I’ve been coworking at a nearby town and a couple of us decided to try to help encourage each of us in our startups.

Being a startup junkie and an Agile Coach, I thought, “Why not a startup standup?” Each week we meet in person. There, each of us announces what they accomplished in the last week, what they’re planning in the next week, and what they’re number one problem is. No classes, no group-gropes, no fluff. Immediately after the ten-minute standup we can each help each other if one of us has an obstacle that we know about. Plus we can help each other position our work mentally in order to focus more on the right stuff and less on the wrong stuff.

So how to describe what we should be talking about?

I pulled down a couple PG essays, a blog on the Lean Startup concept, and some notes Derek Sivers made while reading the Lean Startup book. But heck, it was still too much verbiage. Put together, it was WAY too much to expect noobs without context to plough through. I decided to cut a bit. So here’s an effort to make a crash course in what you should know and talk about during a weekly report of your activities in a startup. I liberally edited for clarity and brevity.

1. What is a startup? (From PG’s 2012 essay)

Not every company is a startup. Millions of companies are started every year in the United States. Only a tiny fraction are startups. Startups are companies that make something people want that have the ability to scale rapidly. They may or may not involve technology.

For a company to grow really big, it must (a) make something lots of people want, and (b) reach and serve all those people. Barbershops are doing fine in the (a) department. Almost everyone needs their hair cut. The problem for a barbershop, as for any retail establishment, is (b). A barbershop serves customers in person, and few will travel far for a haircut. And even if they did the barbershop couldn’t accommodate them.

Writing software is a great way to solve (b), but you can still end up constrained in (a). If you write software to teach Tibetan to Hungarian speakers, you’ll be able to reach most of the people who want it, but there won’t be many of them. If you make software to teach English to Chinese speakers, however, you’re in startup territory.

Most businesses are tightly constrained in (a) or (b). The distinctive feature of successful startups is that they’re not.

2. Do you need a cool idea?

No, you do not.

3. What are you concentrating on and talking about while you are developing your startup? You are creating and testing value and growth hypothesis. A value hypothesis is a concrete way to determine what you are doing has value to your customer. A growth hypothesis is a concrete way to determine how you gain new customers. These are both measurable, and you have to have real results that indicate success or failure for your hypothesis. That means heavy, direct interaction with the people you are supposed to be making things that they want. More Lean Startup goodness from Sivers’ notes:

Startups are human institution designed to create new products and services under conditions of extreme uncertainty.

The stories in the magazines are lies: hard work and perseverance don’t lead to success. It’s the boring stuff that matters the most.

Startups exist to learn how to build a sustainable business. This learning can be validated scientifically by running frequent experiments.

The goal of a startup is to figure out the right thing to build – the thing customers want and will pay for – as quickly as possible.

Too many startup business plans look more like they are planning to launch a rocket ship than drive a car. They prescribe the steps to take and the results to expect in excruciating detail, and as in planning to launch a rocket, they are set up in such a way that even tiny errors in assumptions can lead to catastrophic outcomes.

The customers failed to materialize, the company had committed itself so completely that they could not adapt in time. They had “achieved failure” – successfully, faithfully, and rigorously executing a plan that turned out to have been utterly flawed.

Instead of making complex plans that are based on a lot of assumptions, you can make constant adjustments with a steering wheel called the Build-Measure-Learn feedback loop. Through this process of steering, we can learn when and if it’s time to make a sharp turn called a pivot or whether we should persevere along our current path.

Validated learning is the process of demonstrating empirically that a team has discovered valuable truths about a startup’s present and future business prospects. It is more concrete, more accurate, and faster than market forecasting or classical business planning.

Learning is the essential unit of progress for startups. The effort that is not absolutely necessary for learning what customers want can be eliminated. I call this validated learning because it is always demonstrated by positive improvements in the startup’s core metrics. As we’ve seen, it’s easy to kid yourself about what you think customers want. It’s also easy to learn things that are completely irrelevant. Thus, validated learning is backed up by empirical data collected from real customers.

Learn to see every startup in any industry as a grand experiment. The question is not “Can this product be built?” In the modern economy, almost any product that can be imagined can be built. The more pertinent questions are “Should this product be built?” and “Can we build a sustainable business around this set of products and services?” To answer those questions, we need a method for systematically breaking down a business plan into its component parts and testing each part empirically.

One of the most important lessons of the scientific method: if you cannot fail, you cannot learn.

