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I personally found out that knowing how to use ai coding assistants productively is a skill like any other and a) it requires a significant investment of time b

by ithkuil 8mo ago

I personally found out that knowing how to use ai coding assistants productively is a skill like any other and a) it requires a significant investment of time b) can be quite rewarding to learn just as any other skill c) might be useful now or in the future and d) doesn't negate the usefulness of any other skills acquired on the past nor diminishes the usefulness of learning new skills in the future

pipes 8mo ago
On the using AI assistants I find that everything is moving so fast that I feel constantly like "I'm doing this wrong". Is the answer simply "dedicate time to experimenting? I keep hearing "spec driven design" or "Ralph" maybe I should learn those? Genuine thoughts and questions btw.
- bobthepanda 8mo ago
  I think find what works for you, and everything else is kind of noise. At the end of the day, it doesn’t matter if a cat is black or white so long as it catches mice. —— Ive also found that picking something and learning about it helps me with mental models for picking up other paradigms later, similar to how learning Java doesn’t actually prevent you from say picking up Python or Javascript
- gnatolf 8mo ago
  Everybody feels like this, and I think nobody stays ahead of the curve for a prolonged time. There's just too many wrinkles. But also, you don't have to upgrade every iteration. I think it's absolutely worthwhile to step off the hamster wheel every now and then, just work with you head down for a while and come back after a few weeks. One notices that even though the world didn't stop spinning, you didn't get the whiplash of every rotation.
- gnatolf 8mo ago
  More specifically regarding spec-driven development: There's a good reason that most successful examples of those tools like openspec are to-do apps etc. As soon as the project grows to 'relevant' size of complexity, maintaining specs is just as hard as whatever other methodology offers. Also from my brief attempts - similar to human based coding, we actually do quite well with incomplete specs. So do agents, but they'll shrug at all the implicit things much more than humans do. So you'll see more flip-flopped things you did not specify, and if you nail everything down hard, the specs get unwieldy - large and overly detailed.
  - zozbot234 8mo ago
    > if you nail everything down hard, the specs get unwieldy - large and overly detailed That's a rather short-sighted way of putting it. There's no way that the spec is anywhere as unwieldly as the actual code, and the more details, the better. If it gets too large, work on splitting a self-contained subset of it to a separate document.
    - lelanthran 8mo ago
      > There's no way that the spec is anywhere as unwieldly as the actual code, and the more details, the better. I disagree - the spec is more unwieldy, simply by the fact of using ambiguous language without even the benefit of a type checker or compiler to verify that the language has no ambiguities.
      - skydhash 8mo ago
        People are keen to forget that programming languages are specs. And a good technique for coding is to build up you own set of symbols (variables, struct, and functions) so that the spec become easier to write and edit. Writing spec with natural language is playing russian roulette with the goals of the system, using AI as the gun.
- Our_Benefactors 8mo ago
  I don’t think Ralph is worthwhile, at least the few times I’ve tried to set it up I spent more time fighting to get the configuration right than if I had simply run the prompt. Coworkers had similar experiences, it’s better to set a good allowlist for Claude.
secbear 8mo ago
Agreed, my experience and code quality with claude code and agentic workflows has dramatically increased since investing in learning how to properly use these tools. Ralph Wiggum based approaches and HumanLayer's agents/commands (in their .claude/) have boosted my productivity the most. https://github.com/snwfdhmp/awesome-ralph https://github.com/snwfdhmp/awesome-ralph https://github.com/humanlayer https://github.com/humanlayer
imiric 8mo ago
> knowing how to use ai coding assistants productively is a skill like any other No, it's different from other skills in several ways. For one, the difficulty of this skill is largely overstated. All it requires is basic natural language reading and writing, the ability to organize work and issue clear instructions, and some relatively simple technical knowledge about managing context effectively, knowing which tool to use for which task, and other minor details. This pales in comparison with the difficulty of learning a programming language and classical programming. After all, the entire point of these tools is to lower the required skill ceiling of tasks that were previously inaccessible to many people. The fact that millions of people are now using them, with varying degrees of success for various reasons, is a testament of this. I would argue that the results depend far more on the user's familiarity with the domain than their skill level. Domain experts know how to ask the right questions, provide useful guidance, and can tell when the output is of poor quality or