Comment by K0balt
12 hours ago
Lol. I’m totally with you on agentic UX development. It’s frequently terrible, and you can tell which companies are telling everyone to 10x with AI. But the problem is testing, not the coding. My first stab at a UX render usually sucks too, it’s the iteration that brings perfection. It’s the same for agentic development.
What I meant though wasn’t agents building UX. I meant that in our case at least, the agent is the UX. “put a new extension 117 for Sam at the port next to Jane’s, and have it ring through to his cell when he’s not in the office. Leave the old 117 as is but only ring where Sam is, if that is known” basically, agents just do everything with SSH, and you can talk to them instead of poking around with a mouse. We don’t build ux for internal systems anymore. Local inference is strong enough to be reliable now with the correct tools and policies, and for 10-20k in hardware you are self contained. (Obviously $more if you are going to have a lot of people using it at the same time)
The “one wierd trick” is to build testing jugs for everything. Before a configuration is deployed, it’s tested against a toy instance, all existing functions are tested in all common cases, new functions verified, inputs fuzzed, adversarily abused, and stress tested against dummy loads. If its code, it gets examined against development policy, self containment, explicit interface walls, race conditions, code standards, complexity, factorability, and often A/B testing of different architectural choices. Except cryptography and a couple of other things, we generally prohibit the use of any libraries, it’s just not needed and the code never passes our tests anyway.
People are just YOLOing it and assuming that if it basically functions and looks right then it must be perfect. You’d have the same luck if you told your UX guy “test only the obvious, and if it looks about right at first glance, merge it. Don’t do extensive testing.”
The real thing with AI is that now you can afford to do a ridiculous amount of automated testing, setting up test fixtures, hardware simulators, mannequins of all the external interfaces, fuzzing, etc. Our testing code is 2-3x our product code, and we are shipping 10% of the bugs we shipped with humans, and it’s still 1/4 the cost and 4-10x the speed.
People shipping all the crap that is everywhere now have bad process engineering. Plain and simple. If you try to build software with AI like you used to with people, you’re going to have a bad time. The pipeline is very different.
> My first stab at a UX render usually sucks too, it’s the iteration that brings perfection
With AI, your iteration cycle gets 10x/100x quicker. For the same developer effort, you can effectively try out 10s of ideas the same period of time.
Iteration also has a human component. When a person works hard and writes the code, they are personally invested in its success. So iteration, or, chucking out someone’s hard work is psychologically damaging and causes human conflicts in teams. If AI wrote it, and AI deleted it, no-one gets upset. All that matters are good ideas. Reducing the human cost of iteration is just as important as the time saving.
And, now you have freed up implementation time, you now have way more time for testing, that thing that everyone wished they had more time to do, with a super intelligent 100x developer (ai) as your coding partner, and a 100x lever for automating regression testing. Bad UX has zero excuses.
>With AI, your iteration cycle gets 10x/100x quicker. For the same developer effort, you can effectively try out 10s of ideas the same period of time.
This, except not (just) for UX, but for everything else too. Tonnes of ideas and side project people had on hold for lack of time and/or knowledge, have now been built and trialed thanks to AI.
You see this in the recent boom of reverse engineered multi platform releases of vintage video games that were once tied to a specific console.
Or people reverse engineering their crappy IoT home smart devices to build better multi platform UIs controllers for them.
Which is why I'm really struggling to understand how tech people can still now say with a straight face "AI isn't useful for me". Maybe they just lack imagination?
kudos. Precisely this. People are doing agentic design backwards very often: YOLO then cry. But, if first you write skills, specs, set up orchestration, architecture and flows, including review layer, discrimination layer and trajectory management layer, then you task the agents with creation of verifiable testing and static analysis rig, based on the golden samples of high-quality manually engineered code, and only then you tell then to write conformant code.
Agents (and LLMs) are inherently non-deterministic. In coding practice, this translates to garbage code in the long run. The solution is simple - make the process as deterministic, verifiable and rigid as possible. Suddenly, you get all the bonuses of agentic flows (insane initial speed, trivial cost, express iterations etc.) with none of the usual problems... and suddenly, humans have hard time matching the quality of the final artifact with hand-written code, because we suck at testing, fuzzing and debugging - because we're basically single-threaded and overfocused. Agents, OTOH, excel at it, and context management is also trivial compared to humans.
This feels like a detached backpedaling pivot to save face tbh.
But anyway.
I'm sure there are people that use the tech wrong. That can be said about any tech in existence.
Most people, actually. Remember, friend - ~half of the population has two digits in their IQ, by definition.
If we aren't in that half, it's by sheer luck, and nothing else.