functional programming taught us this decades ago. State is the root of all evil.
If the outcome of my interaction with the interface (e.g. tap a place on the screen) is a function of not just where i tap but the last 2-6 places i recently tapped (menus etc) suddenly you've added massive complexity and mental overhead.
can't wait to get back to a button that does the same thing every time every time i press it [1]
tesla screens, carplay, mercedes screens, its been getting worse for a while
1) I know in reality most are sliders or an on/off toggle but the point stands
I think one of the main examples that i saw in a swyx article a while back is that using the sort of ALL CAPS and *IMPORTANT* language that works decently with claude will actually detune the codex models and make them perform worse. I will see if I can find the post
it is very hard for me to take seriously any system that is not proven for shipping production code in complex codebases that have been around for a while.
I've been down the "don't read the code" path and I can say it leads nowhere good.
I am perhaps talking my own book here, but I'd like to see more tools that brag about "shipped N real features to production" or "solved Y problem in large-10-year-old-codebase"
I'm not saying that coding agents can't do these things and such tools don't exist, I'm just afraid that counting 100k+ LOC that the author didn't read kind of fuels the "this is all hype-slop" argument rather than helping people discover the ways that coding agents can solve real and valuable problems.
there is the theoretical "how the world should be" and there is the practical "what's working today" - decry the latter and wait around for the former at your peril
I don’t think anyone serious would recommend it for serious production systems. I respect the Ralph technique as a fascinating learning exercise in understanding llm context windows and how to squeeze more performance (read: quality) from today’s models
Even if in the absolute the ceiling remains low, it’s interesting the degree to which good context engineering raises it
I read it. i agree this is out of touch. Not because the things its saying are wrong, but because the things its saying have been true for almost a year now. They are not "getting worse" they "have been bad". I am staggered to find this article qualifies as "news".
If you're going to write about something that's been true and discussed widely online for a year+, at least have the awareness/integrity to not brand it as "this new thing is happening".
engineers always want to re write from scratch and it never works.
a tale as old as time - my second job out of college back in like 2016, I landed at the tail end of a 3-month feature-freeze refactor project. was pitched to the CEO as 1-month, sprawled out to 3 months, still wasn't finished. Non-technical teams were pissed, technical teams were exhausted, all hope was lost. Ended up cutting a bunch of scope and slopping out a bunch of bugs anyway.
i had the privilege of working w/ some incredible eng leaders at my previous gig - they were very good at working both upwards and downwards to execute against the "50/50" rule - half of any given sprint's work is focused on new features, and half is focused on bug fixes, chores, things that improve team velocity.
I think the key here is “if X then Y syntax” - this seems to be quite effective at piercing through the “probably ignore this” system message by highlighting WHEN a given instruction is “highly relevant”
agree - i've had claude one-shot this for me at least 10 times at this point cause i'm too lazy to lug whatever code around. literally made a new one this morning
For the record I do think the AI community tries to unnecessarily reinvent the wheel on crap all the time.
sure, readme.md is a great place to put content. But there's things I'd put in a readme that I'd never put in a claude.md if we want to squeeze the most out of these models.
Further, claude/agents.md have special quality-of-life mechanics with the coding agent harnesses like e.g. `injecting this file into the context window whenever an agent touches this directory, no matter whether the model wants to read it or not`
> What people often forget about LLMs is that they are largely trained on public information which means that nothing new needs to be invented.
I don't think this is relevant at all - when you're working with coding agents, the more you can finesse and manage every token that goes into your model and how its presented, the better results you can get. And the public data that goes into the models is near useless if you're working in a complex codebase, compared to the results you can get if you invest time into how context is collected and presented to your agent.
> If I tell them exactly how to build something the work needed to review the resulting changes is a whole lot less taxing.
Totally matches my experience- the act of planning the work, defining what you want and what you don’t, ordering the steps and declaring the verification workflows—-whether I write it or another engineer writes it, it makes the review step so much easier from a cognitive load perspective.
I have had a user story and a research plan and only realized deep in the implementation that a fundamental detail about how the code works was missing (specifically, that types and sdks are generated from OpenAPI spec) - this missing meant the plan was wrong (didn’t read carefully enough) and the implementation was a mess
If the outcome of my interaction with the interface (e.g. tap a place on the screen) is a function of not just where i tap but the last 2-6 places i recently tapped (menus etc) suddenly you've added massive complexity and mental overhead.
can't wait to get back to a button that does the same thing every time every time i press it [1]
tesla screens, carplay, mercedes screens, its been getting worse for a while
1) I know in reality most are sliders or an on/off toggle but the point stands