Ask HN: What are successful projects that started as prototyped hypotheses?

[vlaaad]

As I see it, there are 2 main ends of a spectrum when it comes to releasing projects that aim to solve problems:

- top-down approach: you state your problem, think it through, consider all related work in this problem space, think very hard, come up with multiple possible solutions, evaluate their trade-offs and implement the best one (a-la Hammock-Driven Design: https://www.youtube.com/watch?v=f84n5oFoZBc&t=1816s)

- rapid prototyping: you state your problem, come up with the easiest possible solution, test it, repeat (a-la Lean Development: https://en.wikipedia.org/wiki/Lean_software_development)

I know some great examples of the first approach (Clojure, Datomic, maybe Git?), but I don't know that many successes of the second approach. Furthermore, my personal work experience leads me to believe that the second approach, at least in practice, leads to a lot of wasted effort, so I'm interested to know whether it is so or not.

[marcus_holmes]

I get the feeling that the "wasted effort" in the second approach is about rewriting code.

Rewriting code is good in my experience. It's always better the second time around (or third, or fourth). It's not that my first attempt was rubbish, it's that I didn't understand the problem as well as I did the second time (and so on).

Lean is also about avoiding premature optimisation. Which is hard because it cuts against the grain of our engineer sensibilities. Doing something "good enough for now" is tough, when you know that with just a few more days' effort you could make it bulletproof. But I've had to delete "bulletproof" code so many times, because it turns out the product didn't need that feature, or it needed to work differently.

In the long term, Lean avoids more wasted effort, in my experience.

[AstralStorm]

There's a difference between Lean and Instant Legacy Code. The key difference is focus on simplicity including cyclomatic, compositional etc. Simple is not the same as simplistic. Lean as a methodology is meant to remove obstructions and waste in manufacturing. Effort is not a thing that can be wasted. Excess code is the waste. Fixing bugs is wasted time compared to not having them.

"Good enough for now" is a great excuse to keep hacks around and letting them accumulate to the point where code is unmaintainable. Meaning too much code, meaning waste. Even better is "it works now, do not touch" especially when current code base is untested.

Programmers are typically lazy and do not bulletproof anything ever. Thus rampant security issues.

The alleged wasted effort is from the point of view of some manager who doesn't get to tick boxes quicker. (And disregards later massive drop in development velocity while presumably demanding same results.) This means spotted issues are pushed towards never unless a customer reports them. Which they won't or even can't so you get your software brand recognized as buggy trash - with workarounds being commonly peddled among users and devops.

[QueensGambit]

This is a common view these days. But as a technical founder, I disagree with this view. Once you launch the bare minimum first version, there are different customer segments who pull you in different directions. Often you chase one path and find that the customer segment is not lucrative enough and chase the next. Till you find a compelling usecase with money making potential, you will end up with various set of features used by different customer segments.

This might still be less wasteful when compared to building an entire product and finding no customers. But, it is taxing on the technical founder! Lean washing shouldn't set a wrong expectation for the technical founder involved in startups that follow the rapid prototyping approach.

[dangerface]

I agree, ultimately you never know if your effort was wasted until the prototype is made and you know if it's successful or not which is the only purpose of a prototype.

> It's not that my first attempt was rubbish, it's that I didn't understand the problem as well as I did the second time

I think thats too soft, I know my first attempt will be rubbish so I intend it to be so. To me the point of a prototype is to help you learn the problem more than to solve it.

If you plan to keep your prototype if it works out then I think you have missed a trick, a prototype should aim to fail quickly.

If your prototype is useful then I think it fails its point as a prototype.

[wefarrell]

Twitter: https://en.wikipedia.org/wiki/Twitter#Creation_and_initial_r...

Airbnb: https://www.telegraph.co.uk/technology/news/9525267/Airbnb-T...

Facebook: https://en.wikipedia.org/wiki/History_of_Facebook#FaceMash

Yahoo: https://en.wikipedia.org/wiki/History_of_Yahoo!

