A summary of Paul Graham’s 18 mistakes that kill startups

Those of you that subscribe to my startup newsletter are familiar with my habit of summarizing the best long-form startup articles.

PG has arguably the most comprehensive, well-written set of essays for inexperienced entrepreneurs. Many of his lessons will naturally be acquired when you start companies, because in starting companies you will make mistakes and from mistakes you will learn these lessons, but if you want to avoid at least some of those mistakes, or make different ones instead, you should be reading his essays.

This essay, The 18 Mistakes That Kill Startups, is one of the best and it’s included in the startup newsletter. (subscribe here)

Like most of my blog posts, I write it in part to share advice with readers and in part to remind myself of what’s important.

This sums up the essay:

In a sense there’s just one mistake that kills startups: not making something users want. If you make something users want, you’ll probably be fine, whatever else you do or don’t do. […] So really this is a list of 18 things that cause startups not to make something users want. Nearly all failure funnels through that.

Here are the 18 mistakes:

1. Single Founder – all of the great technology companies had 2 founders (Apple, Microsoft, Google). Although I would argue Mark Zuckerberg and Jeff Bezos have come closest to breaking this rule

2. Bad Location – if you’re serious, be in the Valley (this includes SF)

3. Marginal Niche – avoid small markets, and focus on big problems in big markets

4. Derivative Idea – don’t take an existing success and tweak it in a small way. I think a lot of the “Airbnb for X” or “Heroku for Y” have this problem, too

5. Obstinacy – your original business plan is probably wrong, but it’s important not to change too quickly, either

6. Hiring Bad Programmers – self-explanatory; implied: starting a company as a business founder, without a strong technical cofounder

7. Choosing the Wrong Platform – platforms include Windows, Apple’s App Store, and Facebook; choose carefully since they’re your partner, whether you like it or not

8. Slowness in Launching – get your product into users’ hands as soon as you have a “quantum of utility”, then iterate quickly

9. Launching Too Early – less important than #8, but if you launch too early, you risk hurting your reputation

10. Having No Specific User in Mind – can you envision EXACTLY what your ideal user looks like, how she behaves, and what she wears?

11. Raising Too Little Money – raise enough to get to the next step, and then 50-100% more for buffer

12. Spending Too Much – happens when you hire too many people, and/or pay too much salary (give equity instead)

13. Raising Too Much Money – when this happens, you’re expected to spend it quickly, and your company becomes less nimble

14. Poor Investor Management – ignore them, and they’ll be upset; heavily involve them, and they may wind up calling the shots

15. Sacrificing Users to (Supposed) Profit – we were guilty of this: too much emphasis on finding a business model and earning revenue, before we had a product that users wanted

16. Not Wanting to Get Your Hands Dirty – the best founders do whatever’s necessary to grow the company, in particular understanding their users and acquiring more of them

17. Fights Between Founders – most unresolvable disputes are due to differences between people, not due to the particulars of a situation, so choose your cofounder(s) carefully

18. A Half-Hearted Effort – quit your day job, and be obsessed with your startup

Will automation render human workers obsolete? Daniel Akst explains

Dilbert on automationY’all know I’m a big fan of reading stuff and then summarizing it. I’ve been doing CliffsNotes for books with my 1-page cheatsheets, and for startup articles with 1-read-a-day.

Wilson Quarterly is a new find. Their articles are long (3,000+ words), well-researched, and written in a “scholarly journalist” voice like The Economist.

Daniel Akst writes the weekly R&D column for WSJ. His essay, Automation Anxiety, is perfectly timed with some questions on my mind, such as:

  • As U.S. jobs are increasingly concentrated in technology and knowledge, what happens to workers who are left behind?
  • How will the U.S. maintain its global leadership, as we increasingly see signs of strain in its economy, its cultural influence, and its moral authority?
  • What will the “job of the future” look like?
  • How many of today’s jobs will be automated, and in what way?

My bias is to write down insights that are new to me, as opposed to what I think will be most interesting to the widest swath of readers. Treat it like a Costco free sample: if you enjoy it, go and read the whole thing.

CliffsNotes for Automation Anxiety by Daniel Akst

His main question:

But now, with the advent of machines that are infinitely more intelligent and powerful than most people could have imagined a century ago, has the day finally come when technology will leave millions of us permanently displaced?

A big part of his thesis:

Notice Bloom’s insights: first, that technology could obviate arduous manual labor; second, that this would cost somebody a job; and third, that it would also create a job, but for a different person altogether.

