japhyr

I've only implemented support for one provider at the moment, but it is structured in a way where I can add support for any other providers or local models. It feels good to not be locked into any one company's models or harness.

Yes, it's so easy to build a harness for a lot of use cases now, and you learn so much from doing so.

I'm a solo developer, and I didn't want to sort out all the boundaries and permissions of Claude or other heavy harnesses. All I wanted was something that can read, write, and modify files in a project directory. I gave myself three days to see if I could make a harness that was complete enough to work on my own projects. It was usable in less than a day.

I love using it, because I know exactly what its boundaries are, and how they're enforced. When I need more features I can either implement them in my own harness, or choose a heavier harness with much clearer understanding of what to look for.

When people have gotten excited about having so many tests, I've asked them what their plan is when 500 of their 1000 test suddenly stop passing. I've always favored 50 tests I know are meaningful, where any failure is something to respond to, over 500 tests with a bunch of overlap and edge cases I'm not sure matter. But now people aren't even thinking about that, they're just letting the agents make all those decisions.

I think this approach will continue to work for some people and orgs, but others are going to hit walls where their agents can't manage the mountains anymore. It's going to be interesting to see how people and orgs respond when that happens.

He doesn't really think, he reacts. And his every reaction is centered around "How can I make this about me?"

I like this article. We've read a lot of takes quite similar to this, and I think it's worth continuing to write and share reflections just like this.

> Yet, through much effort and 40 years of debate we had reached an equilibrium. Now AI has thrown that out the window.

The only thing I'd like to add here is that "AI" in this sentence should really be read as "the companies building frontier AI models have thrown this out the window". I don't necessarily think the author should have used a phrase like that, because it gets quite pedantic to read posts where such precise language is used all the time. But when we talk about where to go as an industry and as a society, we need to keep that distinction in mind.

The tech is here to stay, but the tech itself is not what's thrown our norms out the window. It's the people running these companies who are putting their vision and their profits above everyone else in the world. Most of us are exploring this tech and trying to figure out what it's useful for. It's a much harder question to try and figure out what to do about the people using this tech to consolidate wealth and power. We can't hold a technology responsible for anything, but we can hold people responsible for their impact on everyone else.

I'm the author of Python Crash Course, and I got this exact same email this week. I was thinking of writing a public response as well, because any attempt to sincerely answer these questions takes something along the lines of a full post. It's also worth a public response because many people who are getting into programming for the first time right now are asking variations of these same questions.

> Do I think that AI enables people to develop faster than they can keep up?

Absolutely. That's the core of this person's email, and everyone else who asks similar questions. Just five years ago, the only way to build a working project of moderate complexity was to learn the basic to intermediate concepts required to make an MVP. Now, if you can steer an LLM reasonably well, you can quickly build an MVP that goes well beyond your own understanding of the implementation.

I don't think anyone has clear answers to all the questions brought up in this email. I think people can learn faster than they used to, because they can make connections between different areas faster than they used to. But it requires skill and discipline in how you learn, and how you work. You have to intentionally build your understanding as you build your projects.

Are you seeing companies that are in over their heads because they don't have enough domain knowledge?

I think that's always been an issue in tech, but it feels like AI exacerbates the issue. I see people starting companies and services where their primary domain knowledge seems to be whatever their AI tells them. It's sometimes enough to get off the ground, but I wonder how long it takes for customers/clients who actually need the domain knowledge to bail.

> I did a full (human) blank page rewrite three days ago

You did a "blank page rewrite" of a 576 page book "three days ago"?

Of course everyone hates AI. For most people, it's actively making their lives worse, not better.

AI is a really effective technology when used with restraint, in appropriate places. But it's rarely being used with restraint, and it's being inserted just about everywhere.

If you're trying to work in AI on a product related to education, you've got a really high bar to clear to prove that you're actually helping students learn better, and teachers teach better.

I didn't see this until this morning, and the continuing through for the whole 18 words was a really good experience. I got 14/18, and that was much more satisfying than ending at my first failure.