management and let the Decision maker be exclusively focused on reviewing inputs, approving or rejecting. Under an SLA.
My hypothesis is that the future of work in tech will be a series of these input/output queue reviewers. It's going to be really boring I think. Probably like how it's boring being a factory robot monitor.
Over the long run, companies that spend resources on this micromanagement of earnings probably are not seeing the forest for the trees. I cringe thinking about how much time and top talent at a company is spent preparing for earnings rather than spending those hours improving the business itself.
> why do you think it’s still important to stay strong in CS fundamentals?
I don't think anyone at any level has any idea what the future is holding with this rapid pace of change. What some old timers think is going to be useful in a post-Claude world isn't really meaningful.
I think if I had limited time to prioritize learnings at the moment it would be prioritizing AI tooling comfort (e.g. getting comfortable doing 5 things shallowly in parallel) versus going super deep in understanding.
1.5% is both terrifying from a Citrini scenario, but also not nearly close enough yet to replace my accountant. Like with everything the question will be how quickly it can add ~2 9s of accuracy - is that 2 years or 20
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