(Author here) Haha that is a great point. I was trying to come up with a term that described my personal workflow and specifically felt different than vibe coding (because it's geared towards how professional programmers can use agents). Very open to alternative terms!

Exactly. I think the traditional meaning of “asynchronous programming” was coined first. So, let’s stick with that.

Same! I was hoping this would have some insights into pitfalls or the like with javascript promises or python async, but alas no such luck.

Same here. I've read the author's braintrust.dev as "brain - Rust - Dev", so I was expecting a discussion on Rust Async development.

I disagree with being detailed, many times I want to AI to think of things, half the time it comes up with something I wouldn't have that I like.

The thing I would add is to retry to prompt, don't tell it to fix a mistake. Rewind and change the prompt to tell It not to do that it did.

(Author here) I can certainly appreciate having an alternate perspective, but I think it's unfair to say it's DOA. I've personally used this workflow for the last 6 months and shipped a lot of features into our product, including the lowest levels of infra all the way to UI code. I definitely think there is a lot to improve. But it works, at least for me :)

Figuring out what you want is the hard part about programming. I think that's where AI augmentation will really shine, because it lowers the time between iterations and experiments.

That said, this article is basically describing being a product owner.

You're right, reviews aren't the way forward. We don't do code reviews on compiler output (unless you're writing a compiler). The way forward is strong static and analytic guardrails and stochastic error correction (multiple solutions proposed with LLM as a judge before implementation, multiple code review agents with different personas that have been prompted to be strict/adversarial but not nit-pick) with robust test suites that have also been through multiple passes of audits and red-teaming by agents. You should rarely have to look at the code, it should be a significant escalation event like when you need to coordinate with Apple due to XCode bugs.

Coding interview of the future: "Show us how you would prompt this binary sort."

(Author here) Personally, I try to combat this by synchronously working on 1 task and asynchronously working on others. I am not sure it's perfect, but it definitely helps me avoid atrophy.

What the article describes is:

1. Learn how to describe what you want in an unambiguous dialect of natural language.

2. Submit it to a program that takes a long time to transform that input into a computer language.

3. Review the output for errors.

Sounds like we’ve reinvented compilers. Except they’re really bad and they take forever. Most people don’t have to review the assembly language / bytecode output of their compilers, because we expect them to actually work.

For generative skills I agree, but for me the real change is in how I read and debug code. After reading so much AI-generated code with subtle mistakes, I can spot errors much quicker even in human-written code. And when I can't, that usually means the code needs a refactor.

I'd compare it to gym work: some exercises work best until they don't, and then you switch to a less effective exercise to get you out of your plateau. Same with code and AI. If you're already good (because of years of hard won lessons), it can push you that extra bit.

But yeah, default to the better exercise and just code yourself, at least on the project's core.

so... normal team lead -> manager pipeline?

Agreed.

> Hand it off. Delegate the implementation to an AI agent, a teammate, or even your future self with comprehensive notes.

The AI agent just feels like a way to create tech debt on a massive scale while not being able to identify it as tech debt.

I think it can only work if the product owner literally owns the product as in has FULL decision making power about what goes or doesn't go etc. it doesn't work when a product manager is a glorified in between guy, dictating the wishes of the CEO through a game of telephone from the management.

I do think that AI will work well compared to the low end of offshoring, where to get good results you need people who could do the work themselves tightly involved. AI will give you slop code faster and cheaper, and that is sometimes enough.

The question is how it compares to the medium level of offshoring. Near term I think that at comparable cost ($100s of dollars per week), it'll give faster results at an acceptable tradeoff in quality for most uses. I don't think most companies want to spend thousands of dollars a month on developer tools per developer though... even though they often do.

I was ready for a deep-dive into things like asyncio in python; where it came from and what problems it promised to solve!

They don't really as once the spec gets detailed enough it becomes so large and unwieldy that nobody with any actual power reads the things.

An executive at a large company once told me about something where a spec had been written and reviewed by all relevant stakeholders: "That may be what I asked for, but its not what I want."

Async/await themselves are not that much magic really, it's a bit of syntactic sugar over promise chains. Of course, understanding promises is its own bag.

ChatGPT explanation: https://chatgpt.com/share/68c30421-be3c-8011-8431-8f3385a654...

To elaborate a bit, telling them that you should not "aList.foreach(asyncMethod)", but you'd better do "Promise.all(aList.map(asyncMethod))" is NOT very easy for them.

Man are you going to be disappointed when you read the article.

Indeed! Why not just call it "asynchronous software development" or something similar? "asynchronous programming" is a bad choice, partly because it will be un-googleable.

I actually enjoy writing code... most of the time. I find myself turning to AI to write code I have an aversion to writing, not as a substitute for my own practice, but to get code that I would not have written in the first place. Like benchmarks, bash scripts, dashboards, unit tests, etc.

I can live without these things, but they're nice to have without expending the effort to figure out all the boilerplate necessary for solving very simple problems at their core. Sometimes AI can't get all the way to a solution, but usually it sets up enough of the boilerplate that only the fun part remains, and that's easy enough to do.