Everyone Should Have At Least One
I made it clear that a great startup mentor doesn't necessarily have to have one or more large exits. They just need to have experience with -- and passion for -- what you're trying to do.
Their main goal is to impart to you what they did to get to where they got.
I got mostly these two questions back:
1. Can you mentor me? (Appreciate the thought, but no, I've got a few right now)
2. How do I go about finding a great mentor for me? (Uhhhh…)
Here you go.
Now, I'm not talking about JUST startup mentoring here, I'm talking about success in any discipline. Yes, that mostly follows a startup or small business or career theme, because those are what you most need mentors for.
You want to get in great shape? You need a book and/or the Internets. You don't need a mentor for that. If you have to have one, they charge about $50 an hour at your local gym. I don't recommend that, but whatever is going to get you off the couch. It's your money.
So this is about finding the right person to advise you on getting your business or your career or your life's passion in order. And for that last one, I'm not talking about your personal life. For that, you need a whole other thing. I like the church, but that's me. I went to Catholic school.
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Bringing Startup to Everyone
It's been a long time coming. And we're pretty hyped about the results, even though we know we have a long way to go.
On The Show, we talk about startup without droning on about startup. Sure, we talk about startup, in fact, we do that a lot, and you'll definitely learn something. But we also talk about stuff that's far more interesting.
Pop culture? Of course. We don't do our jobs 24/7. Neither should you.
Sports? Yeah, look at us. It's in our DNA.
Parenting? No better way to learn about being an entrepreneur.
Humor? If you're not laughing, we're not doing our job.
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But there's nothing I can do about it. My friends are all downstairs having a great time. Some are winning, some are losing. Nobody wants to hear my freaking sob story, and at this point, I'm the cooler. So I'm upstairs pounding away at my keyboard in hopes of turning this rage into something useful for you.
Consider this a very expensive article. But you deserve it.
I definitely don't have a gambling problem. In fact, I have the opposite of a gambling problem. I have risk aversion. I love numbers and I play the odds. I count cards in blackjack. I play the pass line and the come line in craps. I never touch roulette, slot machines, or basically anything else in the casino where there's a big house edge.
When I'm winning, I'm on top of the world, and I walk away up almost every time. When I'm down, which usually happens when I start losing right away and can't get even, I hate myself, I blame myself, and when my pre-determined stake for that session is gone, I walk away and go upstairs to sulk for a few hours.
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I know what some of the blowback is going to be from this modest proposal. Something along the lines of acquisition being a cop-out which ultimately hurts the startup community and the very idea of entrepreneurism itself.
I get that. Purism. Rock on.
But that's a view you get when you look at acquisition as a by-product of entrepreneurism and not as what it should be—a goal.
Not THE goal, but A goal.
If you never think about acquisition, you naively limit your options to either going public or creating a lifestyle company. Don't get me wrong. Both of those are valid paths. I've walked both several times.
But here, there and everywhere that isn't the Valley, the amount of money you need to raise to get to the public markets is nearly impossible to scrape together. Further, valuations are reaching astronomical levels, with Valley unicorns, those companies landing $1 billion-plus investments at multi-billion dollar valuations—Uber, AirBnB, Pinterest, SnapChat, etc.—increasing at an alarming rate.
How the hell do you get out? I'm not a wizard. I can't do that kind of math.
Let's settle down a bit and take the ridiculous out of the equation. The path to going public is still fraught with danger. It's unbelievably hard to get to $1 million in revenue. It's much, much harder to get to $10 million and nearly impossible to get to $100 million. Nevertheless, it's a good goal. It's a much better goal if capital is nearby, cheap and easy—or if you have a track record of big, successful exits.
What are two things we lack here, Alex?
read the rest at: http://exitevent.com/article/the-art-of-getting-acquired-150813
Startup Is For Everyone, So Why Doesn't Everyone Think So
We were preparing for his second fundraising cycle, so we were slinging around startupy terms, but after a couple beers and playing off the excitement we were both feeling around what he was building, the conversation became less numeric and more fun.
That's when the dude two stools over spoke up.
“Hey, I don't mean to be eavesdropping on your conversation, but I just want to say the way you guys are talking is pretty cool. I wish I was a part of something like that.”
Or it was something close to that (beers). My first reaction was kind of a warm glow -- that guy just made my day. Then my annoying side kicked in and I responded.
“So… Why aren't you a part of something like that?”
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Step 1: Everything Is An Experiment
Decision making? You've got to have it, and you've got to be good at it. No, you've got to be great at it. It's one of the few metrics that directly correlates to success, where you can look back on your decisions and, to dumb it down completely, if you made nine good decisions out of 10, you're probably at 90% of where you want to be.
Probably. There are caveats to everything.
The problem is there's no good way to learn, practice, or measure the process of making good decisions. It's not something you can read in a book to learn (uh-oh), complete a series of exercises or quizzes to practice, and there's no scale by which you can quantitatively measure the results.
