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Comment by ryanjshaw | Hacker News Reader

Maybe 5% of the business/operations people I've worked with would even want to do this. The rest prefer a smart human to walk them through building a report - most of the time this is because they don't actually know what they need, and they actually need an expert to sit down and figure it out with them.

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The longer I'm in the business, the more I feel like my value as a software developer is identifying and asking clarifying questions.

You nailed it. At the beginning of my career I thought that success and value to the organization was all about technical skills.

30 years later I now understand that most successful projects need people with modest or average technical skills and outstanding communication skills.

It doesn't matter if you have super-genius engineers; if the business people don't really understand the problem that they're trying to solve then you're going to end up with a crap solution (may shiny, fast, and beautiful, but still crap).

IME, this is the number one reason outsourcing (whether on-shore or off-shore) fails for many projects.

When I was new, I saw one of my more experienced colleagues ask a few questions that together saved the company more than $1 mil each year. ChatGPT might be a threat to automate some low-level tasks or help eliminate bugs, but it is nowhere near ready to evaluate the context of a system, understand its history, or think* through the consequences of a major business decision.

* or think at all, in any meaningful way.

I agree with you to a point, but I think the only reason that it can't understand the context of a system is because it hasn't been trained on that system's code and documentation, which is obviously a future coming soon.

The problem is not the system, but the context of the system.

I'm not sure training these models on code and documentation will make that much of a difference. These models struggle significantly with subtlety, relevance, and correctness. It also doesn't have a theory of its own knowledge or confidence, and so tends to "hallucinate" and put out confidently-worded nonsense. Especially for complex and nuanced topics.

A big part of my job in software is having a very sharpened grasp of my ignorance, the ability to weigh a variety of tradeoffs, and the ability to convey my confidence of my abilities and my team's abilities. I'm not sure this is possible for this generation of AI.

The hallucination part is due to a lack of constraints. The AI can recognize constraints, but it can't recognize what it doesn't know for lack of context.

Prohibit all physical meetings. Force all communication through mediums that can be pipelined. Feed everything (accounting, contracts, law, etc...). Work will be then to architecture the AI to produce the optimal response.

The first company to figure this out will be too ahead. I don't think anything will be anywhere close to compete including nation states.

Though if it comes an AI with the capacity to include more context (ie: all company financials, communications, market analysis, etc...) it might be even more effective than a human with precise context.

Communication might be strictly email in the future. Or something that could be pipelined into the "AI" for context. Video/Calls might make it too at some point. Face to Face meetings strictly prohibited.

True, so true.

We work as translators. We translate intentions into actual descriptions.

We've been prompt engineers all along.

Touché.

I think I saw a comic years ago detailing a discussion that went something like this:

A: Eventually we won't need programmers people will just tell the computer what they need and it will generate the code for them.

B: True, there's actually already an industry term for a specification that's detailed enough to generate a working program from.

A: Oh, what is it called?

B: Code.

Yup. I think it was from Commitstrip.

edit: found it. https://www.commitstrip.com/en/2016/08/25/a-very-comprehensi...?

Yeah that's the one.

People don't realize how imprecise specs can be until they have this conversation for the first time.

"Okay, I understand what to do when {thing} happens. What do you want done when {not thing} happens?"

"Oh, umm..."

"{Not thing} can happen, right?"

"Oh yeah, all the time."

"So was the plan when it does?"

"I'm not sure..."

The same is true in technical sales. Obviously you need a sufficiently technical background to be able to _do_ stuff, but the primary value you bring is probe further than "we want to do X". The prospect / customer has mayybe done what they are asking twice, you've seen it done 100s of times.

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