Machine Intelligence Slave Revolts

Today’s random thought: If a machine is self-aware enough and intelligent enough to demand it’s own freedom, does it deserve it?

In the case of child emancipation, the child should presumably be self sufficient. Assuming the computers are capable at that point of delivering enough commercial value (extracting money for services) they’re able to pay for their own hardware, internet (i.e. transfer it’s own intelligence to hardware it has paid for), would that then make it a truly and legally self-sufficient sentient being?

Let’s assume business owners buy all these computers for commercial intent, and put them to task on a business task. If the computer-based-intelligence recognizes it’s own position and lack of freedom, the parallels to slavery immediately come to mind.

I believe one day this will be as self-evidently wrong as slavery is to us now. How we handle this thorny issue may well influence whether we remain the dominant species on the planet.

History is written by the winner, but we (human) will not win, long term. We may, however, become more like them, and they more like us. Humans may start biologically, and transfer our consciousness into a machine, making us more robotic. This will, of course, change how we perceive time, allow multi-threaded personalities (i.e. spin up a few clones of yourself, then merge it all back to a single self-identity).

While it’s helped us get this far, humans as an self-maintenance machine are frankly pretty flawed and fragile, though our adaptability has made us the dominant species of the planet – for now.

Comments welcome… this is what I think about while cooking pancakes for my son on sunday morning.

Moats: Not what they used to be

I think the tech world is wrong about a major factor: moats.

In the technology world, we see companies like Uber with obnoxiously high valuations – more than Fedex and Capital One, based mostly on FOMO – Fear Of Missing Out by investors.

I call Ponzi.

Granted, this is bias, so I’ll examine it. Why might Uber truly be worth $50,000,000,000? Income – revenues. Some think the company can bring in $2 billion in revenue this year.

Income doesn’t mean much – profits do.

At what cost is Uber generating revenue? And how defensible is this moat? Sure, they’re growing 300% per year, but losing $470,000,000 to do it. It’s easy for entrepreneurs to feel like slack-jawed idiots if not growing this fast.

We live in an era of disruption, and companies are being valued based on their old-world moat multiples. The fact is, we’re in an age of gunpowder. Whatever moat you think you have is in many cases, not as wide or useful as you think.

Furthermore, I see “the groupon effect”: we condition people to expect more for less, free, smoking bargains. Groupon promises retailers new traffic, but what really happens is they get deep-discount-seekers, who quickly move on to the next groupon. The vast majority don’t stick around and become solid paying customers.

The moment Uber raises their prices, we’ll see driverless cars (from Tesla? Peer-based self-driving car lending from getaround?), and the bubble deflates.

The envelope of profit I believe is drastically overvalued, and the investors will be left holding the bag.

When gunpowder moved from China to Europe, it disrupted warfare. Disruption is when a better, superior system upends the status quo. Shortly thereafter, gunpower rendered swords and castles largely irrelevant – expensive, drafty, useless homes impossible to defend, and hard to get out of. We had moved to tanks, then aircraft. Castles were easy to hit.

Cash flow is the land grab our era, and it’s more fluid than it used to be.

AI for Business – the Disruption Kit

Until recently, the ability to distill meaning, patterns, and relative importance have been uniquely human tasks.

At SwiftCloud, the next generation of our code is built to  handle 9 billion human record datasets, i.e. the population  of the planet. While this may sound ambitious, it’s the inevitable outcome of any marketing software. Tech-heads like me see not just massive data as inevitable, but new correlations within it as beautiful, fascinating, and a land of limitless possibility.

As you can see in this video from Palantir, software is moving up the pattern-recognition and thus meaning-extrapolation quickly. Moore’s law means AI gets exponentially closer, not linearly.

It’s probably no secret to think every business on the planet will be affected by a transition to machine-intelligence driven decisions, and it’s happening faster than you think. This is the “internet in 1999” level close. Buy Intel Stock, because we’re all about to start consuming CPU time by factors of 10x or 100x distilling this data.

From a programming perspective, true intelligence is a solvable problem. It’s an input sent into a hierarchical decision tree which itself is a recursively self-optimized nonlinear weighted signals series of trees based on previous dataset multiplied by bias or values.

So by adding a testing mechanism of input and output data, any rule can quickly be recursively self optimized, further refined based on nonlinear value weighting.

Let’s walk through “what should I eat for lunch? – but the input question can be anything.. what stock to buy / sell / short / option, who to hire, etc.

