I dont want to dump on the founder here. I appreciate their guts for saying the uncomfy part out loud and being so honest, open and aware of their own thoughts. Major kudos in my book. But dont quit without a quit criteria - a problem, customer conversations, recurring problem insight. Fuck the VCs that say just do it, its advice for rich kids not people who worry about finances running out. Given that this author worked at Posthog, it probably means they lived in London and got paid a decent salary but not a good one. eg Posthog lists their comp at 120k pounds with equity (that thing doesnt have liquidity yet). Thats not a top of the line offer in London where Meta / Goog and others would beat it. Once you have say 100k pounds saved up and mortgage for the next 2 years, maybe then you can think of bootstrapping without an insight. Until then, Leetcode, promotions, better offers are your ticket out of a middle class life. VCs wont show up with more money if and when you're hungry.
Regular user here. Cant live without this addon, I absolutely love this. Its been a while since I have to manually dismiss a consent popup. Although the redirects from Google and company can get a bit annoying.
Same here - did the grind for a few years then went straight to big tech. I got offers from the full set of FAANG. I still have a disdain for code monkey work as a job (I really think its practically unskilled labour). I had studied ML to a fairly high level, so landing gigs was easy. Not to mention the money is so much better.
I mean its a matter of RoI, isnt it ? Investing in your existing partnership means that specific business can come to you for their problems rather than work up so much expertise bloat. I suppose there a point after which more expertise hurts a business.
If big companies could align themselves quickly they could copy your software since 10years ago. The issue is unwillingness. Why would Meta bother with copying a SaaS ? They are making money head over fist with their ads business. Keep in mind how much money big tech makes. Mark Zuckerberg personally is worth 100B dollars, most startups will be lucky to hit that number in their lifetime. Point is, its bot worth their time to pursue new ideas but rather buy out existing ones. Which is good news.
Zero to one makes this crystal clear. Most startups die because they didnt manage to sell not because they didnt manage to build the product. Secondly there was never a code moat. Code was always cheap. But architecture, distribution, quality control, integration once landed, this is where money is mostly made. Most indie or small companies die because they just pick shitty problems. eg nobody cares about a goddamn notes app, the one on Mac works fine and most people write garbage in their notes like utter trash. So obviously a notes app has little value because the asset it manages has very little value. Not so much if you are building something like document storage for regulated industries. Or compliance software. In these cases, its the business domain expertise which counts. Even when applying for jobs without domain expertise code monkeys never get paid past a threshold. People / entities that command a premium are the ones with domain knowledge.
The most talked about air pollution story in India is Delhi. If you live in India you probably know that the major contributor there is not vehicle smoke but smoke from burning stubbles from nearby agricultural fields. It doesnt happen in other countries with similar agricultural output since stubble finds more profitable avenues eg fodder for livestock. In India, the most profitable thing to do with stubble is to burn it and prepare quickly for the next sowing season.
This is to say that the EV transition wont put a major dent in Delhi's annual air pollution story.
For the other cities, it will have the same impact as anywhere else. Eg when Paris banned or limited vehicle traffic, the air quality improves substantially (BBC had a few before / after pics). Given that India is densely packed, an EV transition should improve air quality markedly atleast in major cities. It wont do anything for other sorts of pollution such as water pollution in the Yamuna but that will take time since these days even London can't keep shit out of the Thames.
In AOF mode does Redis write all changes to a WAL ? Is this paired with periodic snapshotting to prevent the log from growing too large ? Does this work in distributed mode or is this single node thing ?
Because the time investment isnt worth it most of the time. Unless its a widely used framework / library its worth no ones time to try and understand API docs, each and every component and then deal with some genius patterns thrown here and here. Its a skill that has low market value so sharpening it isnt worth it.
