Sci-Fi, Logic, and the Future of Work

I’ve been working with AI systems across workflows, pushing the boundaries to see where the gears grind. During this process, a series of moronic abstract thoughts began to coalesce into something one could call a theory. If one got extremely drunk and covered one eye, that is.

Anytime I brain fart a theory into existence, I design a test. My test for this theory was collaborating with AI to write a Sci-Fi novel, ‘Project WTF’. I love to write, not that I care if you read it; I think of it more as taking my logic and imagination to the gym.

Sci-Fi provides a canvas for abstraction. It allows you to discuss real-world issues without the human emotional response system blocking out the message. If you read Dune, you accidentally learned a little history of western oppression of the Middle East for the purpose of resource exploitation. The book tracked for me, having been assigned as one of Uncle Sam’s oil mercenaries in the region many moons ago.

The Synthesis Loop

In this workflow, I am not "prompting" a machine to do my work; I am architecting intent.

The Source: I provide the raw resource, my cynical observations of human systems.

The Refiner: The system provides a ‘fictional skin,’ taking those systemic critiques and abstracting them into world-building mechanics.

The Plot Test: The system creates ground rules for the world. It then tests my concepts, stories, and characters against those rules. If you’ve played D&D, this all rang a bell.

The Result: 'Strategic distance’, making a harsh truth palatable through fiction without losing its teeth.

Why Do You Care?

Let's abstract the process:

Knowledge Worker (The Source): Provides the intent (desired outcome) along with context and constraints.

The AI System (The Refiner): Produces a framework for collaboration designed for an outcome.

The Result: The knowledge worker and AI system become the ‘Engineers of an Outcome’.

Moving Beyond Platitudes

"The future is not something we enter. The future is something we create." - Leonard I. Sweet

We're at a unique point where the incentive structure, the technology, and the goal of building the future are all aligned. It’s in our best interest, it’s best for society, and it will be highly profitable. We should be using AI as a collaborator with empowered humans to unlock the trapped potential in the people we already employ.

Knowledge work has become an assembly line, move an endless pile of similar problems from one side of the desk to the other. No wonder you don't get 100% of what your people have to give. We don’t need to replace them. We need to get out of their way.

The future won’t be led by a spreadsheet in a boardroom. That spreadsheet is designed to account for decades of bloat and inefficiency. The future will be driven by those who reinvent the process by using the AI tools they’ve been handed the way we’ve always used tools: in our own hands, to create a better output.

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'Why' Has Become a Curse Word

Our Human Superpower is Now a Curse Word

I’m an ornery hermit. I live in a log house miles from the nearest human and further from a cell signal. I don’t interact with other apes in person more than twice a month if I get my druthers. I do it for their sake, not mine. My personality is abrasive; nobody should be subjected to it.

Like a child, I ask "why" about everything lacking an explanation. Unlike a dog, I refuse to memorize the thoughts you want me to just because you said so. I won't accept "I don't know" or "that's just how it is." If a process or system doesn't make sense at this exact point on the timeline, it’s unacceptable.

We’re squandering our greatest human gift by beating that curiosity out of our emerging adults. We replace the "why" with an "education" system built on the "memorize then test" pattern of indoctrination.

The Tamara Trajectory

Imagine we didn't do that. Imagine you fostered that curiosity in a child, let's call her Tamara. You skip the indoctrination and focus on the scientific method and tools for parsing objective reality from a world of noise.

Fast forward 30 years: Tamara is the CEO of a Fortune 1000 BioTech company.

Day One: She looks at the org chart. It makes no sense.
The Question: "Why do we organize this way?"
The Answer: Nobody has one.
The Realization: Every industry uses the same command-and-control hierarchy: banks, oil, manufacturing. That's not optimization, that's lack of innovation and imagination.

Tamara realizes that businesses in 2026 are still running in organizational silos designed for the assembly line of the Industrial Revolution. We took a non-optimized factory floor management style and slapped it over knowledge work without ever asking why. Then we smashed that 'follow button' yo! (yes, our species is sad).

Because Tamara still has her "why," she can actually fix the problem instead of just managing the symptoms. Be like Tamara. Don't be a dog. Ask why.

Within our portfolio of companies, we're taking Tamara's lead. We're asking why, then asking again and again, until we find the right problems to solve.

Right now, we’re focused on why Al projects fail 80% of the time despite billions in investment. The answer isn't "better AI." It’s a "dirty data" problem that everyone is trying to ignore. I f'ng love 'why'.