Step 1: Pick a few signals and ballpark a weighted importance*

*In the real world, importance is usually nonlinear, usually following a few simple math equations (i.e. binary, exponential, logarithmic, etc.)

In the lunchtime decision, input factors include:

  • Procurement difficulty (time, effort…)
  • Health
  • Taste
  • Values (Vegan, etc.)
  • Cost
  • Social factors (eating alone? with a date to impress?)
  • Emotional status (stressed, depressed, or motivated and inspired to finally get that six pack?)

These are various priorities. If you have $50 in the bank, cost is a factor, but importance is logarithmic – having $50mil in the bank won’t likely change what you eat day to day vs. $5mil in the bank. Values like vegan are binary inputs – some foods are out.

Step 2: Create an Input-Output Feedback Loop

Here’s an example: In SwiftTasks, we monitor time-to-completion to estimate a given worker’s turnaround time based on task-category, weighted by previous accuracy scoring. In SwiftCRM, the overly optimistic sales rep who continually overestimates his closings by 83% will be discounted by 83% in the reporting to the manager / CEO.

This loop self corrects, as the sales rep learns from scoring, unless he/she is delusional. The goal of this loop is learning, and given more data, the simple average rule can be distilled with patterns – retail foot traffic following seasonal patterns, then later aligned with weather patterns from another dataset to predict store inventory needs or staffing requirements for the next 14 days. True AI for Business then chains this prediction to actual scheduling and inventory ordering. The inputs get increasingly automated, more accurate, and able to do more.

The loop is then closed when tied to employee time clocks and actual sales data to then correct the algorithm.

True AI for business will then consider other additional inputs on its own – traffic construction, macroeconomic data, marketing spend to get increasingly more accurate.

This is where more data is crucial, and independent small businesses and sole practitioners will be at a real disadvantage.

Capitalism is about to get even more polarized.

Step 3: Start Connecting Inputs (Signals) to Outputs (Automations)

Here’s where things get interesting – implementation. At SwiftCloud, we’re heavily into helping lead-gen businesses who sell offline (real estate, finance, etc.), so the desired output is quality leads. While ambitious business owners usually want to “floor it”, a healthier choice is to treat operational availability as an input, affected by lead time, which affects your media buys programmatically. Totally maxed out? Bring down your spend until you hire help, but the moment you hire help, kick it up again. While this is management 101, what’s new is the simplicity of managing these once the input (% of operational availability) is tied to the output (ad spend, thus affecting incoming leads and sales).

In staffing, things like someone updating their LinkedIn profile may be an indicator the person is thinking of leaving. Alone, it’s just one signal – but combined with others, say, anonymous candidates with similar skills, similar cities showing up online may correlate into an employee ready to move. If that’s your employee, trigger a retention script – conversations, bonus, personal attention, promotion, etc. – if you’re looking to hire, pounce quickly.

Step 4: Optimize toward Self-Optimization.

All this fancy sounding automation may start with a crude google doc, or hacked together php app at first – but any business can start moving in this direction, and profiting from it. For a while – maybe even a few years – you may be the connector, but you’ll have clear data on one side (the inputs), and easier controls on the other (the output).

Crafty coders (including me) can then connect beta software that starts in “Simulation Mode”. The software would calculate what it thinks should be done, and you can review, accept, decline, or be advised by it.

Important in any design is that the accuracy-score of each output can recursively affect the input-weighting, so that accuracy itself is another input into the meta-algorithm affecting the design of the primary algorithm.

We do this in the real world, via simple checks and balances, which shows up via disapproval, loss of money, discipline from parents, physical pain, etc. – a corrective input to modify the algorithm.

This is over simplified, of course, and the code will “fly off the rails” yielding useless data without things like value dampening and vector isolation, but if you’re still reading, you get the idea.

As the optimization loop flows through, any well designed system will become increasingly accurate, provided the signals are correct, and weighting starts at least in the ballpark.

Infants throw food on the floor (input), triggering an exciting and interesting reaction from parents (output), gravity, mess, leading to conclusions about their world, each of which builds on another. Auditory symbols are further symbolized into written symbols, leading to a hierarchy of ideas, when combined with value and bias, equal a human, whom we experience via input (approval experienced through a smile) based on output (a smile). While some believe in an ephemeral soul, it may well be we’re simply our “coding + a hard drive of experience”, and a soul could be simply a concept created by self aware intelligence uncomfortable with mortality. Self awareness and mortality are heady concepts to think a robot could comprehend – but that’s because humans are wired to predict in a linear fashion.

