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jwpapi

874 karma · joined May 31, 2022

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jwpapi··on Claude Fable 5
I don’t even think that Boris is really just one person. He apparently vibe coded Claude Code and is responding on Threads, Twitter, HN and everywhere.
jwpapi··on I design with Claude more than Figma now
I’m looking for an alternative too..
jwpapi··on Do the Hardest Thing
I think author even mentions it on the side: the hardest thing thats also valuable
jwpapi··on Mouseless – keyboard-driven control of macOS/Linux/Windows
Does anyone use a trackpoint and has still compared to this? I get it’s faster then reaching to mouse, but faster then trackpoint?
jwpapi··on Uber's $1,500/Month AI Limit Is a Useful Signal for AI Tool Pricing
If you estimate 10k salary per engineer that means the moment it’s cheaper for them to hire another engineer but that doesn’t mean it’s improving productivity 15% but if 15% is the moment it stopped being better than another human we can assume 7.5%?

Probably even less because you would spend those 1500 extra per employee also if you just save 10% so 150 per employee that’s 1.5% on salary.

This is imho one of the best ranges we can assume for now how much would that be on the whole swe market?

jwpapi··on Expanding Project Glasswing
Ragebait god
jwpapi··on Can the stockmarket swallow Anthropic, SpaceX and OpenAI?
Because it doesn’t work without me
jwpapi··on Backpressure is all you need
Such a fantasy, it leads to two problems.

Increased complexity of your systems. Increased pipelines of your system.

You might reduce the likelihood of errors, but at an overproportinal cost of time it takes to complete (which some might argue is irrelevant, but has the cost of human context), and with an way higher time and focus needed for all bugs that the system doesnt work.

You’ll have to fix adapt and maintain all your verification layers, because just because you set them up they are not perfect.

Your testing pipeline becomes incredible slow and you need to maintain it as well.

It’s tremendously weaker than a hands-on approach.

I’ve written this exact same article in January and since then completely switched my position.

Good luck on everyone trying this. You shuffling your own grave and waste time.

jwpapi··on I think Anthropic and OpenAI have found product-market fit
It was challenging for me as well, but my pace and level is now that I use it for these cases at the moment:

New language, infrastructure, general level of understanding of something I barely have an idea of.

Rubber duck debugging, if i dont know the correct solution

Checking my code for issues and bugs.

But not for:

- writing my code - agentic coding (help me)

The inference has reduced drastically. It’s basically just chatting. I don’t let it write anything, but sometimes I purposely use the browser window instead of them sitting in my codebase, because I know it gets things subtly wrong and migth focus on the wrong things.

The same way people used to say don’t copypaste code at least write it out I think it’s still true. It helps to buidl the mental model and to find the right abstractions.

jwpapi··on I think Anthropic and OpenAI have found product-market fit
I see you trying really hard to make things right and are everywhere in the comment. I feel a bit bad in formulating my comments a bit polemical.

Also my highest respect for responding so calmly without lowering your debating level to mine. I try to best to explain what I think is wrong.

To start I didn’t interpret the article as a burn.

I think it’s interesting to explain what’s wrong with it, because it seems similar to what‘s wrong with AI. The issues are subtle.

- Anthropic doesn’t have a profitable quarter, it’s financial engineering (https://www.wheresyoured.at/anthropics-profitability-swindle...)

- The first argument about your subscription price, doesn’t has anything to do with the overall claim of the article. It would if at all be a weak argument to support the opposite. Subsidizing prices signals a lack of PMF.

- That you hire sales people after you had a billions of funding is nothing surprising and doesn’t indicate PMF or not.

- AI Implementations are fresh and of course AI Failures are thin, but so are AI successes. I haven’t seen any companies creating billions of shareholder value because they’ve massively invested in AI and their competitiors didn’t You really can look at these things in 5 to 10 years and it is multi-faceted including cultural acceptance.

- That they need to buy more compute to satisfy the requests is probably the strongest argument in the artical, but don’t conclusive. The product is been sold heavily subsidized and in hype cycle. And again both OPENAI and Anthropic have to show growth in order to justify the IPO.

