In my experience (15+ years), the biggest trade-off is a lack of technical innovation. Current AI is unable to innovate. Humans can, but doing so requires spending extended periods deep in the code and building a solid mental model of the system.

Just like GPs argument about quality; the majority of businesses doesnt need innovation and often even fights it.

I’ve been in the industry for a much shorter period than both of you; but the companies I worked for didnt really innovate anything.

Businesses in a competitive market need some kind of innovation to do better than their competition. This doesn't have to be software of course, but often software does play some part in it. And it doesn't mean it's their in-house software, but someone has to develop it after all.

Most of the "innovation" I'm seeing is coming out of non-engineering teams vibe coding solutions or operational harnesses based on their non-engineering domain expertise.

It is fairly mortifying to watch them build solutions in hours or days that are designed better than the projects they were prescribing to product engineering teams to take literal months to spike, PRD, build - then maintained and governed better - with no real understanding of how it works.

Obviously lots of caveats to be made here, but fascinating to watch it play out (at least in places where infosec is robust enough to give a sales manager access to Claude Code).

I find it interesting how we want to make war on russia and china while our entire society relies more and more on completely unsecured software that they can take down and disrupt us with very little effort.

In my mind we should be much more defensive before we even think about doing anything offensive.

No, they don't. There are multiple businesses doing the same thing serving the same market in all kinds of industries.

>the biggest trade-off is a lack of technical innovation.

Most businesses and developers shouldn't be innovating, but instead providing secure solutions to their clients. The last 30 years of "innovation" has given us countless security bugs.

There’s certainly more software being made now than before, which necessarily increases the number of (security) bugs. There are also a lot more users and use cases (e.g. smartphones).

But I’m not at all convinced that 30 years ago things were appropriately secure or usable.

Or in the enterprise world it's given us billions of dollars of waste by re implementing the wheel

What I wonder then is...is it going to be the final word on the evolution of software development? AI has been trained on practices that were developed by people, by professionals and amateurs, by discussions on discussion boards, at tech events, through written books and then disseminated across open source projects. If no one writes code anymore then how to write and build software projects will never evolve beyond the 2022 state of affairs.

That data goes into pretraining the initial model. The agentic post-training relies on the model making stochastic exploration. So in a sense it learns via trial and error. By the accounts I have read, this second stage is the dominant reason we have seen the increase in model capabilities in the past year. It is still not clear how innovative the models can be, but they are not just relying on static data.

It seems like we have more innovation around "developer(=agent) experience" than ever. Look at all the people building various agent control plane systems, containers, isolation, issue tracking, project management etc.

That’s software engineering bubble.

Go out to a bakery, tire shop see how much they innovate. Then go one rung up to services they consume like insurance and banking. All of this chain is super conservative.

innovation is about being able to reach for better solutions to problems where previously it would "take too long". e.g. DSLs.

Product quality still matters which is a result of code quality rather than the number of features you've shipped in the last week.

You are both correct.

We'll have to wait and see how many companys get hurt by overuse of AI coding, the one I work at included.

Codex/CC and other OpenAI and Anthropic products like Dots, are examples of how quickly real products can be built today. But to me, they feel more like mediocre products bloated with feature slop. Nothing extraordinary or technologically innovative.

Pi.dev and Cursor's Tab completion are two of the most innovative and extraordinary products I know in AI era, and both were built by humans, at least in their "breakthrough" stages.

Simply adding features doesn't make the product or technology exceptional. I think the industry know in the phase like "ok, i can close my one thousand github tickets in a week". But that won't make their product or technology significantly better. Creating an extraordinary product is an extra ordinary task that only humans are capable of for now.

For the first time in history, a $1T company is trying to solve a problem that none of its paying customers actually have.

I am curious what does the first and probably the last human who solved a millennium problem thinks about this.

It like saying before the ai era that you don’t have a problem you can’t solve without ai

Almost everything is true about Azure as well, especially obscure pricing and complexity in absolutely everything.

Where are the solutions to the problems?

I don't see them. Perhaps a reasoning LLM can generate them. Anyway, my interest is simply in learning techniques that are relevant to programming.

Where can I find solutions to the problems in the course?