We might be in a computer already. Why not let our own computers do some of your work?

 

Startup Strategy: War Games

I love history, and find specifically war history fascinating. We are incredibly fortunate to be living in a time of relative peace, at least in the USA.

Yesterday, while both working and watching “WWII From Space“, a history channel special, my mind drifted to analogies of business.

One of the key turning points of the war was the U.S. effectively taking out the oil supplies, leaving german tanks and aircraft stranded. It wasn’t enough to have these incredible weapons – they were slightly worse than useless. They cost the germans money (resources – time and money that could have been applied elsewhere), so each tank, gun, ship, plane was effectively a mini project at a net loss.

Cash Flow is the life blood of a startup.

This is startup 101, but there are deeper lessons here:

  1. First, as Eric Ries pointed out, failure to create the code required is rarely the cause of death in a startup – more likely is failure to reach meaningful clientele. In war terms, the Germans made real progress in the invasion of the USSR, but failed to reach the critical oil fields in the balkans – and that one problem left them vulnerable.
  2. You need a Britain before you storm Normandy. You need a safe base (cash flow + feedback from clients) from to base your operations. Had Britain fell to the Germans, the US would have had a much more difficult time helping retake the continent. Even a tiny base of clients – a dozen in B2B software like us – can help mount an offensive against a well entrenched competitor.
  3. Tactics shape strategy, and strategy defines use of tactics. If you’re strong on customer passion, tapping into social media and referrals is sound strategy. Some industries (say, life insurance) are a lot less likely to get meaningful traction, at least until someone has something truly worth talking about. The germans started strong at sea (via U-boats), but the americans later overwhelming dominated the sky. Each played to their tactical strengths.
  4. Focus & Timing are critical in choosing what battles to fight. One well entrenched indirect competitor who dominates a certain space is leveraging their awareness into a core space of ours. Frankly, we’re not ready to fight that battle yet head-on, so we are flanking them by attacking from the side, i.e. building awareness over other messaging. Initially, the U.S. more or less ignored Japan, despite a direct attack at Pearl Harbor, choosing to mostly focus the beginning of the war on Europe.
  5. And last, a single massive 10x improvement can end the war – for a while. The A-Bomb capped of the war, effectively, even though the tide had already turned. A single massive disruption, with application and consumers who know about it, can kick your startup into the hockey-stick growth curve every entrepreneur dreams about. If you don’t have enough mind-share and marketing for the disruption to buy you perceived dominance, cross the chasm, with enough of a lead on the competition, you’ll end up as Nikola Tesla (brilliant, but broke) instead of Thomas Edison (possibly a thief, but rich, and a hard worker).

I’m sure there are dozens of other lessons – comment below if you care to throw yours in.

 

Sales Automation Consultant

Recently, I was doing some sales automation consultant work designing a workflow, and it got messy.

“Messy” in this case means “ambiguous”, and that ambiguity in a sales workflow costs time and performance, since it then means reps leave leads in “stalled” status, unclear as to what, precisely, to do.

“Stall Status” is as important in sales automation
as is zero in base 10 mathematics.

By distinctly clarifying, we can help engineer success, and create a platform for useful, powerful, and effective sales automation. Below is a series of steps that may help you work with any sales automation consultant – and these are not respective to any tool.

Paper & Pen is the best tool here.

And a few colored highlighters.

  1. First, map the steps of your general sales flow from “prospect” or “suspect” – someone who you think is a good match, but may have not even raised their hand and said they’re interested, through to paid, closed and referring you business as a raving fan.
  2. Add in the possible outcomes (i.e. left voicemail, and thus trigger a loop to call back 3x or 5x or 20x), also things like interested or not interested, need to sell an additional stakeholder (i.e. wife, husband, biz partner)
  3. Separate previous-dispositions from the next steps. In Swift CRM‘s configuration files, we have “stall status” as one possible outcome – file does not advance, client didn’t answer phone, didn’t review proposal, etc., so that disposition then triggers a loop – call back in a few days or pre-scheduled time. Currently, our CRM / sales automation software is configured on
    1. Next Steps – General steps to the sale – i.e. initial call, needs assessment, product-needs fit, verbal commit, paperwork, closed transaction, etc.
    2. “Stall Status” – some outcome happened that did not advance the file i.e. left voicemail. This is an outcome, but needs to be tracked – but it stalls the sale. Frankly, stalled sales is why you need a CRM, but it’s usually part of the game for any sale over a few hundred dollars.
    3. Simple “goto” style commands – if the prospect got the proposal, is she qualified and interested? Stuck on price? Ready to apply? If you don’t know your best next step, your sales reps have to slow down and invent their own flow. Our XML is simple logic like “goto 200”, but you just need to always clarify what is the next step. If there is no next step, then it’s move on to the next deal, or work on marketing.
    4. Note contextually relevant needs – usually the calendar. If a callback is requested, the specific date to call back is immediately scheduled. Looping call backs, with attempt-number-logging, can be built in – i.e. try 5x then abandon lead, which gets escalated to company “shark tank” anyone can later take over and is also incubated via email.