- Regarding the part about revenue I refer to the linkedm article above, as it does explain it very well.

The conclusion is reasonable given the arguments, but not the title.

However it is missing all the real discussion points that are actually in observation at the moment.

Local models as alternatives, IPO finanical engineering, how AI implementation actually will perform over years... Let’s all not forget crypto. It’s been full of "use cases" just a bunch of years ago. I like the idea of crypto(btc,eth) and I’m still invested, but 99.99% of coins have died on promies.

So this is not a piece of critical thinking, but this reads like a twitter thread to sell me a course :/

jwpapi··on I think Anthropic and OpenAI have found product-market fit
Now what percentage of the 200$ have been used on the useful stuff and how much on exploration or other stuff.

How long would it taken you to do it yourself? How much longer will the next task take you, compared to when you would’ve written the code yourself. How is the mental model compared to when you would’ve written it yourself?.

I’m not saying you’re wrong, again there are use cases. But the calculation is not plain and simple it goes deep into our perception, perceived productivity versus actual productivity.

I’ve 2 months maxxed out all 6k of Claude Code and bought Antigravity on top. My codebase became 140k lines. I introduced tons of bugs and spent another 2 months, deleting 80k of code. I wish I would’ve just chatted with AI and not let agents touch my codebase. I would’ve saved approx 300$ subscription prices a month and 2 months of my life.

jwpapi··on I think Anthropic and OpenAI have found product-market fit
Unfortunately Simon drank from the AI Cool Aid.

I know everything you’ve done for the tech community, but I please you to take some time off and reflect on this article. It’s not on par with ur usual level, but the tendency has been visible from the last couple of articles.

jwpapi··on I think Anthropic and OpenAI have found product-market fit
You kind of got it right, but the biggest loser of them all are the investors especially the index investors. They don’t even decide what they invest in but the savings that goes in funds need to invest in these stocks.

It’s quite an elaborate swindle obviously. But you generate hype with underselling your core product, you claim way more usability then there is. Users will experience usability initially. Everything multiplies with each other and then you put it on the market. Everybody involved makes money and you’ve succesfully extracted money from everyone who’s invested in NASDAQ index funds at the very least.

> Dario and Sam are saying “if you buy our coding agent subscription you can build a game with zero skill and one shot and then be rich”?

That’s Anthropics marketing, yes.

Also their offering is not uniqe that justifies a 1 trillion valuation. The first companies are already rowing back. It’s a really certain time window that they are about to hit now with their IPOs

The companies that have signed these enterprise deals haven’t done a ROI analysis. They had Fomo.

jwpapi··on I think Anthropic and OpenAI have found product-market fit
I have to give them kudos. This whole thing is the greatest swindle of all time.

AI has some use cases, but not at the price it’s currently priced at. I’ve been on AI since GPT-2 with a lot of heavy users. Every user has the same story, curiosity, surprise, hype, hate, realization. Enterprise is usually a bit behind and are right now at hype cycle, that’s where they sold all the deals and do the IPO.

It’s really a VC masterclass.

Don’t get me wrong there is are useful cases of AI, but not the way the want it to be. Quite similar to Blockchain. The idea of decentralized money has right to exist. 99% of other coins not.

AI is a faster, but still less accurate search engine. AI is great in finding bugs, it’s great at ruber duck debugging.

The reason I call it a swindle is, because along with the marketing it gives tons of people in the world the impression, they can now build their own startup, game, infra etc without the need to learn it themselves. This leads to millions of abandoned and low qualiy projects and products, because the vast majority has never built the mental modal necessary to solve the problem thoroughly. In the end they’ve wasted months and money (but burnt tokens). This is what I call a swindle.

All early adaptors I know have not drastically winded down their usage, not because of money, but because there is no new case. If you want to explore a new project you can get onboarded quickly learn a lot and then switch to documentation and live testing. For me usage is the lowest it has been the last 2 years.

I would not let AI touch my code. I have anxiety around it, because it will gripple back up. I will let it read my code and let me know what I did wrong so I’m sharpening myself.

100s of companies including open source solution can offer that for me.