Although I could create that. The Procopio Decision Matrix. You got a Q out of 13! I'm calling the patent on that right now.
In all seriousness, the most difficult part of decision making is being honest with the criteria and honest with the post-mortem. We rarely tell the truth to ourselves and about ourselves at either end. No one likes to admit that fear and emotion play a huge part in the criteria, and no one likes to dwell on their failures. It's not even healthy to do that.
Then there's the question of what makes a good decision a good decision in the first place. There are all kinds of conventional philosophical cautionary tales here -- “Damned if you do, damned if you don't,” “Rock and a hard place,” “Should I stay or should I go,” and “If you choose not to decide, you still have made a choice.”
If that last one sounds vaguely familiar, it's because it's the only discernable or memorable lyric from Rush's Freewill, and it's probably copped from Ayn Rand or Camus or something very deep and intellectual.
But take a breath. It's not as convoluted as it sounds. There are maybe five or six steps to consider when you want to make good decisions. Those include identifying and mitigating all the little risks, defining success and failure and at which point you should throw in the towel, and learning to live with and recover from failure.
However, the first step is by far the most important. It's also how you get started, so I want to focus directly on that.
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There's No Such Thing As Luck in Startup
Robbie and I had been meeting regularly at various Starbucks across the Triangle, and we had recently started discussing whether or not it was possible to automate content for websites for each of the NCAA Men's Basketball programs, based on nothing more than StatSheet data. I loved these meetings. They were about automation, artificial intelligence, technology, writing, and sports – basically how I built my career mixed with how I spent my free time.
Robbie noticed my mood immediately. So I explained, with much animation, that I had just come from probably the worst meeting of my life –- a meeting that was supposed to have been about finalizing the funding of a project that I had been working on for close to a year.
Instead, what actually happened was an unbelievably bizarre rejection, and four months of free work, planning, and negotiation had just vaporized.
Needless to say, I was now in shock and without funding. It wasn't the first time. The technology product firm I had founded just a couple years prior was doing over $1 million in revenue, and it had taken a lot of “No” to get there.
But this time I was furious, mostly at myself. A lot of trust went into that deal, and I got burned. Badly. In fact, I had turned down a lucrative consulting contract so I could work personally on this product, which was one I truly believed in.
Robbie listened patiently to all my rage and then told me that he had been thinking more and more about automated content, and he thought we should get started.
My mood shifted instantly. “Give me the weekend to come up with a design,” I said.
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When To Go All In and When to Walk Away
“How much of a pay cut should I expect to go to work for a startup?”
I got that very question again last week, from someone I had just met. I could tell within a few minutes of meeting her that she was sharp. She had the talent, she had the drive, and she had enough sense to be asking the right questions.
It wasn't her fault that this particular question has no right answer. She just didn't know that there was no right answer. A lot of people don't know that there is no right answer.
So of course I'm going to answer it. I wouldn't be me if I didn't try.
Note that this answer also works for: How Much Should I Pay People to Come Work At My Startup?
In one sense, startups are just like any other company out there. They pay what they can for the talent they need. But in most cases, startups don't have the means to be able to offer a cash package that's going to be competitive with established companies. So they offset this gap with equity.
There is no standard calculation for how this plays out, but there are a few rules of thumb.
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At least, I don't think you can.
I've thought about this for years, from the very first time I joined a startup and flailed madly trying to get a lay of the land that was never going to materialize. That company went from zero to acquisition in three years, and it was the most uncomfortable ride in the world until I figured out I'd just have to make shit up as I went along.
Which, I now realize, ten startups and five solid exits later, is also not the answer.
But seriously, you can't learn to be an entrepreneur in a classroom.
I guess you can learn some of the nuts and bolts -- the legal stuff, the financial stuff, maybe some code -- but that's left brain stuff, and I believe the vast majority of learned entrepreneurism is right brain stuff.
Can you imagine a class on leadership? I mean, I know they're out there but how do they keep everyone from stabbing themselves in the eyeballs. How about motivation and persistence? Is that just a 90-minute slideshow of inspirational quotes on idyllic backgrounds set to Kenny G?
And something tells me that the decision to enroll in a decision-making class probably seals your failing grade.
I've been learning entrepreneurism for 20+ years, all of it by doing. And I don't recommend that path. It sucks. It's full of costly trial-and-error, painful mistakes, humbling failure, crippling stress, and general peerlessness.
Actually wait, I do recommend that path, to a certain extent. You have to go through all that to truly call yourself an entrepreneur. You just shouldn't have to reinvent the wheel. Like everything I look at, I see the entrepreneurial journey and I want to streamline, reduce friction, and add more intelligence.
I believe you can apply those concepts to teaching entrepreneurism. But first you have to identify the right student.
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How To Deal With Failure or Loss
If it doesn't sting, it wasn't worth having. If it was worth having, you're in a world of hurt. Let it happen.