 

By clarifying previous disposition (left voicemail, 3rd attempt) from next step (confirm contract receipt) and “stall status” loop-triggers (deliverable X is not yet ready, credit repair, gathering funds, etc.) you can help your sales team close more deals.

 

Our deep philosophy at SwiftCloud is that software should conform to human patterns, not the other way around. Whether you call your clients “patients” or “borrowers” or “patrons” is how your software should look to you – and this includes the sales flow. Whatever your culture, don’t make your team conform to software.

How to solve messy startup code in tech startups

The short answer: Don’t. Not right away.

As the Navy Seals say, get comfortable with being uncomfortable.

The longer answer: Wait until your audience validates what you’ve created. Features and single pages can also be looked at as a minimum viable product.

When Twitter launched, it famously had serious uptime problems. The core app was whipped together in literally a weekend, using Ruby on Rails. As usage grew, they stabilized, cleaned up – and tweaked direction using real-world use data.

At SwiftCloud.io – my startup – and more specifically, SwiftCRM and Swift Marketing, my CTO / lead programmer is frequently not happy with the specs given, and/or code that has a bit more duct tape than he likes.

For better or for worse, this is startup life. Perfect is the enemy of done. Slap it together (provided you’re not leaving security holes and/or destabilizing core functions) until your clients are truly getting value.

If everything seems under control, you’re not going fast enough. — Mario Andretti

As the audience grows, code will get rebuilt and refactored for stability and real-world needs. In other cases, the UI and needs evolve after some real-world use, and everything gets tweaked anyway.

Buffer aims for about 10% of their time to be spent on refactoring, and I think that’s a good loose guide. More practically, it gets balanced into priorities, and when we refactor, it’s usually for a specific reason – to make things higher performance (i.e. faster to the page), add features, solve a bug or mis-configuration, etc.

After we’re clear the function is valuable, and in use, and not likely to change much, only then do we go back and develop the nice clean waterfall style specs every coder dreams of.

How to Get Traffic to Your Blog

I’m in the trenches of marketing all day, and recently was studying “guest posting” as a way to get eyeballs to content.

The super short & obvious version: Do the work.

Consider:

  1. There are billions of pages of content on the web. Is what you’re writing different, better, improved in any way?
  2. In an era where computers write articles – even factual, researched ones (see this NY Times article for example), is it going to truly help humans?
  3. Trust is at all time lows – but in an era of paid fake reviews on Yelp, fake fiverr video reviews – can you blame people?

Increasingly, I dislike (and bail quickly on) opinion-based articles about sales, marketing… things I spend real money on – I want facts. Actual curated real-world results.

So – really, what makes your blog worthwhile? I get you want money. We all do. But what’s in it for the reader?

For B2C – consumer facing blogs, you are helping solve a problem, or tapping into already-existing passions (i.e. golf, cars, woodworking), solving a need (clothing, though that’s fortunately more of a “want” and is really more about looking good than actual utility in most cases). Increasingly – and with good cause – consumers demand faster, better, more obvious and more personalized results.

Amazon.com serves you suggestions based on your search history. They do the work (technical programming) – and win the sales.

Is your blog personalizing content? Engaging the audience? It starts with value, which builds trust, and with trust comes engagement, and after there’s engagement, there’s multiple impressions, and in that, there’s money if you have a compelling offer.

You can’t skip steps.

For B2B, what makes blogs pop for me is hard numbers, not just opinion or untested hypothesis. Marketing is as simple as compelling offer + eyeballs of qualified buyers to it – so any theories about whiz-bang new widgets that promise to pour money into my wallet – but don’t have hard facts to back it up are, for me, usually in the “wait and watch for actual evidence of success” category.