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Waiting on the $500B Ad Economy Bubble Bust


Wall Street’s primary export is short-term euphoria masking long-term systemic rot. Right now, they’re propping up the entire U.S. economy on a house of cards built from consumer data mining, behavioral manipulation, and hyper-targeted advertising. It’s a $500B market fueled by the belief that if you track everything about everyone, you can sell them anything.

There’s just one glaring flaw in the math: Data doesn't buy products. People do.

We’ve entered a cycle of "efficiency" that is actually a death spiral. Companies are slashing 20% or more of their workforces to "optimize" margins and please the analyst desk. In the same breath, those same companies are doubling down on ad spend to reach a consumer base they just finished impoverishing.

The most glaring examples:

Here is how the system breaks when the math stops working:

Phase 1: The First to Struggle

The initial tremors hit the companies built on "optionality."

Phase 2: The Total Failure

When the struggle turns to collapse, the "middle-men" of the data economy disappear.

The Moral

We have spent two decades valuing the extraction of value over the creation of it. We built an economy that knows exactly what a consumer wants but has systematically removed that consumer's ability to pay for it, along with any value the products may have had.

Food for thought: If your business model requires a $500B bubble of behavioral manipulation to remain solvent, you aren't an innovator. You’re a parasite waiting for the host to stop breathing.

Real value doesn't require a tracker; it requires a solution to a problem worth solving. Build accordingly.

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The Truth-Machine of Gilly-Goo

The Count of the Wobbleygooks

I help you, you help me, and then we both see, That a world that is fixed is the best place to be. Life is a team sport, we’re all on the field, and the truth is the power that makes the best yield. It isn't just nice, and it isn't just sweet, It's the smartest way possible to stand on your feet.

In the center of town, where the Snaggle-Vines grow, Stands a Great Gilly-Machine, all a-gleam and a-glow! It hummed with a whistle! It whirred with a thump! Producing the Fizz-Juice that makes your heart jump! It puffed out the Puff-Pills! It clinked out the Toys! For all of the Gilly-Goo girls and the boys.

But this Great Gilly-Engine, so shiny and vast, Needs a very specific and special breakfast. It doesn’t eat crackers! It doesn’t eat cheese! It eats Only-True-Things, if you please, if you please! It needs the exact count of Snallywag-Socks, And the "Ground Truth" of pebbles inside of your box.

Young Pip was the Player in charge of the Count, To tell the Machine the exact right amount. He’d count every Wobbleygook, green, blue, and red, Then whisper the number right into its head. "Six Wobbleys today!" he would shout with a grin, And the Fizz-Juice would pour from the spout to the bin.

But one Tuesday morning, while counting the Goo, Pip tripped on his shoelace and dropped a, oops... Two! Two Wobbleygooks tumbled! They rolled down the hill! They splashed in the river and sat very still. Now Pip had a problem. His count was quite wrong. (And the Machine needs the Truth to keep humming its song).

"If I tell the team," Pip thought with a sigh, "They’ll know I’m a stumbler! They’ll know I’m that guy! They’ll pause the whole game, read maintenance books, And give me those 'Oh-Pip-You-Clumsy-Oaf' looks." So he looked at the Engine, and whispered a lie: "The count is still Six!" with a wink of his eye.

He thought he was clever! He thought he was fast! He thought that his "Fiction" would certainly last. He’d saved his own face! He’d stayed on the track! But he’d put a big hole in the team’s Gilly-Goo-Sack...

Dot’s Helpful Drip-Drop

Now Dot was the Player on the very next base, With a Gilly-Goo wrench and a smile on her face. Her job was to polish the Wobbleygook Shells, And ring all the Gilly-Goo Gongs and the Bells. She waited for Six, as the Engine went clink, But she only saw Four... which made young Dot blink.

"That’s funny," said Dot, "Pip whispered for Six, But there’s only these Four for my wrenches to fix! If I tell the team that the count is quite low, The Gilly-Goo Game will be dreadfully slow. Poor Pip will feel silly, his face will turn red, And the 'Team' will have chores and go late to their bed."

So Dot, being 'kind' in a way that was wrong, Decided to help the Machine get along. She took some old Snallywag-Socks from a pile, And stuffed them in Wobbleygook Shells with a smile! She made the Four look like a Six-pack of Goo, By adding some fluff and a little bit of glue.

