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It's interesting to see how most of the comments here are either "no, this is how lots of startups end up with a mess they have to clean up" or "yes, lots of st
by sanderjd 3y ago
It's interesting to see how most of the comments here are either "no, this is how lots of startups end up with a mess they have to clean up" or "yes, lots of startups optimize this stuff too early".
And I think that's because both things are true! This is one of the many hard parts about starting a brand new company, figuring out the right balance to strike on this. It's no surprise that companies mostly get it wrong, and in both directions.
There's no single right answer here. It depends on exactly what the company does, the exact path to product market fit, what growth looks like afterwards, and how lucky the guesses about all that stuff were.
- svachalek 3y agoAre there companies that die because they produced something people loved and wanted to buy but just couldn't deliver because off the shelf components were just too subpar? I haven't seen that case. I have seen companies die trying to perfect software no one is buying though, quite often.
- brigadier132 3y agoOf course companies have died because of quality issues. Framing it as "they produce something people love but the quality is subpar" is a false framing. There are no subpar products that people love. First of all, "quality" is relative. See chatgpt, it's wrong half the time, in a decade if someone were to release a chatbot of chat gpt quality we would say it's terrible. But today, it's the best we have. The classic story is how airbnb and stripe launched without coding anything, everything was done manually. Now launch an airbnb competitor today using the same strategy. Obviously comparing yourself to airbnb is dumb, because back then all software was terrible. The actually successful modern companies of the past few years are openai, tiktok and figma. They all launched with complete products and are massively successful. That's what it takes today. > I have seen companies die trying to perfect software no one is buying though, quite often. Most companies die.
- anonylizard 3y agoQuality is absolute. There were multiple LLMs released before ChatGPT, none made any splash, including GPT-3. Meta released one like 2 weeks before ChatGPT, and had to shut it down for bad output quality. Only GPT3.5 started to meet the 'wow factor' for it to go fully viral. Until a product hits a minimum quality threshold, its useless. Which is basically what you stated later. Now most areas are mature enough that a copy pasted solution hits that minimum threshold (Eg, setting up a basic ecommerce site with ordering and payment). But for uncharted territory, that threshold is very real, hit it or die.
- sanderjd 3y agoI think almost certainly, yes? But I think it would require a whole research project to gather persuasive data on this, in both directions. But my intuition is that failing to find product market fit (for whatever reason) kills companies earlier, whereas hitting product market fit with a subpar engineering foundation is more likely to slow companies down in later stages where they die more slowly or just underachieve. I think Twitter is probably the best known example of that second pattern. It may be apocryphal that this was their problem, but either way, I think this is a real phenomenon in general.
- konschubert 3y agoYou can use off-the shelf components and use boring technology without making a big mess out of technical debt. The alternative to building your own DB isn't to put everything into a big json file. The correct alternative is Postgres.
- sanderjd 3y agoThis is basically what I was trying to say as well. The trade-off I'm talking about is not "off the shelf and boring" vs. "bespoke and exciting", it's more nuanced than that. The decision companies have to make is more like "what is worth our time and investment and what isn't?". That "time and investment" trade-off may involve custom code vs. off-the-shelf solutions, or it may be between a managed psql that doesn't provide a useful configuration vs. self-hosting and maintaining that configuration yourself, or any number of other build-vs-buy and expedience-vs-longevity decisions. My point is just that it's very case specific, and you can easily guess wrong in either direction.