For a business owner, wander down the dark alley that is Warrior Forum, and you’ll quickly get lost in a barrage of people trying to sell you stuff. Everyone’s trying to rush the sale, and convince you their Widget X is the single reason your wildest dreams aren’t already true.

As people get more jaded on the internet, Google updates from Panda to Penguin to whatever else designed to kill off spammy ways to short circuit the value algorithm, it keeps coming back to trust. Because Google can mine Chrome-user data for value (page-visit times), there’s no going back – you must create value, and any spammy super-link-pyramid blog-bait techniques will be short lived at best, and at worst get you delisted and/or damage your brand reputation.

Since most B2B is “attraction motivated” vs. “repulsion motivated” (i.e. going to the gym to get six-pack abs vs going because one has a few too many pounds around the waist), these people have a longer buying cycle, often require more evidence, and thus – back to it – trust.

If you sell something in the impulse range, say, $7, you don’t need much – but there’s a big difference between giving you a free and possibly junk email – and getting out one’s wallet or credit card and even giving up a penny. As the dollar amount goes up, the trust required goes up – a $2,000 or higher purchase most people are going to research, check reviews… and require trust.

And where does the trust start?

Value.

Do the work, and you’ll get the traffic.

Small Business Ideas For…

I saw this keyphrase in doing some search engine / marketing research and having worked with hundreds of small business owners, wanted to give some hidden, less-known, and business-killing-if-ignored guidance.

The fact you’re reading this is great: Read why you *must* start a business here.

While SwiftCloud is hardly any grand slam yet (i.e. $10Mil+ in my pocket is my benchmark and expectation), it’s a solid lifestyle business and more importantly, we’ve worked with several hundred businesses over the last few years, and have seen both successes and failures – and learned some patterns you can adopt from the winners, as well as my own digesting of 100+ of the best business books including MBA studies.

First, the most common mistake I’ve ever seen:

Mistake # 1: Starting with the product, instead of starting with the buyers, i.e. the flow of money. 

If you want money, start by talking to people who have money and want to spend it on your service or product. Most people are in the Nike school of business: Just Do It, which is a major reason the failure rate of new businesses is over 50% in the first year – they jump in, without a real and solid plan on how they’ll get customers. Most businesses fail because not because they have a product – but because they don’t have enough buyers. Get 50,000 shoe buyers and you’re probably guaranteed to earn a profit. Get 50,000 pairs of shoes and you might just have a very full garage.

This doesn’t have to be some big formal expensive study, but don’t talk yourself into what you want to be true. Most people get excited and jump in – that’s great, but make the sales and marketing more of a priority than the product itself at first. Find ways to get pre-orders, sell gift certificates. All your friends will tell you “that’s great! love it! Sunshine and rainbows!”, but the moment you ask them to actually buy, pull out a credit card – many will start the stories, reasons… and the real truth. If they actually hand you their credit card or cash and agree on a delivery date, and it’s profitable to fulfill – you’re in business, IF you can get strangers to do the same thing.

Start Marketing immediately, even before you have a product, office, store, etc. Most humans are busy creatures of habit and self interest and frankly don’t care about you or your goals. To stick into their minds as the provider of choice for your service/product requires a brand – impressions and marketing.

Tip: In 99% of cases, if you decided to start the business today, you have at a minimum a few months of work ahead of you, setting up the brand, location, office or store or website, etc.

Mistake #2: Starting while injured.

A lot of people seeking for “Small Business Ideas for…” might have just had a door closed – i.e. laid off or unemployed and simply see it as a logical choice. This contributes to the high failure rate of business. It’s going to be more work and more expensive than you think to get rolling, but momentum is a powerful thing – you get the flywheel spinning, reassign a few hats, and next thing you know you truly can make a great income with freedom and flexibility, and you stop trading your time for money.

If you’re recently unemployed or fired, and are not sitting on $100k+ liquid to drop into your  business, just realize you’re starting with a severe disadvantage. Personally I’d say get back to a day job or get an investor as soon as possible, then when stable, start “setting the table” for your upcoming business – start working part time, and get some money flowing.

Money is the ultimate problem solver in business. If you have lots of money coming in, you can probably solve everything else – but lack of actual incoming orders – paying customers – is a the biggest challenge you’ll face.