[Edmond]

Maybe the OP needs to clarify what type of "problems" exactly he is referring to..the examples he gives point to problems requiring significant engineering efforts, which is very different from the examples you note above.

[dasil003]

Top-down generally only works for a well-understood problem domain, and even then it only holds up for focused projects where you have the power to declare what is in scope and out of scope in a very strong fashion. This works better for dev tools, libraries, middleware or other projects that are abstract and not tied too closely to a specific business or end-user goal. In other words, the more abstract the tool and the more technical the audience, the more likely that you can drive massive impact while maintaining a simple vision and avoiding all kinds of edge cases and incidental complexity.

Rapid prototyping is more optimal for any end-user product or any new domain, because it’s a faster way to discover the unknown unknowns, both in terms of user features as well as well as technical challenges you may not have anticipated.

[irjustin]

I believe Git to be actually part of the 2nd than the first group.

Linus built the working prototype/self-hosted in 3 days mixing a lot of his learnings from bit-keeper and his knowledge of disk management [1].

To me, that's rapid prototyping. It's enough domain knowledge to make it work for himself well. He didn't spend a bunch of time thinking nor coming up with solution since he was actively building Linux at the time. The key is he employed the help of others to build Git and eventually take it over since he wanted to focus on Linux.

This all comes with a huge caveat in that Linus's 3 days == 1000 of mine. His 'just enough' knowledge is near expert level.

As others have asked, what are you trying to build? A technical solution or an end-user solution.

Technical solutions do require a lot more domain knowledge than a twitter/airbnb (at the early stages).

In the end, I believe in rapid prototyping and failing fast[2]. Learn just enough, whether technical or end-consumer to launch fast.

The thing I agree 100% is though, don't break user-space [3]. I believe this applies to end users of products, whether developers or customers. Once people start consuming something, don't break it. Doesn't matter whether you believe it to be 'correct' or a 'bug'. Expectation management of slow and easy depreciation.

[1] https://en.wikipedia.org/wiki/Git#History [2] http://paulgraham.com/startupmistakes.html [3] https://lkml.org/lkml/2012/12/23/75

[ssivark]

Linus’s three days of coding effort was probably preceded by months/years of thinking abut the essence of version control for a large distributed development project (a la the Linux kernel). It’s difficult to just stumble on what became the internal structure of git in just a few days if you just started thinking about version control systems.

So, for me the distinction between the two approaches (prototyping -vs- hammock driven) is lately about whether you are solving a largely known/understood problem (equivalent to having domain expertise, in an absolute sense) -vs- solving problems to which you don’t know the answers. In the latter case, there is no shortcut getting around thinking time.

Or, as they say: “A month in the laboratory could save an hour in the library”

[zupa-hu]

I feel like the question is mixing 2 things.

One is using a top-down approach versus an iterative approach. The other is about the nature of your problem: do you have product risk or market risk?

The lean approach is about eliminating waste, which, in the context of startups, often means building something small and talking to users. But that's only because most startups have market risk. If you have product risk, you should still iterate on your solution instead of building it in one go.

I feel like you are asking for examples where the market-risk was addressed. The most interesting companies would be those where the first test was a total miss and they solved a totally different problem in the end.

[chubot]

I don't think your dichotomy is valid.

Git definitely doesn't fit the first approach. Not sure why you would state that.

Maybe the core of Clojure, with the persistent data structures, fits the first approach, but I doubt the rest of it does (speaking as an outsider to th eproject).

"Implement the best one" belies a lot of sweat and places where it could have gone wrong. In other words, the initial thinking is not even addressing half of the problem or doing half the work.

The philosophy of Clojure itself is very much based on iteration and interactive programming. You need a lot of action, feedback, and iteratino in addition to the "think very hard" part.