A true experiment follows the scientific method. It begins with a clear hypothesis that makes predictions about what is supposed to happen. It then tests those predictions empirically. Just as scientific experimentation is informed by theory, startup experimentation is guided by the startup’s vision. The goal of every startup experiment is to discover how to build a sustainable business around that vision.

A minimum viable product (MVP) is simply the fastest way to get through the Build-Measure-Learn feedback loop with the minimum amount of effort. The goal of the MVP is to begin the process of learning. Its goal is to test fundamental business hypotheses.

Most entrepreneurs approach a question like this by building the product and then checking to see how customers react to it. I consider this to be exactly backward because it can lead to a lot of waste. First, if it turns out that we’re building something nobody wants, the whole exercise will be an avoidable expense of time and money. If customers won’t sign up for the free trial, they’ll never get to experience the amazing features that await them. Even if they do sign up, there are many other opportunities for waste. For example, how many features do we really need to include to appeal to early adopters? Every extra feature is a form of waste, and if we delay the test for these extra features, it comes with a tremendous potential cost in terms of learning and cycle time. The lesson of the MVP is that any additional work beyond what was required to start learning is waste, no matter how important it might have seemed at the time. [Which may include actually building anything at all]

(Dropbox:) To avoid the risk of waking up after years of development with a product nobody wanted, Drew did something unexpectedly easy: he made a video. The video is banal, a simple three-minute demonstration of the technology as it is meant to work. It was all he needed at first to test a value hypothesis. Many entrepreneurs refuse to spend any time in development at all until some initial value and growth hypotheses have been tested in the real world and they have real metrics from the tests. (Anecdotes, like “I showed it to twenty people and they liked it” are not real metrics)

MVP can seem like a dangerous branding risk. Easy solution: launch the MVP under a different brand name. Experiment under the radar and then do a public marketing launch once the product has proved itself with real customers.

Prepare for the fact that MVPs often result in bad news.

The solution to this dilemma is a commitment to iteration. You have to commit to a locked-in agreement – ahead of time – that no matter what comes of testing the MVP, you will not give up hope.

A startup’s job is to
(1) rigorously measure where it is right now, confronting the hard truths that assessment reveals, and then
(2) devise experiments to learn how to move the real numbers closer to the ideal reflected in the business plan.

The failure of the “launch it and see what happens” approach should now be evident: you will always succeed – in seeing what happens. Except in rare cases, the early results will be ambiguous, and you won’t know whether to pivot or persevere, whether to change direction or stay the course.

Entrepreneurs need to face their fears and be willing to fail, often in a public way. In fact, entrepreneurs who have a high profile, either because of personal fame or because they are operating as part of a famous brand, face an extreme version of this problem.

I recommend that every startup have a regular “pivot or persevere” meeting.

Remember that the rationale for building low-quality MVPs is that developing any features beyond what early adopters require is a form of waste. However, the logic of this takes you only so far. Once you have found success with early adopters, you want to sell to mainstream customers. Mainstream customers have different requirements and are much more demanding. A pivot is required.

Startups don’t starve; they drown.

Startups have to focus on the big experiments that lead to validated learning. The engines of growth framework helps them stay focused on the metrics that matter.

Companies using the sticky engine of growth track their attrition rate or churn rate very carefully. The churn rate is defined as the fraction of customers in any period who fail to remain engaged with the company’s product. The rules that govern the sticky engine of growth are pretty simple: if the rate of new customer acquisition exceeds the churn rate, the product will grow. The speed of growth is determined by what I call the rate of compounding, which is simply the natural growth rate minus the churn rate.

Focus needs to be on improving customer retention. This goes against the standard intuition in that if a company lacks growth, it should invest more in sales and marketing. This counterintuitive result is hard to infer from standard vanity metrics.

4. So formulating and reporting on hard metrics resulting from direct user contact that prove or disprove our value and growth hypotheses is what we should focus on. Once we do that, what are some common mistakes? (From PG’s 2005 essay)