Some stats

  • US shed 6.3mm manufacturing jobs between 1990 and 2010
  • Unemployment is at 7.5%, 4 years after our “Great Recession”

Akst goes on to compare our situation today to similar automation and job market fears in the 1950s and 1960s (the Kennedy, LBJ eras). Unemployment was high (hitting 7% at one point)

The prominent economist Robert Heilbroner argued that rapid technological change had supercharged productivity in agriculture and manufacturing, and now threatened “a whole new group of skills—the sorting, filing, checking, calculating, remembering, comparing, okaying skills—that are the special preserve of the office worker.”

And here we get to the second piece of Akst’s argument:

some of its most important effects were felt not in the economic realm but in the arena of social change

In the 1950s and 60s, we mistakenly assumed that there was a ceiling to demand for goods and services (hah!):

Although the principle that human wants are insatiable is enshrined in every introductory economics course, it was somehow forgotten by intellectuals who themselves probably weren’t very materialistic, and who might only have been dimly aware of the great slouching beasts of retailing—the new shopping malls—going up on the edge of town

Interestingly, there was also concern that – with consistently shorter working days – we’d hit a point where we hardly worked at all. What would we do with the leisure time??

In the first half of the 20th century, the number of hours worked per week had shrunk by a quarter for the average worker, and in 1967 the futurist Herman Kahn declared that this trend would continue, predicting a four-day work week—and 13 weeks of vacation.

Some writers got it right:

Simon wrote, “The world’s problems in this generation and the next are problems of scarcity, not of intolerable abundance. The bogeyman of automation consumes worrying capacity that should be saved for real problems—like population, poverty, the Bomb, and our own neuroses.”

The people most affected were middle-aged, working class men (as they are today):

The economists Michael Greenstone and Adam Looney found that from 1969 to 2009, the median earnings of men ages 25 to 64 dropped by 28 percent after inflation. For those without a high school diploma, the drop was 66 percent. This is to say nothing of lost pensions and health insurance.

Why such declines? #1, entrance of women and immigrants into the workforce, #2, increased global trade, #3, rising use of technology

In fact, the proportion of men who were not in the formal labor force tripled from 1960 to 2009, to a remarkable 18 percent

Sociologist Daniel Bell was particularly prescient:

Bell acknowledged that there would be disruptions. And he was accurate about their nature, writing that “many workers, particularly older ones, may find it difficult ever again to find suitable jobs. It is also likely that small geographical pockets of the United States may find themselves becoming ‘depressed areas’ as old industries fade or are moved away.”

Bell also foretold the social impact of such changes:

“creating a new salariat instead of a proletariat, as automated processes reduce[d] the number of industrial workers required.” He accurately foresaw a world in which “muscular fatigue [would be] replaced by mental tension”

Like some thinkers in the 50s and 60s, Akst believes that the big problem is (re)distribution:

“The economy of abundance can sustain all citizens in comfort and economic security whether or not they engage in what is commonly reckoned as work,” the committee continued, arguing for “an unqualified commitment to provide every individual and every family with an adequate income as a matter of right.”

Why? Because automation presents us with a windfall, and the hard question is how it’s shared:

This doesn’t mean we must embrace the utopianism of the Triple Revolution manifesto or return to the despised system of open-ended welfare abolished during the Clinton years. But inevitably, if only to maintain social peace, it will mean a movement toward some of the universal programs—medical coverage, long-term care insurance, low-cost access to higher education—that have helped other advanced countries shelter their work forces from economic shocks better than the United States has, and control costs while they’re at it.

And a couple insightful comments:

It seems to me that unless we can invent a new kind of labour – post-physical, post-mental – we will have to come up with a new kind of wealth creation mechanism that allows for 1) the use of fewer workers and 2) a fair distribution of the wealth created. – idespair

Akst devotes an anemic, apologetic two paragraphs to the central fact of his essay – the adaptation required this time is fundamentally political rather than technological. And to most eyes that political solution can hardly be described as anything but radical. – civisisus

Thanks for reading, folks. Here’s the full article.

A collection of shiny objects

I have a problem. I collect trivia like raccoons collect shiny objects.

I store this collection in a notebook called “Random facts and learnings”.

It’s inspired by Steven Johnson’s Spark File:

I’ve been maintaining a single document where I keep all my hunches: ideas for articles, speeches, software features, startups, ways of framing a chapter I know I’m going to write, even whole books. I now keep it as a Google document so I can update it from wherever I happen to be. There’s no organizing principle to it, no taxonomy–just a chronological list of semi-random ideas that I’ve managed to capture before I forgot them. I call it the spark file.

Sometimes you start a new thing, and after awhile, you stop that new thing. A fad diet, a new friend, a Kindle book.

Sometimes you start a new thing, and you keep doing it. In fact, you find it hard to stop.