inaccurate. No amount of technical expertise will help you make these judgments if you're not familiar with the domain to begin with, which can only lead to poor results. > might be useful now or in the future How will this skill be useful in the future? Isn't the goal of the companies producing these tools to make them accessible to as many people as possible? If the technology continues to improve, won't it become easier to use, and be able to produce better output with less guidance? It's amusing to me that people think this technology is another layer of abstraction, and that they can focus on "important" things while the machine works on the tedious details. Don't you see that this is simply a transition period, and that whatever work you're doing now, could eventually be done better/faster/cheaper by the same technology? The goal is to replace all cognitive work. Just because this is not entirely possible today, doesn't mean that it won't be tomorrow. I'm of the opinion that this goal is unachievable with the current tech generation, and that the bubble will burst soon unless another breakthrough is reached. In the meantime, your own skills will continue to atrophy the more you rely on this tech, instead of on your own intellect.
- Our_Benefactors 8mo ago
  > In the meantime, your own skills will continue to atrophy the more you rely on this tech, instead of on your own intellect You’re right. I’m going back to writing assembly. These compilers have totally atrophied my ability to write machine code!
isodev 8mo ago
The addictive nature of the technology persists though. So even if we say certain skills are required to use it, then also it must come with a warning label and avoided by people with addictive personalities/substance abuse issues etc.
- mettamage 8mo ago
  It's addictive because of a hypothesis I have about addiction. I have no data to back it up other than knowing a lot of addicted people and I have studied neuroscience, yet I still think there's something to it. It's definitely not fully true though. Addiction occurs because as humans we bond with people but we also bond with things. It could be an activity, a subject, anything. We get addicted because we're bonded to it. Usually this happens because we're not in fertile grounds to bond with what we need to bond with (usually a good group of friends). When I look at addicted people a lot of them bond with people that have not so great values (big house, fast cars, designer clothing, etc.), adopt those values themselves and get addicted to drugs. This drugs is usually supplied by the people they bond with. However, they bond with those people in the first place because of being aimless and receiving little guidance in their upbringing. I'm just saying all that to make it more concrete with what I mean about "good people". Back to LLMs. A lot of us are bonding with it, even if we still perceive it as an AI. We're bonding with it because when it comes to certain emotional needs, they're not being fulfilled. Enter a computer that will listen endlessly to you and is intellectually smarter than most humans, albeit it makes very very dumb mistakes at times (like ordering +1000 drinks when you ask for a few). That's where we're at right now. I've noticed I'm bonded with it. Oh, and to some who feel this opinion is a bit strong, it is. But consider that we used to joke that "Google is your best friend" when it just came out and long thereafter. I think there's something to this take but it's not fully in the right direction I think.
sidrag22 8mo ago
As much as i loved the relation of vibe coding to slots and their related flow states in this article, I also think what you are stating is the exact reason these tools are not the same as slots, the skill gap is there and its massive. I think there are a ton of people just pulling the lever over and over, instead of stepping back and considering how they should pull the lever. When you step back and consider this, you are for sure going to end up falling deeper into the engineering, architecture realm. Ensuring that continually pulling the lever doesn't result in potential future headaches. I think a ton of people in this community are struggling with the lose of flow state, and attempting to still somehow enter it through prompting. The game in my view has just changed, its more about just generating the code, and being thoughtful about what comes next, its rapid usage of a junior to design your system, and if you overdue the rapidness the junior will give you headaches.
- skydhash 8mo ago
  > I think there are a ton of people just pulling the lever over and over, instead of stepping back and considering how they should pull the lever There are deeper considerations like why pull the lever, or is it the correct lever? So many api usages is either seeing someone using a forklift to go the gym (bypassing the point), using it to lift a cereal box (overpowered), or using it to do watchmaking (very much the wrong tool). Programming languages are languages, yes. But we only use them for two reasons. They can be mapped down to hardware ISA and they’re human shaped. The computer doesn’t care about the wrong formula as long as they can compute it. So it falls on us to ensure that the correct formula is being computed. And a lot of AI proponents is trying to get rid of that part.

