Some, but not very much. Writing code is hard. Ai will do a lot of tedious code that you procrastinate writing.

Also when you are writing code yourself you are implicitly checking it whilst at the back of your mind retaining some form of the entire system as a whole.

People seem to gloss over this... As a CEO if people don't function like this I'd be awake at night sweating.

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bonesss 10 hours ago | parent | next [-]

That’s the reverse-centaur issue I see: humans are not great at repetitive nuanced similar seeming tasks, putting the onus on humans to retroactively approve high volumes of critical code has them managing a critical failure mode at their weakest and worst. Automated reviews should be enhancing known good-faith code, manual reviews of high volume superficially sound but subversive code is begging for issues over time.

Which results the software engineering issue I’m not seeing addressed by the hype: bugs cost tens to hundreds of times their coding cost to resolve if they require internal or external communication to address. Even if everyone has been 10x’ed, the math still strongly favours not making mistakes in the first place.

An LLM workflow that yields 10x an engineer but psychopathically lies and sabotages client facing processes/resources once a quarter is likely a NNPP (net negative producing programmer), once opportunity and volatility costs are factored in.

	▲	demosito666 6 hours ago \| parent \| next [-]
		> Even if everyone has been 10x’ed, the math still strongly favours not making mistakes in the first place The math depends on importance of the software. A mistake in a typical CRUD enterprise app with 100 users has zero impact on anything. You will fix it when you have time, the important thing is that the app was delivered in a week a year ago and was solving some problem ever since. It has already made enormous profit if you compare it with today’s (yesterday’s ?) manual development that would take half a year and cost millions. A mistake in a nuclear reactor control code would be a total different thing. Whatever time savings you made on coding are irrelevant if it allowed for a critical bug to slip through. Between the two extremes you thus have a whole spectrum of tasks that either benefit or lose from applying coding with LLMs. And there are also more axes than this low to high failure cost, which also affect the math. For example, even non-important but large app will likely soon degrade into unmanageable state if developed with too little human intervention and you will be forced to start from scratch loosing a lot of time.
	▲	bluGill 6 hours ago \| parent \| prev [-]
		I have found ai extreemly good at finding all those really hard bugs though. Ai is a greater force multiplier when there is a complex bug than in gneen field code.

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bluGill 10 hours ago | parent | prev | next [-]

Sortof. I work on a system too large for anyone to know the whole thing. Often people who don't know each other do something that will break the other. (Often because of the number of different people - most individuals go years between this)

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raw_anon_1111 9 hours ago | parent | prev [-]

No I’m keeping up with the system as a whole because I’m always working at a system level when I’m using AI instead of worrying about the “how”

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ansibsha 9 hours ago | parent [-]

No you’re not. The “how” is your job to understand, and if you don’t you’ll end up like the devs in the article.

We as an industry have been able to offload a lot of “how” via deterministic systems built by humans with expert understanding. LLMs give you the illusion of this.

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raw_anon_1111 9 hours ago | parent [-]

No in my case the “how” is

1. I spoke to sales to find out about the customer

2. I read every line of the contract (SOW)

3. I did the initial requirements gathering over a couple of days with the client - or maybe up to 3 weeks

3. I designed every single bit of AWS architecture and code

4. I did the design review with the client

5. I led the customer acceptance testing

> We as an industry have been able to offload a lot of “how” via deterministic systems built by humans with expert understanding. LLMs

I assure you the mid level developers or god forbid foreign contractors were not “experts” with 30 years of coding experience and at the time 8 years of pre LLM AWS experience. It’s been well over a decade - ironically before LLMs - that my responsibility was only for code I wrote with my own two hands

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ansibsha 5 hours ago | parent | next [-]

Yes, and trusting an LLM here is not a good idea. You know it will make important mistakes.

I’m not saying trusting cheap devs is a good idea either. I do think cheap devs are actually at risk here.

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raw_anon_1111 4 hours ago | parent [-]

I am not “trusting” either - I’m validating that they meet the functional and non functional requirements just like with an LLM. I have never blindly trusted any developer when my neck was the one on the line in front of my CTO/director or customer.

I didn’t blindly trust the Salesforce consultants either. I also didn’t verify every line of oSql (not a typo) they wrote.

	▲	icedchai 3 hours ago \| parent [-]
		Actually, it's SOQL. I did Salesforce crap for many years.

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6 hours ago | parent | prev [-]

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