That’s the story of “Random facts and learnings”. It’s my spark file for trivia. When I read a statistic, a study, or an acronym, and think to myself, “I’d like to remember this, but probably won’t”, into the spark file it goes. My shiny collection is now ~40 pages.

Here are 5 items that I hope will catch your eye. I’ll attempt to curate and share more each month.

1. Mountain dew was originally slang for moonshine

2. Cryptophasia is the tendency for twins to communicate in their own private language. Like so.

3. Getting married causes a 2-year increase in happiness. Once a married couple has children, happiness steadily declines until the children leave the house, then marriage happiness begins to increase again

4. We have a functional and complex neural network or ‘brain’ in the gut, called the enteric brain, and fear is mediated by this brain. The # of neurons in our gut is equivalent to that of a cat’s!

5. Where does “raining cats and dogs” come from? One interpretation: in the old days, when it rained really hard, they’d find dead dogs and cats in the storm waters

Do you collect trivia, too? I’d love to hear from you. Thanks as always.

The secrets of Reed Hastings and Netflix culture

Recent share price swings aside, Netflix is among the most innovative companies of the last 2 decades.

They’re also incredibly transparent, to our benefit.

I first read this presentation 4 years ago. I remember thinking, “holy shit”, and immediately forwarding to the shopkick team.

I’ve re-read it 3 or 4 times. Still not enough.

It’s now part of 1-Read-A-Day.

Here are my takeaways

I bias towards the unusual (since we all know the old yarns of “A players attract other A players”, “employees are your #1 asset”, blah yada etc)

1. A company’s REAL values are shown by who’s rewarded, who’s promoted, and who’s fired (slide 6)

2. “Adequate performance gets a generous severance package” (slide 22, reminds me a little of Zappos’ $1K to quit) [http://blogs.hbr.org/taylor/2008/05/why_zappos_pays_new_employees.html]

3. The Keeper Test: “Which of my people, if they told me they were leaving, for a similar job at a peer company, would I fight hard to keep at Netflix?” (slide 25)

4. “Brilliant jerks” are avoided – hurts effective teamwork (slide 35)

5. Growth –> More complexity –> More processes –> Less talent –> Long-term irrelevance (slide 52)

6. Netflix’s solution to above? Increase talent density to offset rising complexity. Do this by hiring only “high performance people” and giving them more freedom (slide 54)

7. Example: no vacation policy; take what you want (now a startup-world standard) (slide 69)

8. Departments are “highly aligned” (agree on goals), and “loosely coupled” (freedom in implementation) (slide 93)

9. Pay top of market, because Netflix only wants top people – top of market is re-defined with each hire, each performance review (slide 96)

10. Comp is salary-focused. Employees can choose to trade salary for stock options (109)

11. Everyone gets $10K in benefits, from receptionist to CEO (slide 109) – this was published in 2009

12. All options are fully vested – employees stay for the right reasons

13. For promotion, new job must be “big enough”, and you must be a superstar in your current role

That’s it, folks!

Don’t watch the ball, watch the seams

Thanks to http://www.odt.co.nz/sport/tennis/138357/tennis-federer-beats-nadal-atp-finalsIn tennis, we’re told to watch the ball.

My coach used to say, “follow the ball from their racquet to yours,” pointing out that “Sampras, Agassi…they’re always looking at the ball, even after it makes contact.”

We’re supposed to focus on that green dot like a cat on a laser pointer.

On a recent drive to LA, I was listening to The Inner Game of Tennis. Think Zen and the Art of Motorcycle Maintenance, but replace “Zen” with “Inner Game”, and “Art of Motorcycle Maintenance” with “Tennis.”

Really, both could be called “Life wisdom revealed in the pursuit of a hobby”.

In The Inner Game, author W. Timothy Galloway makes a point that I paraphrase thusly:

“Don’t watch the ball…watch the seams.

Bam!

It’s the Inception of life advice.

On Level 1 (the reality level), Galloway is instructing us to watch the ball so closely that we see its seams.

On Level 2 (the rainy-city/van-chase level), Galloway is really telling us to pay attention to detail. If you’re truly watching the ball, you’ll notice it’s not just a fuzzy green object. It has a logo. It turns a disheveled, patchy yellow with use. And it has seams.

On Level 3 (the hotel level) – and that’s as far as this extended metaphor goes – it’s all about pushing our limits. Don’t watch the ball, watch the seams. Don’t make a 3, hit a swish. Don’t aim for a million dollars, go for a billion. Now THAT’S cool.

It brings to mind a Bruce Lee quote, one of my favorites.

There are no limits. There are plateaus, but you must not stay there, you must go beyond them. If it kills you, it kills you. A man must constantly exceed his level.

Are you watching the seams in your life?