by ithkuil 8mo ago

pipes 8mo ago

On the using AI assistants I find that everything is moving so fast that I feel constantly like "I'm doing this wrong". Is the answer simply "dedicate time to experimenting? I keep hearing "spec driven design" or "Ralph" maybe I should learn those? Genuine thoughts and questions btw.

bobthepanda 8mo ago
I think find what works for you, and everything else is kind of noise. At the end of the day, it doesn’t matter if a cat is black or white so long as it catches mice. —— Ive also found that picking something and learning about it helps me with mental models for picking up other paradigms later, similar to how learning Java doesn’t actually prevent you from say picking up Python or Javascript
gnatolf 8mo ago
Everybody feels like this, and I think nobody stays ahead of the curve for a prolonged time. There's just too many wrinkles. But also, you don't have to upgrade every iteration. I think it's absolutely worthwhile to step off the hamster wheel every now and then, just work with you head down for a while and come back after a few weeks. One notices that even though the world didn't stop spinning, you didn't get the whiplash of every rotation.
gnatolf 8mo ago
More specifically regarding spec-driven development: There's a good reason that most successful examples of those tools like openspec are to-do apps etc. As soon as the project grows to 'relevant' size of complexity, maintaining specs is just as hard as whatever other methodology offers. Also from my brief attempts - similar to human based coding, we actually do quite well with incomplete specs. So do agents, but they'll shrug at all the implicit things much more than humans do. So you'll see more flip-flopped things you did not specify, and if you nail everything down hard, the specs get unwieldy - large and overly detailed.
- zozbot234 8mo ago
  > if you nail everything down hard, the specs get unwieldy - large and overly detailed That's a rather short-sighted way of putting it. There's no way that the spec is anywhere as unwieldly as the actual code, and the more details, the better. If it gets too large, work on splitting a self-contained subset of it to a separate document.
  - lelanthran 8mo ago
    > There's no way that the spec is anywhere as unwieldly as the actual code, and the more details, the better. I disagree - the spec is more unwieldy, simply by the fact of using ambiguous language without even the benefit of a type checker or compiler to verify that the language has no ambiguities.
    - skydhash 8mo ago
      People are keen to forget that programming languages are specs. And a good technique for coding is to build up you own set of symbols (variables, struct, and functions) so that the spec become easier to write and edit. Writing spec with natural language is playing russian roulette with the goals of the system, using AI as the gun.
Our_Benefactors 8mo ago
I don’t think Ralph is worthwhile, at least the few times I’ve tried to set it up I spent more time fighting to get the configuration right than if I had simply run the prompt. Coworkers had similar experiences, it’s better to set a good allowlist for Claude.

secbear 8mo ago

Agreed, my experience and code quality with claude code and agentic workflows has dramatically increased since investing in learning how to properly use these tools. Ralph Wiggum based approaches and HumanLayer's agents/commands (in their .claude/) have boosted my productivity the most. https://github.com/snwfdhmp/awesome-ralph https://github.com/snwfdhmp/awesome-ralph https://github.com/humanlayer https://github.com/humanlayer

