How to Get Startup Ideas, Jared Friedman

The first, most common mistake is believing that you need an amazing idea to get started.

When Google started, it was, like, the 20th search engine. And when Facebook started, it was, like, the 20th social network. What made them successful wasn’t a brilliant initial idea. It was a good enough initial idea, combined with great execution.

The next mistake is exactly the opposite: jumping into the first idea that comes to mind, without really stopping to think critically about whether it’s a good idea at all.

Startup ideas morph over time. Take Airbnb, for example. Airbnb was initially literally a website for renting air beds at other people’s houses. It morphed over time into all vacation rentals. So the thing you want to do is to pick a good starting point.

The third mistake is to start with a solution instead of a problem. We see this so commonly at YC that we have a term for it. It’s called a “Solution In Search of a Problem,” or a SISP.

The last mistake is believing that startup ideas are hard to find. Actually, they’re easy to find, because there are many, many real problems left in the world.

Let’s talk about evaluating startup ideas.

The first criteria is how big is this idea? Founder/market fit. The next criteria is how sure are you that you’re solving a big problem? And finally, do you have a new, important insight into this idea?

Here are some other signs to look for that your idea is probably a good one. You’re making something you personally want to have.

Another sign is that this only recently became possible.

My last topic about evaluating startup ideas is to talk about filters. Filters are bad reasons to reject startup ideas.

The first is rejecting ideas that seem hard to get started.

The second filter is ideas that are in a boring space.

The third one is ideas that seem too ambitious.

The last one is that founders instinctively shy away from spaces where there are existing competitors.

Now the part that you’re probably waiting for, how to generate startup ideas.

The best way to have startup ideas is to notice them organically. There are great startup ideas all around you, and when you have a prepared mind, you see them everywhere.

So first, I want to talk about how to have startup ideas organically.

If you’re planning to start a startup way in the future, it’s very helpful to become an expert on something valuable, and the best way is probably to get a job at the forefront of some field. If you’re working at the forefront of some field, really any field, you’ll see good startup ideas before other people. It’s particularly helpful to go work at an existing startup.

Okay, I’m gonna walk through seven recipes for explicitly generating startup ideas.

This first recipe is the best one. You start with what your team is especially good at, and think of ideas that you would have an unfair advantage in executing. Let’s walk through some examples of how to do this. The first thing I do is I go through every company you’ve ever worked at. Internships are fine. And for each one, I’d ask yourself what are things you learned there that other people don’t know? Then, ask yourself, for each company, what seemed broken? What parts of company life were clumsy?

Second recipe, think of things you wish someone else would build for you.

Third recipe. What would you be excited to work on for 10 years, even if it didn’t succeed? What things are you really passionate about? I have seen this recipe lead founders astray, so I wanted to warn you about it. It can lead founders astray by encouraging them to work on something that they’re very passionate about, but that does not have a clear path to being a big business.

Number four, look for things that have changed in the world recently, and think of ideas that are now possible because of this change. For example, a new technology, a new developer platform, a new regulation, a new problem in the world. What are waves that you could ride?

Number five, find companies that have been successful recently, and look for new variants of them. This is a very common way that founders look for ideas, but unfortunately, it’s not necessarily the best one. Ideas that are generated this way often take a form like “Uber for X,” or “Airbnb for Y.” These ideas are very often solutions in search of problems, so if you come up with an idea this way, you should be default skeptical, and you should think really hard about whether it is actually solving a problem.

Number six, you can also crowdsource coming up with an idea by talking to people you know, and asking them for problems they want solved. This is especially interesting to do with people who have particular areas of expertise, like people who work in an interesting industry, for example. The downside with this recipe is that most people are bad at seeing startup ideas. That’s why this strategy seems to work particularly well if the people you ask are other startup founders. They already know how to notice good startup ideas.

And, number seven. Look for industries that seem broken. Any industry that seems broken is probably ripe for disruption. The downside of this recipe is it will often take you to ideas that have poor founder/market fit. It’s not likely to work well if you don’t know anything about the industry you’re hoping to disrupt.

