The same thing happened when figma made it easier make prototypes that looked real and people stopped doing low fidelity mockups.

Everyone understands that a wireframe isn’t done yet and it’s easy to change at that phase.

Before if you had a crap idea you atleast had to face the social back-pressure of explaining it to someone at a local hackers meetup and trying to convince them to build it for you..

> Good old user research or talking to users to validate ideas, iron out issues in the user flows has become too slow for the new process

I haven't seen these in at least a decade in the industry!! Everywhere I used to work was always "PM wanted" or similar and the validation was always just QA making sure the thing works/does the bare minimum!!! Customer input was just for bugs.

I hope that with AI speeding up prototyping we can actually go the other way long term, where we go back to ACTUALLY talking to a customer and then quickly prototyping it to see if it is what they wanted. Figuring out what the customer wants remains the hardest part of software engineering, but at least right now its mainly because we just dont talk to the customer.

Prototypes aren't only for UX though, sometimes they're for exploring whether something is technically possible, or what are the unknown unknowns in a particular area.

For example, for personal projects, I've been wondering if it's possible to automatically create RSS feeds for pages that don't have them (yes), what are the challenges when building an archive-style page dumping system (need to dump CSSOM alongside getOuterHTML, remove/rewrite remote content, walk iframes, automate Chrome, scroll to load lazily loaded content, etc.), and if training a model to remove native ads from markdown coming from readability is possible (no, at least not with my current approach, but using the dom might work).

Can you help me understand what the "cost" of other people producing garbage is? Prototypes are generally shop jigs. You'd feel weird gold-plating a stop block.

Making software for users? Who even does that any more?

I'm in an industry where I can really see this, executed by honestly talented people able to interpret what the LLMs produce. It's bikeshedding hell. If you pursue every possible idea and get to implement all of them and it actually works, in the best possible scenario with no technical debt because you're able to stay on top of it (presumably in the window you have before you just burn out), you end up with all the ideas at once.

The project has tracked your imaginative state, and perhaps the states of your beta testers as they imagine things. It's a power armor suit tailored to specifically you. Nobody else will ever fit it because it's evolving too fast, all to implement your every whim.

I've seen this take 1.0 projects that are intentionally wildly scope-limited and great at that, and balloon until the project is the Everything Machine, doing everything but send email. I guess in the new era, every project expands until it becomes alive and devotes itself to your service… or at least, does its level best to be that for you and your beta team.

These things are not approachable. They're fever dreams, unparsable by outsiders. Discipline is lacking.

Time saves on stupid shit management thinks works!

Similar experience here, however my feeling is that this isn't necessarily a bad thing. Garbage being made is indicative of a gap in the currently-available tools. User research should shift towards analyzing these prototypes and enhancing existing tools to fill this need.

Now it's possible to toss many more. :)

Most places I've worked, devs were basically afraid to prototype

Either you would get chastised for wasting time with prototypes, or worse, your prototype would end up in production

I think the software industry really needs a cultural reset to embrace slower and deliberate development to build quality, but unfortunately AI has us racing recklessly in the wrong direction

I am so tired of it. Are there any companies out there that actually give devs time to build quality software anymore? I'm so burned out of the "move fast and break everything" grind

I think this is nonsense.

Prototyping already existed - how do you think the iPhone came into existence?

I've started making most of my prototypes single HTML documents with inline CSS and JavaScript, because a single file is a lot easier to store somewhere and share and will probably keep on working forever (browsers are really good at backwards compatibility).

I chuck some of them on my public tools.simonwillison.net collection, others in their own GitHub repos with GitHub Pages enabled, and some I just share in a Gist (served via gisthost.github.io) or stick in a public S3 bucket so I have a URL for them.

If a prototype is against an existing project sometimes I'll leave it to silently rot in a branch on GitHub.

You know how when you finish prompting some code generator to build something, and you look over what it has built and feel a sense of emptiness even if it does what you want? I think about what I wish the prototype looked like, and basically start describing details that I expect to exist (think longer versions of e.g. “this should be using our internal graph library, and I figure we can model this task as a traversal, how far have you strayed from this and why?”) and let the agent analyze what it built against my expectations. I’ve spent hours in conversation just “refining the context” this way, and then I channel that into an update process. I figure the prototype is just about proving out behavior, and this next phase is about refining it into the pieces I’ll use elsewhere. It’s kinda fun, I’d absolutely burn out a coworker if I grilled their PRs the way I roast AI contributions :P

I use AI mostly to prototype features in my existing projects. If I have an idea, I use the AI to implement it and try out different ways in which it could be implemented. Then I throw away the code and mostly write the code manually, with AI used primarily for review or docs.

I used Claude extensively during an internal hackweek at my company to prototype a new data analysis application. Probably would have never attempted the project without AI. Now it’s in production with more than 20k weekly users. Almost never use Claude to dev on it now, but it definitely helped me get off the ground.

> What are people doing with prototypes afterward?

I think what people ARENT doing is interesting.

Usability isn't even in your list, it is not something most people even think of.