Disagree here. APIs are meant for using and not learning. But the context matters here. For some paid system, there better be an API thats easy to use or I am throwing AI at the problem or hoping someone else will do it. If its something worth learning - say Guava data structures or RocksDb core - yup I'll invest the time to learn. That learning transfers over. But trying to learn some shitty AWS api and its nuances, no thanks. Some payment system that a handful of people use - no thanks again.
buddy, don't be so modest, this is an ambitious project and I hope you succeed ! This is tough work, I tried to build a Webflow-ish editor myself and it nearly destroyed my sanity.
I tried ShadCN then quickly ported everything over to Mantine. A bit of config magic later, I can quickly whip out functional UIs faster than I can think of features.
The issue seems to be that LLMs already consumed large parts of the templatized code somewhere. Not directly from TW but from some other project. Codex / Claude are also exceptionally good at whipping out a UI quickly even when given flimsy requirements. Its hard running this business and competing against a several billion dollar machine. Wonder how Material UI is doing as they have a similar business model.
Standard promo advice tbh. Do the job and then ask for it. Except there's a brief moment when you are adding value not in proportion to your compensation which will be infuriating. Sometimes its also possible you end up stagnant where you keep performing at a higher level and never get the job. My advice is to always check your market value by talking to recruiters and/or HMs outside of your company. That way once you have the relevant bullets on your resume, either you get the promotion or you just leave. Hedge your bets.
Plus who gives a shit if a penguin teaches the course as long as its good. Open AI Board member teaching an AI course sounds like that terrible startup course that Peter Thiel taught on coursera. Where one of the lessons focussed on Vim. Although tbf Thiel teaching a startups course has a lot more legitimacy. This title just makes it sound like a studio exec trying to teach people how to make movies.
None of the generic thought leadership books are particularly useful. I've noticed that the best way to keep relevant as an engineer is to ignore flavor of the day frameworks and tech but rather focus on the basics. For example, if you're working in financial modeling, one way to improve as an engineer to get better at the domain. Maybe "Advances in Financial Machine Learning" by Marcos López de Prado. You'd have to work through the math and pick up finance on the go (which I assume should be easier part). As for people doing cool stuff in Zig / Rust, what matters is the problem not the hammer they're using to solve it.
I don't think you have to claim you made that thing up. I don't care about the language, the hyperbole of the post just the claims. The claim that you know the OP of an anonymous reddit account is where I'd stop reading.
What about the claims though ? I dont see the point of getting hung up on just this and discrediting the rest of the story. Tbf this proves nothing without more confirmations however it might be possible to design client side A/B tests to catch this type of behaviour. Might be something NYT or some group with a well resourced investigative arm could pull off.
Yup. Engineers do have visibility into fintech systems that they implement, maybe even more so than the bean counters since they can trace exactly which txns went where. These things are logged.
2. tip theft and pay the rent are valid terms here.
3. quite likely something like this will exist and it might not be called that right in the code base but it sounds like something that will show up in Slack conversations. From a pure ML perspective (throwing ethics out the windos, this is a good feature)
4. this one sounds sus because cash flow details may not be something a backend engineer might be privy to.
5. UberEats as well. Either ways its quite difficult to say whether or not this is true. But the post does say that tipping theft works by reducing base pay and having the customer pick up the tab. So its not so straightforward.
Started by reading lots of articles on Topcoder (they have a dynamic programming tutorial which imo is the best material on DP). Then did exercises from CLRS before writing a single line of code. I considered it leg work and not of very high value (remains true though, the best paying jobs in tech are research and in finance its quant trading). Then I dived head first into C++ and Java, slogged through the pain and I got absolutely hooked. I learnt almost all of the computer science I know through books, good old fashioned working through exercises, doing lectures on MIT Ocw. Never paid a single cent for any professional courses or bootcamps or any of that jazz. I did write some Python in high school but most of the work I did while at uni studying something else entirely. My initial objective was not to build anything at all but to just get better at competitive coding. But then I built something reasonably complicated and I have been an engineer ever since. I have worked in ML, distributed systems, low level systems programming in the past 10years. To answer the question I learnt coding by self study.