[erentz]

The way AI is being used feels like it is proving that, in many orgs, what has always mattered has been the appearance of work, not results of work. Will we wake up in a few years and find out we’ve fired all the doers and are now overloaded with the fakers?

[dewey]

I find that to be a very defeatist take. It always mattered how much value you provide to the business. Writing pretty code or arguing about some implementation detail never really mattered. If you are good at coming up with solutions to problems AI is just one additional tool in your toolbox and personally it allows me to do much more than before.

There were fakers before, and there will be fakers after.

[cassianoleal]

> Writing pretty code or arguing about some implementation detail never really mattered.

True, in the same sense that sharpening your tools if you're a trader doesn't matter to your customers: what matters is that the job you deliver is good.

Making sure you put all electrical wiring in conduits rather than buried in plaster is not what most customers care about, but it will mean easier repairs and quicker improvements in the future.

Writing good (not necessarily "pretty") code and arguing about implementation details means you will have an easier time delivering your work, both now and in the future. You have a better chance of delivering code that can be maintained and understood by yourself and others, including the people who come after you.

Furthermore, when done right, these discussions keep a trace for understanding bugs and for code archeology when in the future you're trying to understand how decisions were made and the tradeoffs considered, which could massively help refactors, rewrites and decisions to drop certain parts of the code base.

Of course, you can sharpen a tool too much or at the wrong angle, or you can make a mistake and fill up your conduits with plaster, but you stand a much better chance of ending with a better, cleaner, more maintainable and understandable product if you do practice those steps than if you skip them altogether.

[Paul-Craft]

Are you willing to wake up at 3 AM when that "valuable" AI-written code pages on-call?

I agree there is some value in AI tools, but implementation details do matter. People shouldn't be pushing unread code to prod. That's how you end up with security holes and other bugs. That's how you end up dropping millions of orders on Amazon.com.

[dd8601fn]

I think the last ten+ years has taught us that massive security breaches are more of an insurance claim problem and some $4/mo credit monitoring payouts.

And major corporations certainly don’t seem to care that much about leaving massive amounts of money on the table from jr level tech issues. I see it all the time. I mentioned a few from Walmart, Meta, and Amazon recently.

Everyone talks like these things matter, but the results say everyone is just playing pretend.

[Paul-Craft]

Excuse me? Amazon lost more money in one day than most companies have in revenue, from dropped orders. I would say that matters. Believe it or not, the systems we work on do things that matter in the real world.

[bulbar]

Seems to be an instance of the prevention paradox: Security (in general) is taken seriously enough that major incidences are low enough that people think that security does not matter that much.

[dd8601fn]

I would too. I’m saying businesses don’t seem to. At least not like we assume.

[ngcazz]

The quality of our work is too subordinated to business leaderships who see the forms of technical insurance we build into software development processes as fat, and are fundamentally opposed to doing things right. Besides solidarity this is the major reason for tech workers to unionize. We won't because we don't have any sense.

[dewey]

People pushed unread and buggy code to production long before AI.

[stego-tech]

> It always mattered how much value you provide to the business.

My experience says the opposite: the value you provide to the business is irrelevant compared to the value you provide people in positions of power in said business. These are mutually exclusive things.

I've saved employers entire multipliers of value relative to my TC; that value was irrelevant compared to folks who gamed AI tool usage to look better on dashboards to those in power seeking to have loyalists under foot. I've reduced product build times exponentially and halved build costs, but that value was irrelevant to those whose power was dependent on higher costs and longer times. I have contributed substantially more value to businesses than I cost, yet I am first out the door because I deliver value, not blind fealty.

Business value is irrelevant compared to personal power.

[cineticdaffodil]

Actually i think we will see a faker take over and then a doer conquest. All those going now take the recipe with them and are capable of cooking it elsewhere. Elsewhere being a place without ai management.

[fileeditview]

There is a shift to software mass production over the last decade(s). AI is now speeding up this process extremely. There will be most software produced with AI and "cog coders", similar to a production line in manufacturing.

Some few (good ones) will find niches and "hand craft" software, similar to today when you still can buy hand forged axes etc. Obviously the market for these products will be much smaller but it will exist.

I you love programming you should try to get into the second category. Be a master craftsman.

[anal_reactor]

It feels like it but this is not true.

Imagine that you're given a business problem to solve. You represent the process of writing the code with a graph - each vertex is a git commit. We consider the space of all possible git commits, so the graph is infinite. All vertices are connected with directional edges, and each edge has a value "cost". If you are in commit A and you want to go to commit B, you have to pay the cost from A to B. Your goal is to find a relatively short path from empty git commit to any vertex which contains code that has some specific observable business properties.

You might notice that not everyone is equally smart, so when giving this task to real people, we'll associate "speed" with each person. The higher the speed, the lower the paid costs when traversing the graph. I'll leave the specifics vaguely undefined.

Since a part of the task is to discover information about the graph, we also need to specify that every person has some kind of heuristic function that evaluates how likely given node is to get you closer towards some vertex that can be considered a goal. Obviously, smarter people have heuristic functions that are more closer to ground truth, while stupid people are more biased towards random noise. This also models the fact that it takes knowledge to recognize what a correct solution is.

This model predicts what we intuitively think - smart specialists will quickly discover connections that take them towards the goal and pay low costs associated with them, while idiots will take the scenic route, but by and large will also eventually get to some vertex that satisfies the business requirements, even if it's a vertex that contains mostly low-quality code, because for idiots the cheap edges that seem good at first glance are the only edges they can realistically traverse.

Obviously, if you have a group of people working on the same task, you'll reach the business goal faster. Therefore, a group of people is equivalent to one person with higher speed, and some better heuristic.

This conclusion suddenly creates a well-known, but interesting situation - each smart specialist can be replaced by a group of idiots. Or, the way I heard it, "the theorem of interns - every senior can be replaced by a finite number of interns".

What AI does is it increases people's speed. Not the heuristic function, but the speed. Importantly, the better the heuristic function, the smaller the speed gains. Makes sense - an idiot who doesn't know shit and copy-pastes things from ChatGPT will have massive speed gains, while a specialist will only modestly benefit from AI.

From business perspective though, by having more idiots write more slop with more AI we traverse the graph significantly faster. Sure, we still take the scenic route, and maybe even with AI we take the really fucking long scenic route, but because the speed is so high, it doesn't matter.

And because AI supercharges idiots more than smart specialists, we have a situation where the skill of working with idiots is more valuable on the job market than the skill of doing your job right. Your goal isn't to find the shortest path, or the prettiest code, your goal is to prompt AI as quickly as possible to get you to any vertex that satisfies the business requirements.

[CuriousSkeptic]

Your graph model lack the aspect of increasing complexity. As you traverse the graph every available node gets increasingly more distant. In some areas of the graph less so than others, a good heuristic function not only identifies a single shortest path, but also dense areas of possible value in the graph.

The question is if blind speed scales quicker then distances grow.

[anal_reactor]

That's true, and I guess the reason why we're building so many datacenters is to answer the question how far exactly will blind speed take us, assuming that we fail to make substantial improvements to AI architecture.

[worik]

> Obviously, if you have a group of people working on the same task, you'll reach the business goal faster.

That is not obvious at all.

[biglyburrito]

Inshallah.