• Release Early. get a version 1 out fast, then improve it based on users’ reactions. By “release early” I don’t mean you should release something full of bugs, but that you should release something minimal.
• Keep Pumping Out Features. I don’t mean, of course, that you should make your application ever more complex. By “feature” I mean one unit of hacking– one quantum of making users’ lives better. [Which should directly come from your hypotheses testing results]
• Make Users Happy. There are two things you have to do to make people pause. The most important is to explain, as concisely as possible, what the hell your site is about. How often have you visited a site that seemed to assume you already knew what they did? The other thing I repeat is to give people everything you’ve got, right away. If you have something impressive, try to put it on the front page, because that’s the only one most visitors will see. Though indeed there’s a paradox here: the more you push the good stuff toward the front, the more likely visitors are to explore further.
• Fear the Right Things. Most visible disasters are not so alarming as they seem. Disasters are normal in a startup: a founder quits, you discover a patent that covers what you’re doing, your servers keep crashing, you run into an insoluble technical problem, you have to change your name, a deal falls through– these are all par for the course. They won’t kill you unless you let them.And in any case, competitors are not the biggest threat. Way more startups hose themselves than get crushed by competitors. There are a lot of ways to do it, but the three main ones are internal disputes, inertia, and ignoring users. Each is, by itself, enough to kill you. But if I had to pick the worst, it would be ignoring users. If you want a recipe for a startup that’s going to die, here it is: a couple of founders who have some great idea they know everyone is going to love, and that’s what they’re going to build, no matter what.
• Commitment Is a Self-Fulfilling Prophecy. I now have enough experience with startups to be able to say what the most important quality is in a startup founder, and it’s not what you might think. The most important quality in a startup founder is determination. Not intelligence– determination. [In fact, intelligence, like funding, can be counter-indicative of success.]Time after time VCs invest in startups founded by eminent professors. This may work in biotech, where a lot of startups simply commercialize existing research, but in software you want to invest in students, not professors. Microsoft, Yahoo, and Google were all founded by people who dropped out of school to do it. What students lack in experience they more than make up in dedication. You can lose quite a lot in the brains department and it won’t kill you. But lose even a little bit in the commitment department, and that will kill you very rapidly.
• There Is Always Room. So for all practical purposes, there is no limit to the number of startups. Startups make wealth, which means they make things people want, and if there’s a limit on the number of things people want, we are nowhere near it. I still don’t even have a flying car.
• Don’t Get Your Hopes Up. This is another one I’ve been repeating since long before Y Combinator. It was practically the corporate motto at Viaweb.Startup founders are naturally optimistic. They wouldn’t do it otherwise. But you should treat your optimism the way you’d treat the core of a nuclear reactor: as a source of power that’s also very dangerous. You have to build a shield around it, or it will fry you.The shielding of a reactor is not uniform; the reactor would be useless if it were. It’s pierced in a few places to let pipes in. An optimism shield has to be pierced too. I think the place to draw the line is between what you expect of yourself, and what you expect of other people. It’s ok to be optimistic about what you can do, but assume the worst about machines and other people.This is particularly necessary in a startup, because you tend to be pushing the limits of whatever you’re doing. So things don’t happen in the smooth, predictable way they do in the rest of the world. Things change suddenly, and usually for the worse.

  Shielding your optimism is nowhere more important than with deals. If your startup is doing a deal, just assume it’s not going to happen. The VCs who say they’re going to invest in you aren’t. The company that says they’re going to buy you isn’t. The big customer who wants to use your system in their whole company won’t. Then if things work out you can be pleasantly surprised.

  The reason I warn startups not to get their hopes up is not to save them from being disappointed when things fall through. It’s for a more practical reason: to prevent them from leaning their company against something that’s going to fall over, taking them with it.

• Speed, not Money. The way I’ve described it, starting a startup sounds pretty stressful. It is. When I talk to the founders of the companies we’ve funded, they all say the same thing: I knew it would be hard, but I didn’t realize it would be this hard.So why do it? It would be worth enduring a lot of pain and stress to do something grand or heroic, but just to make money? Is making money really that important?No, not really. It seems ridiculous to me when people take business too seriously. I regard making money as a boring errand to be got out of the way as soon as possible. There is nothing grand or heroic about starting a startup per se.So no, there’s nothing particularly grand about making money. That’s not what makes startups worth the trouble. What’s important about startups is the speed. By compressing the dull but necessary task of making a living into the smallest possible time, you show respect for life, and there is something grand about that.

I could probably tighten this up a lot further given some more time, but it’s definitely decreased in size from the 50 pages it started out as!

Links/Sources:

So 1st, definition of a startup: http://www.paulgraham.com/growth.html

Here are some notes from the book Lean Startup. Good stuff in here. http://sivers.org/book/LeanStartup

Value Hypotheses. http://thesquigglyline.com/2012/03/05/creating-and-testing-a-leanstartup-value-hypothesis-creating-and-testing-a-leanstartup-value-hypothesis/

Finally, some common mistakes. http://www.paulgraham.com/startuplessons.html