[handfuloflight]

You're mischaracterizing my position from the start. I never claimed LLMs "revoke ambiguity from the English language."

I said I'm doing everything a programmer does except writing syntax. So your argument about English being "ambiguous" misses the point. ⍵[⍋⍵]}⍨?10⍴100 is extremely precise to an APL programmer but completely ambiguous to everyone else. Meanwhile "generate 10 random integers from 1 to 100 and sort them in ascending order" is unambiguous to both humans and LLMs. The precision comes from clear specification, not syntax.

You're conflating oversight with "babysitting." When you review and validate code, that's normal engineering process whether it comes from humans or AI. If anything, managing human developers involves actual babysitting: handling office politics, mood swings, sick days, ego management, motivation issues, and interpersonal conflicts. CTOs or managers spend significant time on the human element that has nothing to do with code quality. You're calling technical review "babysitting" while ignoring that managing humans involves literal people management.

You've created a false choice between "prototype" and "production software" as if natural language programming can only produce one or the other. The architectural thinking isn't missing, it's just expressed in natural language rather than syntax. System design, scalability patterns, and business requirements understanding are all still required.

Your assumption that "cognitive load can only be decreased by an engineer who understands your product" ignores that someone can understand their own product better than contractors. You're acting like the goal is to "dismiss humans" when it's about finding more efficient ways to build software, I'd gladly hire other natural language developers with proper vetting, and I actually have plans to do so. And to be sure, I would rather hire the natural language developer who also knows syntax over one who doesn't, all else being equal. Emphasis on all else being equal.

The core issue is you're defending traditional methods on principle rather than engaging with whether the outcomes can actually be achieved differently.

[obirunda]

The point I'm driving at is why? Why program in English if you have to go through similar rigour. If you're not actually handing off the actual engineering, you're putting the solution and having it translate to your language of preference whilst telling everyone how much more productive you are for effectively offloading the trivial part of the process. I'm not arguing that you can't get code from well defined, pedantically written requirements or pseudo code. All I'm saying is that that is less than what is claimed by ai maximalists. Also, if that's all that you're doing with your "agents" just write the code on not deal with the pitfalls?

[handfuloflight]

Yes, I maintain the same engineering rigor: but that rigor now goes toward solving the actual problem instead of wrestling with syntax, debugging semicolons, or managing language specific quirks. My cognitive load shifts from "how do I implement this?" to "what exactly do I want to build?" That's not a trivial difference, it's transformative.

You're calling implementation "trivial" while simultaneously arguing I should keep doing it manually. If it's trivial, why waste time on it? If it's not trivial, then automating it is obviously valuable. You can't have it both ways.

The speed difference isn't just about typing faster, it's about iteration speed. I can test ideas, refine approaches, and pivot architectural decisions in minutes and hours instead of days or weeks. When you're thinking through complex system design, that rapid feedback loop changes everything about how you solve problems.

This is like asking "why use a compiler when you could write assembly?" Higher-level abstractions aren't about reducing rigor, they're about focusing that rigor where it actually matters: on the problem domain, not the implementation mechanics.

You're defending a process based on principle rather than outcomes. I'm optimizing for results.

[obirunda]

It's not the same. Compilers compile to equivalent assembly, LLMs aren't in the same family of outcomes.

If you are arguing for some sort of euphoria of getting lines of code from your presumably rigorous requirements much faster, carry on. This goes both ways though, if you are claiming to be extremely rigorous in your process, I find it curious that you are wrestling with language syntax. Are you unfamiliar with the language you're developing with?

If you know the language and have gone as far as having defined the problem and solution in testable terms, the implementation should indeed be trivial. The choice of writing the code and gaining a deeper understanding of the implementation where you stand to gain from owning this part of the process come with the price of a higher time spent in the codebase, versus offloading it to the model which can be quicker, but it comes with the drawback that you will be less familiar with your own project.

The question ofhow do I implement this? Is an engineering question, not a please implement this solution I wrote in English.

You may feel like the implementation mechanics are divorced from the problem domain but I find that to hardly be the case, most projects I've worked on the implementation often informed the requirements and vice versa.

Abstractions are usually adopted when they are equivalent to the process they are abstracting. You may see capability, and indeed models are capable, but they aren't yet as reliable as the thing you allege them to be abstracting.

I think the new workflows feel faster, and may indeed be on several instances, but there is no free lunch.

[handfuloflight]

'I find it curious that you are wrestling with language syntax': this reveals you completely missed my point while questioning my competence. You've taken the word 'wrestling', which I used to mean 'dealing with', and twisted it to imply incompetence. I'm not 'wrestling' with syntax due to incompetence. I'm eliminating unnecessary cognitive overhead to focus on higher-level problems.

You're also conflating syntax with implementation. Implementation is the logic, algorithms, and architectural decisions. Syntax is just the notation system for expressing that implementation. When you talk about 'implementation informing requirements,' you're describing the feedback loop of discovering constraints, bottlenecks, and design insights while building systems. That feedback comes from running code and testing behavior, not from typing semicolons. You're essentially arguing that the spelling of your code provides architectural insights, which is absurd.

The real issue here is that you're questioning optimization as if it indicates incompetence. It's like asking why a professional chef uses a food processor instead of chopping everything by hand. The answer isn't incompetence: it's optimization. I can spend my mental energy on architecture, system design, and problem-solving instead of semicolon placement and bracket matching.

By all means, spend your time as you wish! I know some people have a real emotional investment in the craft of writing syntax. Chop, chop, chop!

[obirunda]

This is called being obtuse. Also, this illustrates my ambiguity point further, your workflow is not clearly described and only further muddled with every subsequent equivocation you've made.

Also, are you actually using agents or just chatting with a bot and copy-pasting snippets? If you write requirements and let the agent toil, to eventually pass the tests you wrote, that's what I assume you're doing... Oh wait, are you also asking the agents to write the tests?

Here is the thing, if you wrote the code or had the LLM do it for you, who is reviewing it? If you are reviewing it, how is that eliminating actual cognitive load? If you're not reviewing it, and just taking the all tests passed as the threshold into production or worse yet, you have an agent code review it for you, then I'm actually suggesting incompetence.

Now, if you are thoroughly reviewing everything and writing your own tests, then congrats you're not incompetent. But if you're suggesting this is somehow reducing cognitive load, maybe that's true for you, in a "your truth" kind of way. If you simply prefer code reviewing as opposed to code writing have it your way.

I'm not sure you're joining the crowd that says this process makes them 100x more productive in coding tasks, I find that dubious and hilarious.

[handfuloflight]

You're conflating different types of cognitive overhead. There's mechanical overhead (syntax, compilation, language quirks) and strategic overhead (architecture, algorithms, business logic). I'm eliminating the mechanical to focus on the strategic. You're acting like they're the same thing.

Yes, I still need to verify that the generated code implements my architectural intent correctly, but that's pattern recognition and evaluation, not generation. It's the difference between proofreading a translation versus translating from scratch. Both require language knowledge, but reviewing existing code for correctness is cognitively lighter than simultaneously managing syntax, debugging, and logic creation.

You are treating all cognitive overhead as equivalent, which is why you can't understand how automating the mechanical parts could be valuable. It's a fundamental category error on your part.