It has vibe code and dogs in the title
587 karma · joined April 19, 2018
> ...
> Writing good code remains significantly more expensive
I think this is a bad argument. Code was expensive because you were trying to write the expensive good code in the first place.
When you drop your standards, then writing generated code is quick, easy and cheap. Unless you're willing to change your standard, getting it back to "good code" is still an equivalent effort.
There are alternative ways to define the argument for agentic coding, this is just a really really bad argument to kick it off.
Are we saying that llm's have zero economic growth, or are we saying that the sum of winners and losers in llm usage are zero or less than zero?
I think there's many examples of llms resulting in winners, or maybe this signal is just very high in the tech space.
But maybe there's not enough reporting on the losers in llms at the moment? (E.g. did llm displace their jobs, they have llm use cases that failed, etc, etc)
* User uses Google oauth to integrate their open claw
* user gets banned from using Google AI services with no warning
* user still gets charged
If you go backwards, getting charged for services you can't access is rough. I feel sorry for those who are deeply integrated into Google services or getting banned on their main accounts. It's not a great situation.
Also, getting banned without warning is rough as well. I wonder if the situation will be different for business accounts as opposed what seems like personal accounts?
The ban itself seems fair though, google is allowed to restrict usage of their services. Even though it's probably not developer friendly, it's within their rights to do so.
I guess there's some level of post mortem to do on the openclaw side too.
* Why did openclaw allow Google anti gravity logins?
* The plugin is literally called "google-antigravity-auth", why didn't that give the signal to the maintainers?
* Why don't the maintainers, for an integration project, do due diligence checks on the terms of service of everything you're integrating with?
* I ask the LLM for it's understanding of a topic or an existing feature in code. It's not really planning, it's more like understanding the model first
* Then based on its understanding, I can decide how great or small to scope something for the LLM
* An LLM showing good understand can deal with a big task fairly well.
* An LLM showing bad understanding still needs to be prompted to get it right
* What helps a lot is reference implementations. Either I have existing code that serves as the reference or I ask for a reference and I review.
A few folks do it at my work do it OPs way, but my arguments for not doing it this way
* Nobody is measuring the amount of slop within the plan. We only judge the implementation at the end
* it's still non deterministic - folks will have different experiences using OPs methods. If claude updates its model, it outdates OPs suggestions by either making it better or worse. We don't evaluate when things get better, we only focus on things not gone well.
* it's very token heavy - LLM providers insist that you use many tokens to get the task done. It's in their best interest to get you to do this. For me, LLMs should be powerful enough to understand context with minimal tokens because of the investment into model training.
Both ways gets the task done and it just comes down to my preference for now.
For me, I treat the LLM as model training + post processing + input tokens = output tokens. I don't think this is the best way to do non deterministic based software development. For me, we're still trying to shoehorn "old" deterministic programming into a non deterministic LLM.
* I think my biggest frustration is that I don't know how security standards just gets blatantly ignored for the sake of ai progress. It feels really weird that folks with huge influence and reputation in software engineering just promotes this * The confusion comes in because for some reason we decide to drop our standards at a whim. Lines of code as the measurement of quality, ignoring security standards when adopting something. We get taught to not fall for shiny object syndrome, but here we are showing the same behaviour for anything AI related. Maybe I struggle with separating hobbyist coding from professional coding, but this whole situation just confuses me
I think I expected better from influential folks promoting AI tools to at least check validate the safety of using them. "Vibe coding" was safe, claws are not yet safe at all.
Here's the next line and the line after that. Again, LOC is really not a good measurement of software quality and it's even more problematic if it's a measurement of one's ability to understand a codebase.
After all these years, why do we keep coming back to lines of code being an indicator for anything sigh.
I deleted all my social media profiles, but then at my current job I needed to add them back because my work used these and you need accounts to get access to developer accounts.
Anyway, my Facebook feed starts showing me Japanese and Korean nsfw videos. Instagram reels starts showing me increasing racist dark humour reels. I actually have to manage this feed to avoid these types of posts from popping up.
Then there's bots, there's so many bots that you don't even know who's real anymore. Like threads will have a bunch of new accounts posting for the first time. For me, this happens a lot on reddit
Then there's the ai content. There's so much slop in the posts as well as the comments. Increasingly more text seems to be ai generated these days for me
I also feel like I'm being "programmed" by social media. Like using claude is a good example, many folks seems to have started using claude fully in November. Another example is reddit, many times what is upvoted seems "programmed" to appear on the main feed.
In terms of mental wellbeing, I also see my mental wellness being affected. If I look at specific things related to relationships or financially successful people, then I'll eventually go through waves of depression symptoms just because I'm not good enough to be that person.