"There now!" whispered Dot, "I have fixed the mistake! I’ve saved us some time! I have lowered the brake! The team is still winning! The game is still fast! My helpful Little-Fiction will certainly last."

But the Gilly-Machine gave a rattle and cough, And a Gilly-Goo gear-bolt came tumbling off. The Fizz-Juice turned grey, like a puddle of mud, And the Gilly-Goo Gongs gave a hollow-type thud. Because Dot had been 'nice' to save Pip from some shame, She’d added Sunk-Cost to the Gilly-Goo game!

The socks gummed the gears! The glue gunked the wheels! (You can’t imagine how bad a Gilly-Engine feels). By 'fixing' the lie with a lie of her own, The seeds of a System-Wide-Failure were sown.

The Huddle and the Radical Audit

The Coach (the wise Goose) raised a webbed-foot on high, And looked every Gilly-Goo kid in the eye. "Wait! Stop!" cried the Coach, "Blame’s not the game! Nobody wins if we name and we shame! This failure is big, not one little mistake, Problems cascade before everything breaks."

"It isn't just Pip! And it isn't just Dot! It’s the way that we played with the data we got! We hid all the wobbles! We polished the rust! And now our Great Engine is nothing but dust. If you want to be Winners, if you want to be Teams, You have to give Truth to the Gilly-Machine's beams!"

Pip stepped to the front, with his head held up high, (For a Sovereign Player has no use for a lie). "I dropped two green Gooks! I was clumsy and slow! And I whispered a Six just to keep up the show." Dot stepped up beside him, "And I saw the Four! But I stuffed in some socks just to open the door."

They didn't feel small, and they didn't feel bad, (Though the Gilly-Goo park was still gloomy and sad). They felt like a Team with a job to get done, To clean out the Sunk-Cost so they’d have some fun!

They pulled out the fluff! They scraped out the glue! They fished out the socks (which were smelly and blue). They performed a Great Audit, they checked every gear, Until every "Fiction" was gone from the sphere. They didn't just 'sorry', they worked on the core, Until the Ground Truth was just the same as the score.

Then Pip counted Four. Just a plain, simple Four. And the Gilly-Machine gave a happy-type roar! The Fizz-Juice poured out! It was purple and bright! And the Gilly-Goo park was a beautiful sight!

"Life is a team sport!" the Gilly-Goose cried, "With no silly fictions or secrets to hide! When you play for the Truth, and you play for the Team, The world works much better than even your dreams!"

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The Lorax: A History of Silicon Valley

This is adapted from ‘The Lorax’ by the Great Dr. Seuss. If you have not read his work, please do. His stories teach beautiful lessons through the use of whimsy and wonder.

I love Dr. Seuss, so this is a thing I do. If you like it, there are links to others at the end. I make no guarantees as to the freshness of the content.

Unless someone like you cares a whole awful lot, nothing is going to get better. It’s not.

Dr. Seuss 'The Lorax'
  At the far end of tech 
 where the products are sold
 and the wind smells of sandwiches delivered half-cold,
 where no roadmap is ever delivered when told…
 is the street of the Lifted Lorax.
  
 And deep in that end, some people say, 
 if you look deep enough you can still see, today, 
 where the Lorax once stood
 just as long as it could
 before somebody lifted the Lorax away.
 What was the Lorax? 
 And why was it there? 
 And why was it lifted and taken somewhere 
 from the far end of town where the products are sold? 
 The old Once-ler still lives here.
 Ask him. He knows.
  
 You won’t see the Once-ler.
 Don’t look for his booth.
 He stays in his mansion, alone with his things,
 where he drinks cold-pressed juice
 that someone else brings.
 And on rare occasions, out of the blue,
 he tweets
 out a message
 he often repeats
 and tells how the Lorax was lifted away.
  
 He’ll tell you, perhaps…
 If you’re willing to pay.
  
 He’ll send you a link
 to an app where you lay
 one third of your equity, then sign
 NDA
 of course, he will say
 it’s always this way.
    
 He then checks the app
 triple checks the amount
 to ensure he owns you
 that you can’t dismount.
  
 Then he adds what you paid him
 to the piles of cash
 some used for the mortgage
 the rest wipe his ass.
  
 He slacks, “I will ping you by video call,
 While out on my yacht, with crappy sig-nal.
  
 BLURRP!
 The blurps of his call, ring loud in your ear
 and the old Once-ler’s voice is not at all clear,
 since he’s out on the water on cell-phone connection
 choppy and garbled,
 This makes him sound
 quite verbally hobbled.
  
