Some citizens are not as fortunate to live in a country which issues passports accepted in so many places.

I also won the passport lottery.

- Companies using investment funds to play the Ai Agent lottery will run out of funds

- Less tokens will be demanded, causing AI companies to raise prices to pay for overheads

- Bubble pops.

Trusted engineers (of open source projects) can deliver me stone, both the authors and the community (often >100,000 devs) have checked that a specific block is stone and can bear the load.

AI is proven to output all sorts of random stuff. Sometimes a pebble, sometimes foam. It almost always looks like stone to most analysis. However as soon as it's load bearing it's likely to crumble.

Agentic agents have a habit of rebuilding the pyramid and randomly replacing stone blocks with "something else" but we don't know what just yet.

But due to the sunk cost fallacy and the belief that others have made this work you'll keep plowing money into the AI Slot machine.

Such is true for many bugs. Even if you have unit tests, they only test on things you've thought of. It's usually the stuff you haven't thought of that gets you.

No reason not to unit test of course, but don't get a false sense of complacency or assume testing is easy either. That's why it's great to do things very carefully (and probably not with AI Agents).

What's also annoying is that AI's approach is not consistent within a project, a different sort of complexity.

Anyway the use case for me is to realize a new visual style through graphics programming. It's a lot less measurable for an interative AI agent than "Meet this hardware specification from a device with a discoverable API"

I have no doubt AI could create a LOT of variations on "a new visual style" but it's less controllable than just doing it yourself.

Btw, did you "understand" the sound driver after the AI coded it? Could you modify it without further help?

Look, goals can differ. If you don't need to understand and predict every part of the code the AI is generating and you just need it to meet a "sketch" of what you want - by all means use AI. I do use AI in that situation for related or unimportant code.

But if you need full understanding, in my experience the only way to get that is to program it yourself. Unless what the AI is generating is so trivial you already understand it and it's grunt work, you will learn the detail by doing it yourself. Controlling the approach here is important.

However often the best way to handle grunt work is to write better abstractions, something AI sucks at.

It's the programming equivalent of many PG essays. https://www.paulgraham.com/useful.html for instance. There was one on how PG refined their thoughts via writing. It's in there somewhere.

If I understand something, I could write it in assembly if I wanted to. It might take a long time, but I know every level of the stack under my code down to bare metal.

Maybe an AI level of "understand" i.e the same understanding a Senior has of a Junior's code based on daily check-ins is enough for 95% of "boring" programming. But for some tasks you need to either fully understand the code or just tolerate bugs.

At the level of complexity I work at, it's (often) faster to just code it myself than to expect AI to converge on a result I like and then hand check it.

Also, if you finish your work on a module with care - you return to a module you can trust with clear boundraries and known flaws. This is not true of AI output.

Use an encouraging tone. Adopt a skeptical, questioning approach. Call me on things which don't seem right. List possible assumptions I'm making if any.

However, how do you inject logic INTO the middle of a function?

Say you have a function which can iterate over any list and given a condition do a filter. How do you inject the condition logic into that filter function?

In the C days you would use a function pointer for this. C++ introduced templating so you could do this regardless of type. Lambdas make the whole process more ergonomic, it's just declaring a one-shot function in place with some convenient syntax.

In rust instead of the full blown

fn filter_condition(val: ValType) -> bool { // logic }

I can declare a function in place with |val|{logic} - the lambda is just syntactic sugar to make your life easier.

1. Glazes me 2. Lists a variety of assumptions (some can be useful / interesting)

Answers the question

At least this way I don't spend a day pursuing an idea the wrong way because ChatGPT never pointed out something obvious.

Also this calculation probably assumes no baseload power imported from the grid, where means such as wind and tidal power work year-round and help offset the need for batteries.

In a 100% renewable world we would not be extracting or refining oil. Natural gas (used by these turbines) is a byproduct of oil drilling. Were we not burning the oil, the natural gas might be too expensive alone.

Also, in a 100% renewable world we would (by definition) have enough generation all the time - (covered by batteries and good baseload sources) that turbine power was no longer required to cover peak loads.