The best thing you can do with a prototype is give it to (potential) users and observe what they do with it. Just because you think that you're clearly communicating the intent of your system does not mean you are.

Most managers rename the prototype into the product anyway.

It reminds me of Drupal circa 2009.

I was thinking the other day how much better Drupal is. Want a online store? A few commands and bam, online store. Want a newspaper? A few commands and bam, newspaper with publishing workflows, user management, and caching.

Using coding agents isn't much different. There are several things the models are trained to do very well and a few commands will get something. If the developer wants to move the project beyond that, it requires domain knowledge and a lot of hacking.

I wonder if the coding agents will move towards the Drupal model where they create interchangeable components with common interfaces. Like Drupal the coding agents never provide anything truly inovative that hasn't been done before.

> But is it really any faster than using an already existing code generator/scaffolding tool?

Yes, very much so. Our team was fast with those tools and created many of our own before this LLM AI (we used other AIs though to go faster), however it still took weeks to months from idea to launch; the same complexity now takes days, including everything. We already had rigorous processes and those really help now moving at speed. No way anyone can beat this except better AI.

Yea cause it's done while you're still reading the docs for your code generator. lol

Your tone makes me think you already decided that agents aren't worth your time, but I'll give it a try anyways.

I work as a DevOps engineer and have been using agents exclusively to code since the beginning of the year. Agents are really nice to quickly craft utilities to speed up planning. For instance I had it create a small cli for me that'll pull my cards from azure DevOps, load them as json, markdown and csv, and push updates once I'm done. Then I'll load into context transcripts of meetings and other written requirements, cross with current state of repos, to have meaningfully conrextualized work items without me having to implement these myself. I'll just have a long chat with the agent exploring these cards and defining the necessary refinements for description and acceptance criteria than I jusr push them all at once. Anything you can think of you just ask for the agent, so for me I don't trust code, so I'll have all my clis be no-op by default, so they will first print all they'll do and if I think the changes make sense I approve them and let the script commit to the canonical board.

Working with cloud consoles like Aws in general is a huge hassle, so crafting quick inventory utilities and tools for correlating data is a breeze.

Now the work itself is mainly ci pipelines, terraform files and automation. For these I'll base the agents on the specified work items and enrich them with my own understanding of the problem. I then launch the agents and read the agent output attentively. This is very important. You can't just prompt and leave, you need to be present all the time so you can steer the agent into solving the right problems. At the very least you need to review all the changes after an implementation session is done when you came back from making coffee. Many times it tries to create meaningless abstractions or very complicated solutions that I know can be done better. Or I have a different idea of how to organize the project so I do many follow-up sessions to refactor code.

In my personal projects I do a lot of small utilities. I spent some weeks designing and polishing a replacement for zurg and debridmediamanager the way I like it to be, simple and to the point, also tightly integrating them with jellyfin https://gitlab.com/gabriel.chamon/buzz

I have my own micro desktop environment on top of hyprland called Archie which recently I've been redesigning and improving a lot with agents https://gitlab.com/gabriel.chamon/archie

I have my own agile based methodology for creating and managing work items with tight integration with gitlab https://gitlab.com/gabriel.chamon/orisun

I have been improving my fork if gamma-launcher so that installing and managing the game on bazzite is simpler and more automated than relying on workarounds for workflows intended for windows https://gitlab.com/gabriel.chamon/gamma-launcher

Now for how I approach developing with agents. I think it's really important to get your constraints sorted out as soon as possible, so have your agent create a CI pipeline for code quality testing, like with ruff, pyright and pytest, to control style, code consistency and cyclomatic complexity. Put in the AGENTS.md explicit instructions that the agent must run these tools at the end of every coding session. If adopting a new project, use the agent to explore the code and see which refactoring points are worth tackling. Agents really thrive on good codebases, so this first code quality improvement pass is a must.

To sum it up, with agents you give up writing code manually for reading lots of code, exploring the domain with the help of the agent and architecting the solution at a strategic level. You trust the agent but you also verify. And lots and lots of manual testing. My personal take is that I'm infinitely productive now, only constrained by how much code and agent terminal output I can read, and also by the rate limits of the model providers and mental fatigue.

I think you're right

Imagine if instead of f AI generated code, we all just started copying and pasting code from open source repos.

Imagine my velocity! I cloned the Linux kernel in seconds!

Instead we're basically doing exactly that, except through an AI remixer.

It leaves a very sour taste in my mouth

You can argue that's the point of prototyping. Iterate fast. Getting a "junk" prototype in 2 days is better than getting the same in 2 months.

Now the quality of what comes after the iteration depends on the reviewer, and that's no AI's fault.

Well the worst thing is it allows you to make a really convincing pile of junk and get people to pay for it. Then you can worry about the details when you have your first paying customers.

That's where everyone is overconfident. And that's where mature companies like ours are starting to get customers come back again after jumping ship for some vibe coded startup and getting screwed.

LLMs, minimum advantages aside, are merely amplifiers for the worst characteristics of the human race.