Yep

Interesting idea… we actually have a plan to go public in a couple years and I’m holding a few options, but the economy is hitting us like everyone else. I’m no longer optimistic we can reach the numbers for those options to activate

As a developer

• I can jot down a bunch of notes and have ai turn it into a reasonable presentation or documentation or proposal
• zoom has an ai agent which is pretty good about summarizing a meeting. It usually just needs minor corrections and you can send it out much faster than taking notes
• for coding I mostly use ai like autocomplete. Sometimes it’s able to autocomplete entire code blocks
• for something new I might have ai generate a class or something, and use it as a first draft where I then make it work

Not really.

Linter in the build pipeline is generally not useful because most people won’t give results time or priority. You usually can’t fail the build for lint issues so all it does is fill logs. I usually configure a linter and prettifier in a precommit hook, to shift that left. People are more willing to fix their code in small pieces as they try to commit.

But this is also why SonarQube is a key tool. The scanners are lint-like, and you can even import some lint output. But the important part is it tries to prioritize them, score them, and enforce a quality gate based on them. I usually can’t fail a build for lint errors but SonarQube can if there are too many or too priority, or if they are security related.

But this is not the same as a code review. If an ai can use the code base as context, it should be able to add checks for consistency and maintainability similar to the rest of the code. For example I had a junior developer blindly follow the AI to use a different mocking framework than the rest of the code, for no reason other than it may have been more common in the training data. A code review ai should be able to notice that. Maybe this is too advanced for current ai, but the same guy blindly followed ai to add classes that already existed. They were just different enough that SonarQube didn’t flag is as duplicate code but ai ought to be able to summarize functionality and realize they were the same. Or I wonder if ai could do code organization? Junior guys spew classes and methods everywhere without any effort in organizing like with like, so someone can maintain it all. Or how about style? I hope yo never revisit style wars but when you’re modifying code you really need to follow style and naming of what’s already there. Maybe ai code review can pick up on that

Shame. There was a time that people dug out of their own messes, I think you learn more, faster

Yes, that’s how we became senior guys. But when you have deadlines that you’re both on the hook for and they’re just floundering, you can only give them so much opportunity. I’ve had too many arguments with management about letting them merge and I’m not letting that ruin my code base

Speaking of meaningless metrics, how many people ask you for Lines Of Code counts, even today?

We have a new VP collecting metrics on everyone, including lines of code, number of merge requests, times per day using ai, days per week in the office vs at home

I had to sort over 100 lines of data hardcoded into source (don’t ask) and it was a quick function in my IDE.

I feel like “sort” is common enough everywhere that AI should quickly identify the right Google results, and it shouldn’t take 3 min

Code reviews seem like a good opportunity for an LLM. It seems like they would be good at it. I’ve actually spent the last half hour googling for tools.

I’ve spent literally a month in reviews for this junior guy on one stupid feature, and so much of it has been so basic. It’s a combination of him committing ai slop without understanding or vetting it, and being too junior to consider maintainability or usability. It would have saved so much of my time if ai could have done some of those review cycles without me

It may also be self fulfilling. Our new ceo said all upcoming projects must save 15% using ai, and while we’re still hiring it’s only in India.

So 6 months from now we will have status reports talking about how we saved 15% in every project

For some of us that’s more useful. I’m currently playing a DevSecOps role and one of the defining characteristics is I need to know all the tools. On Friday, I was writing some Java modules, then some groovy glue, then spent the after writing a Python utility. While im reasonably good about jumping among languages and tools, those context switches are expensive. I definitely want ai help with that.

That being said, ai is just a step up from search or autocomplete, it’s not magical. I’ve had the most luck with it generating unit tests since they tend to be simple and repetitive (also a major place for the juniors to screw up: ai doesn’t know whether the slop it’s pumping out is useful. You do need to guide it and understand it, and you really need to cull the dreck)

I’m seeing exactly the opposite. It used to be the junior engineers understood they had a lot to learn. However with AI they confidently try entirely wrong changes. They don’t understand how to tell when the ai goes down the wrong path, don’t know how to fix it, and it takes me longer to fix.