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14 Points for ManagementAI is about making better, faster, cheaper...Abstractions raise tempoAct according to actual circumstancesAgile is the steering wheelAndon cords push decisions down the chainArchitecture sells optionsBayesian stats need simulationBayesianBe decision-driven, not data-drivenBe waterBeware of coordination headwindsBeware the ambiguity effectBlend multiple command systemsBuild and sellBullshit is more dangerous than lies to truthBusinessCarseCharacteristics of Special OpsChristopher AlexanderClimb the identity ladderClosed and open systemsComplexityConceptsContent actionability can be a crutchContradictions reveal answersData ScienceData science is not scientificDebt reduces optionalityDecision contexts can be complicated or complexDecisions matterDeleuzeDemingDo not tamperDon't forecastDon't look at the literature too soonDon't make single point forecastsDon't make type 3 errorsDruckerEinstein's DreamsEquality and freedom are opposedFacts dont change mindsFast languagesFire bullets, then cannonballsForecasting in human affairs is precariousFour laws of combatFoxes predict better than hedgehogsFunnel ExperimentGirardGo beyond ExcelHaikusHourly billing punishes expertiseHow Complex Systems FailHow to Get Startup Ideas, Jared FriedmanHow to Measure AnythingHow to Pitch Your Startup, Kevin HaleHow to Talk to Users, Eric MigikovskyHow to do philosophyHuainanziIOHAIIdentifying the Centre of GravityIllusion of objectivityIn complex contexts, simulateIn complex contexts, use AI as sensorsIncentives matterIncrease your tempoInman's rulesIntelligence Analysis FrameworkJockoJohn BoydKeep it simpleKeep movingKeep your identity smallKnow thyselfLeadershipLevel productionLeverage PointsLibertarianismLinear roadmaps are a lieLittle big foreign phrasesLittle big phrasesMBO ignores processesManeuver warfareManufactured fun is no fun at allManufactured fun is not funMarketing AttributionMarketing is designMessy thought, neat thoughtMilitaryModel Questions vs Actor QuestionsMost things aren't treesMuddle throughName three alternativesNations don't trade with each other, people doNever do great thingsNobody knows anythingNon-systemic thinking is LAMONothing in excessOKRs aid EinheitOKRs are not that greatOODA LoopsOmit needless wordsOperating on the front is the way to use...Oren KlaffPaul Graham et alPeople are not the problemPersuasionPhilip MorganPhilosophyPointersPoints of viewsPolicyPournelle's iron law of bureaucracyProbes over experimentsProductivityProducts are functionsQuestions revealQuotesReality has a suprising amount of detailRecognizing the two times of schedules is central...Repeated games are different from single turn onesRithwikRyan Singer on Christopher AlexanderScreen sharing is the modern GembaSocial networks are like ICOsSolutionismSometimes daily billing makes senseSpeed mattersStart with actionState of Play, 20 questions, VGRStoicismStory Structure 101StrategyStrong opinions, weakly heldSubtractSun TzuSystems over goalsSystemsTeam of TeamsThe five elements of an organization that can...The three languages of politicsThe use of AI can be strategicThere are trade-offs everywhereThere is a robustness-efficiency tradeoffThere will be a last timeThink in publicTiagoTimeToyota Production SystemTrainability wins at scaleTraining helps in calibrations and predictionsUse more Saxon words to be clearVGRVia negativaWanting has layersWhat is Decision EngineeringWhen AI met StrategyWittgenstein's RulerWords matterWrite code, talk to usersWriting heightens consciousnessWritingYCombinator Startup SchoolYou need less dataYou need more data14 Points for ManagementAI is about making better, faster, cheaper...Abstractions raise tempoAct according to actual circumstancesAgile is the steering wheelAnalysis and SynthesisAndon cords push decisions down the chainArchitecture sells optionsBayesian stats need simulationBayesianBe a Greek, not a BabylonianBe decision-driven, not data-drivenBe waterBeware of coordination headwindsBeware the ambiguity effectBlend multiple command systemsBuild and sellBullshit is more dangerous than lies to truthBusinessCRAP framework for dealing with workplace bullshitCarseCausalityCharacteristics of Special OpsChristopher AlexanderClimb the identity ladderClosed and open systemsComplexityConceptsContent actionability can be a crutchContradictions reveal answersData ScienceData science is not scientificDebt reduces optionalityDecision contexts can be complicated or complexDecisions matterDeleuzeDemingDesignDo not tamperDon't forecastDon't look at the literature too soonDon't make single point forecastsDon't make type 3 errorsDruckerEinstein's DreamsEquality and freedom are opposedFacts dont change mindsFast languagesFire bullets, then cannonballsForecasting in human affairs is precariousFour laws of combatFoxes predict better than hedgehogsFunnel ExperimentGirardGo beyond ExcelHaikusHourly billing punishes expertiseHow Complex Systems FailHow to Get Startup Ideas, Jared FriedmanHow to Measure AnythingHow to Pitch Your Startup, Kevin HaleHow to Talk to Users, Eric MigikovskyHow to do philosophyHuainanziIOHAIIdentifying the Centre of GravityIllusion of objectivityIn complex contexts, simulateIn complex contexts, use AI as sensorsIncentives matterIncrease your tempoInman's rulesIntelligence Analysis FrameworkJTBD by data teamsJockoJohn BoydKeep it simpleKeep movingKeep your identity smallKnow thyselfLeadershipLevel productionLeverage PointsLibertarianismLinear roadmaps are a lieLittle big foreign phrasesLittle big phrasesLoreMBO ignores processesManeuver warfareManufactured fun is no fun at allManufactured fun is not funMarketing AttributionMarketing is designMessy thought, neat thoughtMilitaryModel Questions vs Actor QuestionsMost things aren't treesMuddle throughName three alternativesNations don't trade with each other, people doNever do great thingsNobody knows anythingNon-systemic thinking is LAMONothing in excessOKRs aid EinheitOKRs are not that greatOODA LoopsOmit needless wordsOperating on the front is the way to use...Oren KlaffPaul Graham et alPeople are not the problemPersuasionPhilip MorganPhilosophyPointersPoints of viewsPolicyPournelle's iron law of bureaucracyProbes over experimentsProductivityProducts are functionsQuestions revealQuotesReality has a suprising amount of detailRecognizing the two times of schedules is central...Repeated games are different from single turn onesRethink design thinkingRithwikRyan Singer on Christopher AlexanderSailing over rowingScreen sharing is the modern GembaSocial networks are like ICOsSolutionismSometimes daily billing makes senseSpeed mattersStart with actionState of Play, 20 questions, VGRStoicismStory Structure 101StrategyStrong opinions, weakly heldSubtractSun TzuSystems over goalsSystemsTeam of TeamsThe Expert's TrilemmaThe five elements of an organization that can...The three languages of politicsThe use of AI can be strategicThere are trade-offs everywhereThere is a robustness-efficiency tradeoffThere will be a last timeThink in publicTiagoTimeTo think is to forgetToyota Production SystemTrainability wins at scaleTraining helps in calibrations and predictionsUse more Saxon words to be clearVGRVia negativaWanting has layersWhat is Decision EngineeringWhen AI met StrategyWittgenstein's RulerWords matterWrite code, talk to usersWriting heightens consciousnessWritingYCombinator Startup SchoolYou need less dataYou need more data