Software engineering is so back.

When designing systems, you want the important details to be right. Especially with authentication and authorization.

From an architecture level, you can know which classes are important to review and which ones are not.

Yeah that is how I see it.

In Software Engineering, we learned about requirements, testings, system design, UMLs, etc, and those seems to be more relevant than ever.

Agile is dead. It presumed writing the code was the slowest part of the cycle. Now it makes more sense to only start writing code when the requirements are known as the code is quick and low cost to change if/when the requirements change later.

There are two problems that arise from cheap code:

1. You get complexity back at the speed that you add code. Also the complexity compounds.

2. As a human you are still responsible for your code, and you need to understand how the important parts of the code base work.

When you combine these problems, you get a complicated code base where you don't understand the important parts.

That is why software design is getting a comeback. It actually helps with both problems. Less complexity and more understanding.

It is insane from a consumer point of view. Luna is cheap and smart enough to do many agentic tasks. Cheap enough so that you can put it on a website without auth.

The Jev model is economically, but also in terms of compute, a much more efficient model. A normal LLM goes token by token, each token in a separate step. Whereas Jev just returns all the results the first round. So it is much better at classification than LLMs.

Compared to traditional ML classification, Jev works without training, like a LLM.

MCPs are winning because within the ChatGPT and Claude apps, there are Plugin stores. These plugins are one-click installation MCP servers, with support for authentication. This is what business users are using.

Exactly this. It’s a very effective way to integrate your app into Claude/openai.

I was anti-MCP at one point when it was eating up a substantial amount of context in Claude code. That’s largely been fixed now.

From my perspective, they are a great way to wrap an API for agent consumption. I can see a future where every major commercial or service website (think airline websites) have an MCP your agent can use to check flight status, rebook, or check you in.

To be fair, after visiting some trade shows recently, a lot of these “parasitic” LLM startups are not very convincing from a business-use case perspective. (They’re not really parasitic, more like a remora attaching itself to a shark, the shark being OpenAI or Anthropic).

At IMTS at Chicago the skepticism amongst the visitors towards AI and pure-AI startups was at an all-time high. More than once I heard, “Oh yeah I visited that AI booth and they couldn’t explain what value they would add to my business.”

So in that sense, while MCPs are “winning”, I also see them as a significant part of the AI “bubble”, specifically solutions looking for problems backed by VC money.

The most interesting use case in my mind is skipping law suits. Obviously you need lawyers in court. But lawyers are people you are basically paying to fight for you.

Instead, if you resolve your dispute outside of court, you don’t need a lawyer. If both parties use ChatGPT to find the relevant laws or read contracts, they could come to an agreement without expensive legal fees.

except for those pesky things called rights

Given the approach from the article, you can commit the hints to git and run tests for verification. The model would be used during coding.

A question I have, with the type { output: string }, would the model not become a LLM? And if it does, shouldn’t it cost the same as a LLM for output?

strings (and all sequential data structures) are not allowed at all - this is how we make sure all outputs can be computed in parallel (thus no output token cost)

I don’t see this as an option in their website

You could theoretically ask “what is the next appropriate character?” and add the entire ascii charset but i doubt it’d work well and you’d be implementing autoregressive churn across network latency…

This voice model can do tool calling. So as long you give it powerful tools, I believe it to be useful.

I can understand the concerns but at the same time it feels weird to deny young people the ability to make their ideas reality. I got proper internet access when I was 12 and that is how I taught myself how to program.

I think over time due the regulations like these younger generations in western countries like US/UK would fall far behind compared to the counterpart in India or China when it comes to AI fluency.

I remember when I was a kid growing up there was the same negative perception on internet back then and most people were not allowing internet access to their kids because of porn. But I had access since I was 13 (it was still dial-up) and thank god I did because I wouldn't be a software engineer if I hadn't.

I taught myself on how to build web pages in dreamweaver, program in visual basic and even to make animations in flash by the time I was 14. One could argue that young kids should learn those skills without the help of AI, but then again, one could argue that I should have learned computing by punch hole and assembly language to learn how it actually works.

What people don't realize is that soon AI would be a new abstraction layer, same as the high level language abstraction we've learned and those languages won't matter just like we don't worry about assembly right now, and I truly feel sorry for the kids that's gonna miss the opportunity to learn AI on their own.

If you give an average classroom of 12 year olds free access to AI, do you think the AVERAGE effect will be that the kids will use the AI to dive really deep into topics and learn programming, or that they will copy and paste the solutions to their homework, and use the freed up time to do other things than study?

Perhaps they can make their ideas reality by learning the fundamentals required to do these things.

As much as I think AI is a productivity enhancer, I still think that it's beneficial for people who are still developing their brains.

Kids should be thinking for themselves, they barely know how to do it yet.

That’s an excellent philosophy that ought be applied to your own child but not extended to others.

I'm not telling anyone how to raise their children, companies have terms of service. When we can't accurately assess risk, the default we reach for is an age minimum (social media, alcohol, driving).

If, in time, we find out that AI usage during developmental learning periods is a major positive, I'm sure they will give AI to 5 year olds, and I'm all for that.

Though, I have a sneaking suspicion it could be similar to kids with tablets. It encourages isolation, rewards addictive behavior, stunts personal growth, and enforces the concept of instant gratification.

That is an unnecessary default and also generalizes AI to the point of being analytically not useful.

> ... at the same time it feels weird to deny young people the ability to make their ideas reality.

I'd not realised the ban covers child brains too. /i

And children will still have access to the internet and resources to teach themselves how to program.

That's a silly reply.

Imagine telling a kid to chisel what they want out of the marble line by line with a straight face when they can clearly see people appearing entire programs into existence in minutes.

Imagine telling a kid they have to learn arithmetic while there's a kid next to him with a calculator.

Imagine telling a kid they have to learn to paint the barn with a brush before they get to use the $12,000 spray rig.

Imagine telling a kid they have to learn to wash mom's car with a sponge and bucket when there's a drive-through car wash down the street.

Imagine telling a kid they have to master a Walmart 20" bicycle before they get to use the Trek Madone $16,000 road bike.

This idea that kids must have it maximally easy is ridiculous. Something broke with parenting in the last few decades because this isn't normal thinking. We are supposed to help children develop themselves into adults, not give the excuses not to. That's some goddamned lazy parenting.

The kid that learns, by the end of their education, to use the more advanced tools is going to economically out competed as an adult by the kid that got stuck learning how to do things the old fashioned way. Amish communities exist snd are productive, but they aren’t competing with graduates from Chinese universities.

I totally agree with the progression though. Learning the old ways (or cheap ways) can help understand the new ways, as long as you eventually progress to the new ways. China, for example, still tests a lot of Euclidean geometry on the gaokao (national tests) even if it is basically obsolete compared to trigonometry, but they have no better way of testing proof skills.

> The kid that learns, by the end of their education, to use the more advanced tools is going to economically out competed as an adult by the kid that got stuck learning how to do things the old fashioned way.

Source?

My first language was RISC Assembly, and it greatly simplified understanding how computers function.

There was no Internet, but rather books in a place called a Library with something called informative context. =3

There are also people arguing that children should have no internet access because its harmful.

But children do have access to internet and often with some protections.

This is also how I feel about AI, where a full ban is the lazy way out. Similarly like the internet, it is not possible to 100% protect a child every potential harmful AI interaction.

Indeed, it is almost like most adults care about kids getting a good healthy start in life, and avoiding the horrendous mistakes of falling for psychopathic cons. =3

Once you know this, you cannot unsee this in every AI design everywhere