I initially joined social media looking to improve my quality of life. But these days, these sites feel like they just want my attention instead of wanting to make people's lives better.
Maybe that's naive of me to think this way, but at one point these sites did feel "good for me". It's just that I didn't catch on to the algorithm changes and their effects on my well being until it was too late.
The way Clio works, "private" is just removing first person speech but leaving a summary of the data behind.
Even though the data is summarized, that still means that your ip is still stored by anthropic? For me it's actually a huge data security issue (that I only figured out now sigh).
So what is the point of me enabling privacy mode when it doesn't really do anything?
Personally, I'm more interested in whether software development has become more or less pay to win with LLMs?
* If I don't know how to do something, llms can get me started really fast. Basically it distills the time taken to research something to a small amount.
* if I know something well, I find myself trying to guide the llm to make the best decisions. I haven't reached the state of completely letting go and trusting the llm yet, because the llm doesn't make good long term decisions
* when working alone, I see the biggest productivity boost in ai and where I can get things done.
* when working in a team, llms are not useful at all and can sometimes be a bottleneck. Not everyone uses llms the same, sharing context as a team is way harder than it should be. People don't want to collaborate. People can't communicate properly.
* so for me, solo engineers or really small teams benefit the most from llms. Larger teams and organizations will struggle because there's simply too much human overheads to overcome. This is currently matching what I'm seeing in posts these days
We have someone who vibe coded software with major security vulnerabilities. This is reported by many folks
We also have someone who vibecoded without reading any of the code. This is self admitted by this person.
We don't know how much of the github stars are bought. We don't know how many twitter followings/tweets are bought.
Then after a bunch of podcasts and interviews, this person gets hired by a big tech company. Would you hire someone who never read any if the code that they've developed? Well, this is what happened here.
In this timeline, I'm not sure I find anything inspiring here. It's telling me that I should rather focus on getting viral/lucky to get a shot at "success". Maybe I should network better to get "successful". I shouldn't be focusing on writing good code or good enough agents. I shouldn't write secure software, instead I should write softwares that can go viral instead. Are companies hiring for vitality or merit these days? What is even happening here?
So am I jealous, yes because this timeline makes no sense as a software engineer. But am I happy for the guy, yeah I also want to make lots of money someday.
But nothing will happen so yeah.
Sorry but this is the whole point of software engineering in a company. The aim is to deliver value to customers at a consistent pace.
If a team cannot manage their own burnout or expectations with their stakeholders then this is a weak team.
It has nothing to do with using ai to make you go faster. Ai does not cause this at all.
I find these types of responses highly offensive and inauthentic. I just wasted my time trying to understand another human being.
This is not okay.
Do you have examples of this? I'm aware of raises, but not aware of any profitable ai companies yet
> When I made my 2029 prediction this is more-or-less the quality of result I had in mind.
There seems to be a lot of compensation and leniency made by the author here.
So, it is seemingly impressive that someone was able to use agents to build a browser.
But they used trillions of tokens? This equates to millions of dollars of spend. Are we really happy with this?
The browser itself is not fully complete. There's rendering glitches stated in the article. So millions of dollars for something that has obvious bugs.
This is also pure agent code. Can a code base like this ever be maintained by a team of humans? Are you vendor locked into a specific model if you want to build more features? How will support work? How will releases work? The lack of reflection over the rest of the software lifecycle except building is shocking.
So I'm not sure after reflecting, whether any of this is impressive outside of "someone with unlimited tokens built a browser using ai agents". It's the same class of problem being solved over and over again. Nothing new is really being done here.
Maybe it's just me but there's much more to software than just building.
So I can see this happening in a practical sense.
also really surprised that tech companies have more debt than cash on hand. would be really interesting to know how apple fares in this comparison too.
So this is impressive for me in terms of how fast things have progressed.
Anthropic will move onto bigger projects and other teams/companies will be stuck with sunk cost fallacy to try and get mcp to work for them.
Good luck to everyone.
It will probably take a while, but is the general public going to be priced out of computers eventually?
But if people don't care, then cool.
* "He's a great engineer" - Yet he's ineffective at doing the job and touch fired him? * "He's top 0.1%" - Of what exactly? How can it be the case when you fired him?
You literally didn't do reference checks properly and you got caught out. And it's all written like these companies are the victims. You're better off admitting that you don't know how to hire.
Soham's behaviour is one thing, but working for any of these companies he was at is a literal red flag.
* It's not clear on how much revenue or new customers is generated by using a coding agent
* It's not clear on how things are going on production. There's only talks about development in the article
I feel ai coding agents will give you the edge. Just this article doesn't talk about revenue or PnL side of things, just perceived costs saved from not employing an engineer.