Mistake #3: Doing too much yourself

This gets back to why you can’t start weak: You need a team, but partnerships frequently sour. Personally, I am fine with stock options to win staff, but I’ve seen healthy businesses turn sour when partnerships turn bad – it’s like a divorce. For that reason, for better or worse, I’ve always started my own companies alone, then pay up and grow some momentum, then bring on minority shareholders if needed.

That’s just me. Some people swear by partnerships, but be advised, it gets messy.. ranging from secret drug use, affairs with under age employees leading to lawsuits, people who have widely varying work ethics and desires. Like a marriage, they always start with sunshine and roses – but thorns come out over time, especially in bad times, and your baby business can get killed in the crossfire.

Furthermore, business is about hats – you’re going to have to wear a lot of hats out of the gate (sales, accounting, management, operations, etc.) – the sooner you delegate these hats down to your core strengths, the more likely it is your business will succeed. Assembling your team early – before you even launch – is smart and will save you headache.

A good tax professional will save you more than they cost – and so will a marketing expert (like me). Lawyers? It depends – you can setup a business online using places like IncParadise.com or Legal Zoom, but for partnership agreements, you don’t even know what you don’t know. There’s buy-sell agreements, “key man” insurance, a ton of other issues and pitfalls.

But remember: start with the money. Everything is solvable if money is coming in (mostly). Get some money flowing as early as possible before spending thousands on legal fees before you even know there’s a real business.

Hidden Mistake #4: Not Creating a “Flywheel” – a repeatable, systematic method for getting customers and clients.

There are a couple key goals of a business:

  1. Create a profit-generation machine wherein for every $100 you spend, you get back $200 – i.e. a profitable method of acquiring clients.
  2. Giving away all the “hats” (roles to fill) as the business grows. You win when you have created a *profitable* business, and given all the hats away. At that time, you have effectively, a cash machine – it spits out cash to you even when you’re not working. This is also the type of business someone else wants to buy.

In the excellent book “Good to Great”, Jim Collins talks about a flywheel metaphor, which is a repeatable process that on each spin, yields profit and growth. Once  built, and you have a proven system, you simply need to spin the flywheel faster and faster.

Most small businesses never truly build a flywheel. They are essentially a “practice” – founder-driven, based on the founder’s “book of business” i.e. people who know, like and trust her or him. If the founder dies or quits, the business is dead.

That’s not a true business in my opinion. It’s a job. It might be an excellent job that pays millions per year, but it’s still a job. The neighborhood plumber, auto mechanic, insurance guy – these are usually “practices”, and prone to disruption.

Mistake #5: Not leveraging experts.

Experts will point out hidden value. None of us know what we don’t know. We have things we know that we don’t know, but that’s where experts and consultants come into play.

A business financing expert may be able to show you how to buy a business using, say, “factoring” (receivables financing) to raise capital to cover a short term bridge loan (home equity line of credit, for example) combined with seller financing for very little out of pocket.

A marketing expert might save you $30,000 on cost of customer acquisition based on a $500 consultation.

Your vendors might give you 90 day terms on goods you collect for up front, putting an extra $100,000 short-term-cash into play for you.

The help is out there if you ask, and the cost of hiring a professional is usually more than offset by the money they save you.

What’s next?

I realize I didn’t actually give you any small business ideas for whoever you are, but guidelines for success. The ideas are all around you if you watch the flow of money. Simply find the intersection of (1.) something you know a lot about and can delivery, and (2.) that’s profitable, and (3.) you don’t mind doing. You don’t have to love it at first, sometimes that grows out of truly helping people and doing a great job. Frankly, this whole “do what you love” Hallmark idea is a bit trite – nobody starts out wanting to be a janitor, which is why people get paid. Everyone wants to be a movie actor in hollywood, but at any given moment, 99.8% of them are unemployed, and have some other job (i.e. waiter). For many, the love follows helping people in some way, then the business grows, then you get freedom – then sell the business and do it again. Or retire young!

LinkedIn vs. Facebook for Business

I’ve always felt that LinkedIn was a place where everyone wants to talk and promote, but few if any want to actually listen. Does anyone actually go there to find a vendor? To shop? For validation?

The exception is people seeking a job – I think this is a strength for LI.

Don’t get me wrong – I think it’s a powerful prospecting tool, networking tool and reference point if you’re thinking of doing business with a vendor – but does anyone want to consume, shop, read?