So far ai overall creates more mess faster.

Don’t get me wrong, it can be a useful tool you have to think of it like autocomplete or internet search. Just like those tools it provides results but the human needs judgement and needs to figure out how to apply the appropriate results.

My company wants metrics on how much time we’re saving with ai, but

• I have to spend more time helping the junior guys out of the holes dug by ai, making it net negative
• it’s just another tool. There’s not really a defined task or set time. If you had to answer how much time autocomplete saved you, could you provide any sort of meaningful answer?

Yet Chinese cars that meet US standards are quite a bit more than that. Where such vehicles are sold in developed markets, they are more like €30-40k

• https://citymagazine.si/en/chinese-cars-in-europe-why-do-we-pay-almost-double-the-price-of-82-for-the-same-vehicle/

By “legacy manufacturers” I mean those who are stuck on internal combustion engines, and focusing on large trucks and luxury trims.

Average new car price in the US has greatly outpaced inflation and is currently almost $50k, closing in on a full year gross average income. Most people can’t afford that. For that rice you get old technology engine, old technology transmission, same features we’ve had for years.

Yet a replacement for my Subaru is much cheaper, only a little over what I paid nine years ago. It has safety features, electronics, and transmission more innovative than us made cars costing twice as much. Many more people can afford this vehicle, and it’s similar in price to what Chinese cars are selling for in Europe.

We don’t need to compete with $4k cars. We need to compete with cars affordable on average salaries, with new features and unique capabilities.

While the transition to electric vehicles has been politicized, it’s coming and it’s inexorable. “Legacy manufacturers” are those avoiding that change

You’d have an argument if legacy manufacturers were trying. We could talk about support if they were willing. They don’t want it. They’ve already given up

I’m not convinced it’s lack of sales. Trucks are the most profitable to manufacture but sales vary by region and some parts of the country are much more interested in smaller cars, but they ceded that market to Japanese manufacturers

It’s not they they can’t make them or that the sales aren’t there but that trucks are the easy route. They’re more profitable per unit and easier sell in some areas.

Part of this is also sleazy dealerships. Trucks have by far the biggest incentives so sleazy dealerships can get people excited about the “deal” they get over list price

Protecting Detroit from competition would’ve just saddled US consumers with decades more of crappy, overpriced, low quality, cars.

And it did. Japanese companies maintained a solid portion of the market in the US, a notable lead in quality, and many consumers no longer willing to waste money on crappy overpriced low quality cars from American companies. American cars were forced to get better and they’re better off for it, but they resisted the entire time, just like today.

American car companies are focusing on their highest profit center, massive trucks. Milking that market for the short term.

…… regardless of their long term survival. It seems extremely short sighted.

Plus people usually bring it up in a stupid way. Yes they did. Yes we do that too (for all the “we” on the internet). Some amount of that is entirely normal on the global market.

The real problem is US conservatives who understand car manufacturing is a strategic industry but do not want to give that guidance to aid the transition to new technology, US politicians who can’t cooperate on a coherent long term industrial policy, US politicians who can’t look beyond short term profits for their corporate owners, or outrage headlines for their constituents. There’s nothing magical about Chinese companies taking over the industry, nothing hidden, just politicians establishing a strategy and sticking with it long enough to benefit

Targeted tariffs and protectionism can help a situation like this, combined with subsidies like the ones Trump cancelled, to give legacy manufacturers a temporary respite to retool and innovate. However backtracking on your transition, reverting to the tried and true short term profits is just hiding your head in the sand. GM will find itself increasingly marginalized and more years behind. You can’t hide behind trumps skirt forever

The problem is the world is transitioning to EVs, and burying your head in the sand won’t change that. Legacy manufacturers could be trying to find their place in the new world while they can, or they can stick with technology of the past, let someone else come to dominate the new technologies, and be left with a ever shrinking market until they disappear

That makes sense. Thanks for helping clarify

Maybe I read this differently than you. I don’t see this as volunteering personal time, but asking people during their work time to help iwith a different job. Not that the article says either way, but volunteering personal time seems unlikely