Having banged my head on years/decade old inconsistencies between Chrome and Firefox with respect to webrtc APIs, some of these inconsistencies will never be ironed out.
But also, imo, Chrome is way more entrenched that LLM agents. I'm sure people will be happy with chromium being containerized this way.
I'm sorry but this article is marketing. From the 3rd paragraph from the end:
> Since our landing page is isolated from core product code, the risk was minimal.
The real question to ask is why your landing page so complex, it is a very standard landing page with sign-ups, pretty graphics, and links to the main bits of the website and not anything connected to a demo instance of your product or anything truly interactable.
Also, you claim this avoided you having to hire another engineer but you then reference human feedback catching the LLM garbage being generated in the repo. Sounds like the appropriate credit is shared between yourself, the LLM, and especially the developer who shepherded this behind the scenes.
OP here - I'm sorry this felt like marketing; that was not my intent! I deliberately posted on my personal blog and tried to focus this post on how I used agentic tools (Claude Code, the Figma Dev Mode MCP) and not anything about what my startup actually does.
That said, I was working on implementing a redesign for my startup's website as the project for the experiment - there's no way around that as context.
> The real question to ask is why your landing page so complex
I disagree on this; I don't think that was an issue. Our landing page would have been very easy for a developer on our team to build, that was never a question.
That said, we're a small startup team with myself, my cofounder / CTO, one engineer, and a design contractor. The two technical folks (my cofounder / CTO and the engineer) are focused on building our core product for the most part. I absolutely agree credit is due to them both for their work!
For this project, they helped me review a couple of my bigger PRs and also helped me navigate our CI/CD, testing, and build processes. I believe I mentioned their help in my blog post explicitly, but if it wasn't clear enough definitely let me know.
My goal in attempting this project was in no way to belittle the effort of actual developers or engineers on our team, whom I highly respect and admire. Instead, it was to share an experiment and my learnings as I tried to tackle our website redesign which otherwise would not have been prioritized.
I had not thought of visualing my mental debugging process as a decision _tree_ and that LLMs (and talking to other humans) are analogous to a foreign graft. Interesting, thanks!
The market clearing wage only applies in economic textbooks, in a perfectly competitive market with balanced supply and demand. The US public transportation sector has major supply/demand imbalances and is a regulated market.
It's not exactly apples to apples because the bls figure is nationwide and doesn't include healthcare benefits, and king county metro may have better than average healthcare, but at least ballparking this: No, public bus drivers are not paid "well above" the median wage
Edit: I found this listing on indeed for greyhound bus drivers (the closest comparison I could think of in the private sector) and starting rate is $28-$31 in Seattle (https://www.indeed.com/m/viewjob?jk=2516c81006044ec8).
i think main thrust, you are right that the numbers are less extreme than i had recalled. SF (which i imagine is the top end) is $31-$47 range or so. i see lower ($25) for greyhound than you do, but frankly that seems unreasonably low so i think “salary.com” is not giving me solid numbers there.
Indeed shows an active listing in SF for Greyhound for the same amount as Seattle. Greyhound appears to have a single national salary scrolling through different cities. https://www.indeed.com/m/viewjob?jk=ad2e68b167688669
Well your perfectionism needs to be pointed towards this line. If you get truly large numbers of users this will either slow down token checking directly or your process for removing ancient expired tokens (I'm assuming there is such a process...) much slower and more problematic.
It's just funny because there are definitely examples of bad code in that repo (as there are in any real project), but you picked something totally routine. And your critique is wrong fwiw—it would easily scale to millions of users. Perhaps you could find something better if you used AI to help you...
Yeah this definitely matches my experience and guess what? Google maps sucks for public transit and isn't actually that good for pedestrian directions (often pointing people to "technically" accessible paths like sketchy sidewalks on busy arterial roads signed for 35mph where people go 50mph). I stopped using Google maps instinctually and now only use it for public transit or drives outside of my city. Doing so has made me a more attentive driver, less lazy, less stressed when unexpected issues on the road occur, restored my navigation skills, and made me a little less of, frankly, an adult man child.
To be fair, if you read the incident report it is a better than average one on details and it was a 20 minute outage without data loss. I've seen many major companies simply not acknowledge that level of outage on their public status page, especially lately
If the corporate directive was to share "if AI has helped and how" I would agree. But my company started that way and when I tested the new sql query analysis tool and reported (nicely and politely with positive feedback too) that it was making up whole tables to join to (assuming we had a simple "users" table with email/id columns which we did not have due to being a large company with purposefully segmented databases. The users data was only ever presented via api calls, never direct dB access).
My report was entirely unacknowledged along with other reports that had negative findings. The team in charge published a self-report about the success rate and claimed over 90% perfect results.