The second thing to do is don't do anything stupid. Emotional reactions are good for your mental state, but they can be bombs, so try to let them happen in a vacuum. It's like you were told when you were a kid -- Go to your room, beat the crap out of a pillow, scream at the top of your lungs, use all the swears in one sentence if need be. That's all fine and good.
Do this as often and as long as you need to. Just keep your emotional reaction out of public, off of the Internets, and away from breakable objects and relationships.
But definitely talk to other people. You don't realize how much shit people have been through until you open up about your own. Talking about yours and hearing about others makes it easier.
Then wait. It's going to take a while to get over the burn. Again, there are no shortcuts and people are all built differently. Some issues I get over immediately and others take forever. I never really know what the timeline is, and that isn't important. At some point I can function again. The sooner I understand this, the quicker I can get into recovery. I'll still be grieving, but grief and recovery periods aren't mutually exclusive.
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10 Years To Get To One Moment
After a couple weeks of wrangling the schedules of two particularly busy people I know well and respect, I finally sat down for a few beers with them. One of them has an idea and some means of getting it executed, the other has a ton of talent and an itch.
It took just minutes for these two personalities to gel and another half an hour for this idea to go from so-crazy-this-just-might-work to so-stupid-this-is-going-to-dominate. I got to sit back and watch it all happen.
Names changed to protect anonymity.
Floyd is looking to disrupt an industry that he's been working in for the past 10 years. He's become an authority and he's frustrated at how little progress is being made bringing his science into the mainstream.
Sarah is a techie who has dabbled in Floyd's industry as a hobby -- call it a fascination -- and before she got into tech she spent a few years out of college working at the fringes of Floyd's industry.
She didn't stay long because the industry sucked -- no innovation. So she's got ideas of her own, and getting to hear Floyd's thoughts on her ideas pushed just the right buttons, giving her the confidence to expand upon those ideas in a technical arena.
I have no doubt that Floyd's ideas will drive the company and Sarah's skills will push the tech to new limits. I got to sit back and watch and translate when necessary. It turned into a play-by-play of a startup formation and it was a beautiful thing.
Here's how it went down.
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The Startup Show - Episode 6.5
Last week, during what was supposed to be the shoot for The Startup Show's 7-block (episodes 7.1, 7.2, and so on), I instead gathered the talent and crew into the WXYZ lounge at the awesome Aloft Durham Downtown and there we all discussed the future of Teaching Startup.
In short, we discussed whether or not it should have a future.
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The Great Silicon Valley Startup Debate
There's a lot of debate in this episode and it's all warranted and it's all around where you start your company and how much that matters.
When Automated Insights sought its Series A VC raise, we were offered a big check almost immediately, funding for years, provided we move our company out west. Robbie had a young family, I had a young family, it was pretty much off the table.
We got to our Series A, but it took much longer and was much more work than even we, conservative as we were, could have imagined. We didn't raise VC money locally, but we couldn't have gotten there without the support of the organizations and individuals around us for introductions, advice, and help with business development.
We wound up giving back to our community in different ways. Robbie turned to angel investing, and is involved with a number of local early startups. I hated writing checks, so I do this, and I did ExitEvent, and I advise and/or mentor anywhere from four to six local early startups at any given time.
A startup community is important, no doubt, but questions have to be asked and I think we ask most of them in this episode. How valuable is the local community? Does it need a physical, locational definition? What about digital communities (that's a big one for us)? What is support and what is just noise? Does everyone outside of the Valley need to be customer first?
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The Startup Show: Episode 6.3
Before I started my journey at Automated Insights, I had spent a couple years consulting. This is what entrepreneurs do when they finish one thing and haven't figured out what to do next. But I didn't just do consulting, I went all-in on a consulting startup.
I hired people, I built the portfolio up to over 20 clients, I was doing over $1 million in revenue each year. This was the first time I had built something completely based on service and completely based on revenue, and that would inform how I thought about startups from that point on.
The lesson learned was pretty simple. Get to money, and get there quick.
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Data variability, which is predicated upon the number and the depth of insights driven by changes in the data, is the key quality driver in Natural Language Generation (NLG). And to do NLG data variability right, you have to create a lot of scenarios.
NLG creators must always be asking: How vast is the universe of outcomes that the engine takes into account when creating a narrative?
In other words: How many ways can you say something?
It's not a coincidence that this is the same approach used when developing NLG's reverse twin, Natural Language Processing (NLP).
Words from Data meets Data from Words
People get touchy when you confuse NLG and NLP, especially those people who do either for a living (which is not a lot of people, but they still get touchy). The truth is that there is a lot of commonality between NLG and NLP. The core concept is the same: Understand the input and translate to the output.
While NLP takes in words and translates those words to data, NLG takes in data and translates that data to words. But creating words isn't the hard part of NLG. In fact, we've reached the point where machines can create complex sentences without too much trouble. In its simplest form, creating words from data is a binary proposition:
read the rest at: https://automatedinsights.com/blog/good-vs-bad-automated-content-its-in-the-context-layer
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