[_0ffh]

Wouldn't Lisp count for the top-down approach? Only that most of the thinking was done without thought spent on an actual implementation, and the actual implementation was done by different people who recognised the practicality of it?

[pbiggar]

Dark (https://darklang.com) was a bit of both. I spent several years thinking about the problem, and once I had a solution and decided to work on it, went into rapid prototyping to figure out if it could work. To a certain extent, we're still in that phase, just with a much bigger team now.

[james_impliu]

Two examples of rapid prototyping spring to mind:

* Twitch, started as one guy streaming his life then they realised lots of gamers were watching, and that they'd like to be able to stream https://www.youtube.com/watch?v=FBOLk9s9Ci4

* Segment, started as a thumbs up/down tool for professors in lectures to work out when students are getting confused. They realised everyone just went to Facebook instead, then they wondered why they couldn't tell this when they were remote! https://www.youtube.com/watch?v=l-vfn97QTr0

[vmurthy]

One of HN favourites (?) DropBox : https://techcrunch.com/2011/10/19/dropbox-minimal-viable-pro...

[misiti3780]

have you ever seen an early write up of the technology that powered that demo. I know it was all written in python but I was curious how they were doing it early on.

[johannes1234321]

The reality often is a mixture.

If you don't know your problem there is nothing to prototype, no minimal viable product. Nothing.

If you spend years analysing and planning you get nowhere.

You need to have an idea, a problem which has to be solved, but should not be lost in the forest.

[TeMPOraL]

At a strategy level, which one of the two points you end up doing depends on who commissions and evaluates the work. If someone hands you a spec and then disappears, only to come back 5 years later and expect to receive a finished project, you'll be working "top-down". If you're trying to solve someone's immediate problem with software, and are in regular contact with that someone, you'll be working in "rapid prototyping". All projects, software or otherwise, are spread around the spectrum between the two endpoints. Where exactly depends on specifics, but if you're starting a new project, the consensus is that you should aim to be closer to the "rapid prototyping" end.

At a tactical level, feature level, you mix both. You state your problem (or get it stated to you), you think it through, hopefully considering at least some related work and doing some hard thinking, come up with multiple possible solutions and evaluate their trade-offs... by implementing their prototypes as fast as possible, because that's the only real way to discover the trade-offs. Depending on how much in a hurry you are, you might pick the first prototype that isn't a total disaster and build your feature from it, then test it, and repeat.

See how "top-down" and "rapid prototyping" is interwoven here. This approach can be expressed as: think before you do, but remember that you only learn the true scope of a problem by attempting to solve it.

[muzani]

I like and have successfully used the Business Model Canvas approach. You fill in all assumptions. Test the riskiest one in the simplest manner, then move on. E.g. if you're not sure you can find the right partnerships, look for that first. If you're not sure the value proposition would work, interview some people, make some mockup PowerPoint slides, and so on.

[widforss]

My personal avalanche detection project https://avanor.se (I haven't started the image uploads for this season yet), seems to fit the second model. It's very simple and small, but is successful in terms of being a prescribed tool for professional avalanche forecasting in Sweden.

I think it's on it's third rewrite or something right now, and runs circles around the only other service in this space regarding bang for the bucks (guess my budget, its smaller than that).

[navd]

Just because you build a project with the second approach, it doesn’t mean you haven’t thought about alternative solutions or design like defined in the first.

A lot of times it’s useful building products by rapidly iterating because you see flaws, holes in your thinking, and get feedback immediately from people who are going to use it.

Immediate (or shorter term) feedback can be very helpful.

But to answer your question, YC talks a lot about Twitch being an example of the second approach.

[jes5199]

A large working system must evolve from a small working system. There's no way to start large.

[empthought]

I think Django is a reasonable example of the second approach.

[z3t4]

Human powered flight.

[pryelluw]

Are you thinking of this as a value driven approach?

[jdennaho]

solve a problem you have, it might now scale or spread, but you received some benefit for it.