All my non-tech friends are now in hype cycle and share their hype and fore forseeable frustration with me.

I have to say I’m in a way impressed in how AI has been rigorously vc-utilized (conciously or not-conciously) to generate these vast companies with the whole world watching.

jwpapi··on Using AI to write better code more slowly
The greatest part of this approach is that you actually become better in the process.

The downside is you use less tokens.

jwpapi··on We let AIs run radio stations
We have AI radio station for years? All the algorithms perform better than the general models though.

I’ve not listened to a radio station for years. No offense :/

jwpapi··on Zerostack – A Unix-inspired coding agent written in pure Rust
Because they don’t have an incentive to maximize your usage, but rather focus on solving probabilistic solvable problems for you.

Bigger harnesses need to balance upping your token usage and being helpful.

jwpapi··on Bun Rust rewrite: "codebase fails basic miri checks, allows for UB in safe rust"
That happened to my project as well. The main issue hasn’t beet that ai couldn’t solve the problem, but it became so slow and you need more and more verification layers and CI/CD that at one point you wish a simpler codebase back, with reasonable tests, with storylines in codes and so on.
jwpapi··on Project Gutenberg – keeps getting better
Ulnar Nerve Entrapement :/
jwpapi··on Project Gutenberg – keeps getting better
Please give me some book recommendations :)
jwpapi··on Rewrite Bun in Rust has been merged
It’s still 400k more lines
jwpapi··on Rewrite Bun in Rust has been merged
How life feels not using bun
jwpapi··on Rewrite Bun in Rust has been merged
This will go down in history as the biggest mistake of software engineering of all time.

Bun is the runtime of Claude Code, which is the core product of a trillion dollar company, which now sits on a vibe-coded app, where not a single person in the world has a proper mental model of.

jwpapi··on I Moved My Digital Stack to Europe
I own the domain govern.eu

I didn‘t yet have a good idea on how to utilize it, open to ideas.

jwpapi··on An AI coding agent, used to write code, needs to reduce your maintenance costs
I really like this question:

If you could wish for a codebase, which codebase would you wish for?

If you think a second on that question, you’ll realize you probably not wishing for a super feature-rich one, but an easy to understand one, quite close to what you have now. One that is easily to maintain and extend, depending on the upcoming business challenges.

jwpapi··on I'm going back to writing code by hand
Obviously this is all my fault and others might have a better jugdement when using it. I’m just sharing my experience compared to the promises you easily might believe reading X/HN/Anthropic.

I still have a lot of usage for AI: Exploration, Double-checking me, teaching me. But writing code became very tough for me to accept. Nex-edit autocompletes mainly

jwpapi··on I'm going back to writing code by hand
That’s the same story I had.

The swindle goes like this, AI on a good codebase can build a lot of features, you think it’s faster it even seems safer and more accurate on times, especially in domains you don’t know everything about.

This goes in for a while whilst the codebase gets bigger and exploration takes longer and failure rate increases. You don’t want it to be true and try harder so you only stop after it practically became impossible to make any changes.

You look at the code again and there is so much code spaghetti is an understatement it’s the Chinese wall.

You start working…, and you realize what was going on

I deleted 75,000 of 140,000 lines of code and I honestly feel like the 3 months I went hard into agentic coding I wasted and I failed my users by building useless features increasing bugs, losing the mental model of my code and not finding the problems I didn’t know about the kind of hard decisions you only see when you in the code, the stuff that wanders in your mind for days

jwpapi··on Bun's experimental Rust rewrite hits 99.8% test compatibility on Linux x64 glibc
https://x.com/bcherny/status/2052126079176093967
jwpapi··on Bun's experimental Rust rewrite hits 99.8% test compatibility on Linux x64 glibc
I meant the developers motivation with "whiny baby" and I take the point that this was over the top and I could’ve found better words.

But I meant that my comment is "politics-based and not technical", because the gut feeling is more based on my reading of soft factors than it is from in-depth technical analysis of everything involved.

jwpapi··on Bun's experimental Rust rewrite hits 99.8% test compatibility on Linux x64 glibc
I meant my comment not the rewrite
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