imiric 8mo ago

> knowing how to use ai coding assistants productively is a skill like any other No, it's different from other skills in several ways. For one, the difficulty of this skill is largely overstated. All it requires is basic natural language reading and writing, the ability to organize work and issue clear instructions, and some relatively simple technical knowledge about managing context effectively, knowing which tool to use for which task, and other minor details. This pales in comparison with the difficulty of learning a programming language and classical programming. After all, the entire point of these tools is to lower the required skill ceiling of tasks that were previously inaccessible to many people. The fact that millions of people are now using them, with varying degrees of success for various reasons, is a testament of this. I would argue that the results depend far more on the user's familiarity with the domain than their skill level. Domain experts know how to ask the right questions, provide useful guidance, and can tell when the output is of poor quality or inaccurate. No amount of technical expertise will help you make these judgments if you're not familiar with the domain to begin with, which can only lead to poor results. > might be useful now or in the future How will this skill be useful in the future? Isn't the goal of the companies producing these tools to make them accessible to as many people as possible? If the technology continues to improve, won't it become easier to use, and be able to produce better output with less guidance? It's amusing to me that people think this technology is another layer of abstraction, and that they can focus on "important" things while the machine works on the tedious details. Don't you see that this is simply a transition period, and that whatever work you're doing now, could eventually be done better/faster/cheaper by the same technology? The goal is to replace all cognitive work. Just because this is not entirely possible today, doesn't mean that it won't be tomorrow. I'm of the opinion that this goal is unachievable with the current tech generation, and that the bubble will burst soon unless another breakthrough is reached. In the meantime, your own skills will continue to atrophy the more you rely on this tech, instead of on your own intellect.

Our_Benefactors 8mo ago
> In the meantime, your own skills will continue to atrophy the more you rely on this tech, instead of on your own intellect You’re right. I’m going back to writing assembly. These compilers have totally atrophied my ability to write machine code!

isodev 8mo ago

The addictive nature of the technology persists though. So even if we say certain skills are required to use it, then also it must come with a warning label and avoided by people with addictive personalities/substance abuse issues etc.

mettamage 8mo ago
It's addictive because of a hypothesis I have about addiction. I have no data to back it up other than knowing a lot of addicted people and I have studied neuroscience, yet I still think there's something to it. It's definitely not fully true though. Addiction occurs because as humans we bond with people but we also bond with things. It could be an activity, a subject, anything. We get addicted because we're bonded to it. Usually this happens because we're not in fertile grounds to bond with what we need to bond with (usually a good group of friends). When I look at addicted people a lot of them bond with people that have not so great values (big house, fast cars, designer clothing, etc.), adopt those values themselves and get addicted to drugs. This drugs is usually supplied by the people they bond with. However, they bond with those people in the first place because of being aimless and receiving little guidance in their upbringing. I'm just saying all that to make it more concrete with what I mean about "good people". Back to LLMs. A lot of us are bonding with it, even if we still perceive it as an AI. We're bonding with it because when it comes to certain emotional needs, they're not being fulfilled. Enter a computer that will listen endlessly to you and is intellectually smarter than most humans, albeit it makes very very dumb mistakes at times (like ordering +1000 drinks when you ask for a few). That's where we're at right now. I've noticed I'm bonded with it. Oh, and to some who feel this opinion is a bit strong, it is. But consider that we used to joke that "Google is your best friend" when it just came out and long thereafter. I think there's something to this take but it's not fully in the right direction I think.

sidrag22 8mo ago

As much as i loved the relation of vibe coding to slots and their related flow states in this article, I also think what you are stating is the exact reason these tools are not the same as slots, the skill gap is there and its massive. I think there are a ton of people just pulling the lever over and over, instead of stepping back and considering how they should pull the lever. When you step back and consider this, you are for sure going to end up falling deeper into the engineering, architecture realm. Ensuring that continually pulling the lever doesn't result in potential future headaches. I think a ton of people in this community are struggling with the lose of flow state, and attempting to still somehow enter it through prompting. The game in my view has just changed, its more about just generating the code, and being thoughtful about what comes next, its rapid usage of a junior to design your system, and if you overdue the rapidness the junior will give you headaches.

skydhash 8mo ago
> I think there are a ton of people just pulling the lever over and over, instead of stepping back and considering how they should pull the lever There are deeper considerations like why pull the lever, or is it the correct lever? So many api usages is either seeing someone using a forklift to go the gym (bypassing the point), using it to lift a cereal box (overpowered), or using it to do watchmaking (very much the wrong tool). Programming languages are languages, yes. But we only use them for two reasons. They can be mapped down to hardware ISA and they’re human shaped. The computer doesn’t care about the wrong formula as long as they can compute it. So it falls on us to ensure that the correct formula is being computed. And a lot of AI proponents is trying to get rid of that part.