About a year later, upper management changed to this style of hard requiring LLM usage. To the point of associating LLM api calls from your intellij instance with the git branch you were on and requiring 50% llm usage on a per-pr basis otherwise you would be pip-ed.
This is abusive behavior aimed at generating a positive response the c suite can give to the board.
I know you don't want to hear this, but I also know you know this is true: you would genuinely need to look at the full dataset that team collected to draw any meaningful conclusion here. Your single example means pretty much nothing in terms of whether the tool makes sense at large scale. Not a single tool or technology exists in this entire field that never fails or has issues. You could just as well argue that because you read something wrong on Google or Stack Overflow that those tools should be banned or discouraged, yet that is clearly false.
That said, I don't agree with or advocate the specific rollout methodology your company is using and agree that it feels more abusive and adversarial than helpful. That approach will certainly risk backfiring, even if they aren't wrong about the large-scale usefulness of the tools.
What you're experiencing is perhaps more poor change management than it is a fundamentally bad call about a toolset or technology. They are almost certainly right at scale more than they are wrong; what they're struggling with is how to rapidly re-skill their employee population when it contains many people resistant to change at this scale and pace.
> I know you don't want to hear this, but I also know you know this is true
I wasn't sanctimonious to you, don't be so to me please.
> you would genuinely need to
> look at the full dataset that
> team collected to draw any
> meaningful conclusion here
I compared notes with a couple friends on other teams and it was the same for each one. Yes it's anecdotes but when the same exact people that are producing/integrating the service are also grading its success AND combine this very argument while hiding any data that could be used against them, I know I am dealing with people who will not tell the truth about what the data actually says.
If you truly think the team responsible for this made a bad call, you need to go look at all the data they collected. Otherwise, yes, you're just sharing a couple anecdotes, and that is problematic and can't be brushed off or ignored. While it's possible that the people integrating the service just ignored negative feedback and are apparently pathological liars (as you accuse them of being), it's also possible that it's actually you who is ignoring most of the data and being disingenuous or manipulative about it. You are demonstrating a lot of paranoid, antagonistic thinking about a team that might just have a broader good-faith perspective than you do.
I get what you are saying, and a situation like this needs to be treated with extreme tact and care. But no, it's not his story, it's a low res approximation of his story as viewed through the lens of the stastical average reddit comment or self published book.
If the father is really into the tech side of it (as opposed to pure laziness), I'd ask him for the prompts alongside the generated text and just ignore the output. The prompts are the writing that is meant for the original commentor, and it is well worth it to take the tact of not judging those by their writing quality independently.
Very funny read from the MBA set when the same collapse is happening in software itself. He's saying MBAs are going to have to shift to data analysis and product design roles, as if those aren't being eaten by the very same processes.
But I don't say this to belittle the author, I just mean funny in how people are all grasping around the same elephant (https://en.m.wikipedia.org/wiki/Blind_men_and_an_elephant). I don't claim to have special insight here, just noticing that this is happening across many diverse professions. My personal theory is that we reached the point of diminishing returns of what can be built and effectuated via software or people management and at some point an economy can't bear the dead weight of people pulling down six figure salaries by moving some javascript or PowerPoint slides around, while the base of the economy (industry, farming, energy production, transportation) dies from lack of investment.
See the general subject of "elite overproduction".
It's not clear at all where "AI" is going. Once AIs get reliable enough to be put in charge of things, rather than being merely advisory, we will have a very different society. Everybody here has probably read the late Marshall Brain's "Manna", which outlines how that might play out.
(I'm reading Pikkety's new "Capital and Ideology". Not far enough in to comment yet.)
> at some point an economy can't bear the dead weight of people pulling down six figure salaries by moving some javascript or PowerPoint slides around, while the base of the economy (industry, farming, energy production, transportation) dies from lack of investment.
What if the base of the economy is well-paid power point rangers buying stuff? Because that’s what most of our economy is: consumer spending.
It’s some sort of myth that the American farmer is the core of our economy or something.
> What if the base of the economy is well-paid power point rangers buying stuff? Because that’s what most of our economy is: consumer spending.
Those "well-paid power point rangers" can't be the base of the economy: properly understood, they're an exploitative/parasite class sitting more towards the top of the pyramid.
> My personal theory is that we reached the point of diminishing returns of what can be built and effectuated via software or people management
I dont think so. There are amazing things that can be done with either, but they require a completely different way of structuring companies, removing the profit motive, or getting rid of a whole lot of "conventional wisdom" and old people.
There are a lot of amazing things that can be done via the management side of things, but have all but been sidelined since the rise of neoliberalism in the 80s and the MBA-ification of management in the 90s and 00s. Doesnt help that these approaches would require that managers are actually competent and learn to work with complexity, data and the like.
But also, imo, Chrome is way more entrenched that LLM agents. I'm sure people will be happy with chromium being containerized this way.