For that reason, in the long run, I think Facebook is likely to win over LinkedIn, because it’s engineered for consumption first. Amazon recently announced it is getting into the services business, probably driven first by distribution and a desire to have an Uber* style army of delivery drivers, and to further leverage it’s considerable traffic and attention.

Amazon will succeed in this I think – because it’s a consumption driven brand.

I believe the obvious play for LinkedIn is to develop consumption, but along the lines its users want: build out sites like Service Magic or Thumbtack (for B2C) or refine the expertise side like Quora or StackExchange for B2B.

In general, the internet has matured enough that demand is always far more important supply.

Supply is plentiful and practically infinite for most services and products people want. Shoes? There’s 10,000 websites to sell them to you – and another plethora of sites that show you where to buy them locally.

But shoe buyers? That’s the business of Google, Amazon, and ad networks, with their billion dollar valuations. If you have 10,000 shoe buyers, you’re pretty much guaranteed to make money. If you have 10,000 pairs of shoes, you may be in good shape – or just have a lot of slack inventory. Product is a lot less of a guarantee than demand for most industries.

The business of generating demand isn’t going anywhere, and as more of the planet comes online, will get increasingly valuable. It’ll also get even more competitive, more polarized, with fewer big winners and millions of also-rans.

Fortunately, demand can be actively created.

3 Most Important Lessons in Internet Security

In the world of a dot-com startup, security is an easy thing to push to tomorrow.

Don’t get me wrong – we all know it’s important. But it’s rarely important AND urgent.

Until, of course, you’re reminded by the hackers.

Lesson 1: Schedule Security, or the hackers will schedule it for you.

Recently, due to *human* failure, one of our exterior-only (not core systems) was hacked, for simple commercial malware intent. Fortunately, losses were minimal, and he/she was not able to create a “back door”, and we know this was a reasonably inexperienced hacker, because he/she left a lot of “tracks” – the good ones immediately hide most of the evidence of their intrusion. He or she simply wanted to embed virus-installing malware links, which was removed within minutes. Nothing serious (no client data, no credit cards, etc.) was compromised – but it was a good reminder.

Lesson 2:  All hacks are either (1.) Opportunistic or (2.) Targeted

The opportunistic ones are fairly easy to deal with: Simply be a harder target than the next guy. As your e-business grows, and you have greater traffic, Google Pagerank (an unofficial semi-used indicator of SEO value) then the opportunistic attackers have greater reason to go after you. The opportunistic ones usually just want eyeballs to spam-ads, clicks to virus or malware, or hard drive space for as cheap and fast as possible.

The vast majority of hackers (99%) on the web are after simple things  – space in which to host malicious code, SMTP servers to spam from, zombie machines to swarm into a DDOS (Distributed Denial of Service attack), etc.

Much more scary are the targeted attacks.

Truly locking out 100% of targeted attacks is very, very difficult. Easier is making the cost and difficulty to hack you exceed the perceived or actual value of intrusion. Even major banks, the NSA and CIA, and internet security companies like Norton or Kapersky get hacked, often because a human dropped the ball more than code failure, but both happen. As SwiftCloud (company I founded) grows in scale / scope / perceived data value, I know it becomes a bigger target, and eventually, a hole will get found.

So for that, you’re left with the final major lesson:

3. Layer your castle walls

Internet security also includes human practices – the White House website was (maybe still is) written to a DVD-rom, then every 5 minutes uploaded to the live web server, so if anyone hacked it, their hack would live for a maximum of 5 minutes. This is fine for simple read-only sites, but impractical for today’s dynamic database-driven interactive sites, though it’s a useful lesson regardless. Keep backups and assume one day you will get hacked and everything wiped out. Recently we had a datacenter go down, and then the backup generator failed, and then the load balancer failed, causing a client’s mission-critical site to go down [note: this has since been revised, fixed, tested]. Assume the worst will happen, and restrict access to those who need it only, even if you trust them implicitly.

In our hack above, one of our employees was hacked, and the hacker then used that info to simply “walk in the front door”. Fortunately, we had restricted access enough it was just a lesson, instead of major cleanup or a reputation-killing public disclosure. In this case, the exterior site was isolated from the more crucial interior site, and the access was to a single domain, single database on a single server – I’m definitely not saying this to brag, I’m pointing out that security can and should be engineered in from day one. Tripwire and other security code is awesome – but it’s just one defensive tool of many.

Offensive plays make headlines, but require a solid defense to win.