 “Now I’ll tell you.” He says, with his ego displayed,
 “how the Lorax got lifted and taken away…
  
 It all started way back…
 such a long, long time back…
  
 Way back in the days when “The Valley” was green
 and orchards spread far
 for a beautiful scene,
 and a house could be bought by a regular Jane…
 one morning I came to this place I remain.
 And I first saw the schools!
 Stanford and Berkley
 their talent you see!
 So much innovation, but money was lacking,
 an untapped resource, for someone like me.
  
 Between them a freeway Junipero Serra
 with a great halfway point up above Santa Clara
 where Sand Hill Road sat, doing just fine, in a soon to die era.
  
 From the nearby South bay
 came cool morning breezes
 which moistened the fruit
 as it hung in the treeses.
  
 But that talent! Those brains!
 Those smart engineers!
 All my life I’ve been searching
 seeking to obtain
 a resource like this
 that I could abuse.
 A resource I’d care about,
 If I’d read Dr. Seuss.
  
 My heart leapt with joy,
 I’d be an investor!
 I leased a small space
 Near an old shopping center
  
 With GREAT BRAINS AND SKILL, plus some damn lucky timing, 
 We started to watch, our net-worth start climbing.
 In no time at all, I had built a small group
 so I cut down an orchard, at the end of the loop.
  
 The moment I’d finished, I heard W-T-F!
 I looked.
 Something popped out of a plum that had struck
 the ground next to where the last tree lay dead,
 His looks were as strange as the things that he said.
  
 He was small. He was old.
 Had a drawl and was bossy.
 He looked straight on over
 Like he didn’t even know me.
  
 “Douche bag! He said, with a stern knowing tone,
 “I am the Lorax. I speak for what’s grown.
 I speak for what’s grown and warn of what comes!
 And I demand to know, what you’ve done to my plums”-
 He was winded and red; his anger was showing.
 “Why the hell would you destroy, all the things that are growing!”
  
 “Look bro” I said. “No need to get pissy.
 It’s one little orchard. No one will miss. See?
 I’m saving the world. This thing is a network.
 To connect all the people, he said as he smirked.
 It’s a book. It’s a phone. It’s music! It’s apps!
 But it has more to offer than all of that crap!
 You can use it for ads and make tons of money!
 Selling people like products while they use a freebie”
  
               The Lorax replied,
               “Dude, your ego is large, so this may just sting.
               There is no one on earth
               who would need such a thing.
  
 Just as my mouth opened to say “go-to-hell”
 around the corner came AOL,
 they thought this web would be great for a buck.
 They hired some people and backed up a truck.
  
 I clowned the old Lorax, “You stupid old man!
 You’ll never quite get, what we just began!”
  
 “I repeat cried the Lorax,
 I speak for what’s grown!”
  
 “You’re expired. I told him.
 “Go retire in peace.”
  
 I ran for the phone, in those days they plugged in,
 I put in quick calls to nephews and cousins.
 I called all my friends, my college frat buddies
 said here’s the scoop, lets go make some monies!
 We’re going to make the old world move forwards!
 Get over here fast, take the road through the orchards,
 Turn left when there’s strip malls instead of more woods.
  
 And in no time at all,
 the cement was flowing,
 buildings and car lots sprung up in quick fashion,
 concrete and rebar were doing the growing.
 We ‘innovated’
 and we stayed very busy,
 with two maybe three drinks at lunches
 wining and dining,
 betting millions on hunches.
  
 Then…
 Hello, there, hello!
 How the money did flow!
 We needed more buildings
 more car lots
 more blow!
  
 So we cleared orchards with speed
 driven purely by greed.
 We were changing the world
 this was progress we said.
 And that Lorax?...
 We guessed he was dead.
  
 The very next month
 a knock at the door
 open it up, and he’s standing there.
  
 He bellowed, “I’m the Lorax, I speak for what grows,
 Which you are destroying, wherever it shows.
 But I’m also in charge of the birds and the bees
 Who live on the fruit of these orchard trees
 and gorge on the nectar and fruit as they please.”
  
 “Because of your buildings, your car lots, and malls
 there’s not enough food for the winter and falls.
 My poor birds and bees and dying in droves
 the rest are out searching for new homes and new groves.”
  
 “This was paradise to them, but now they must go.
 They require new orchards where their families can grow.
 Good luck my fine friends,” he said as he hung his head low.
  
 I, the Once-ler, felt something
 As I watched them all go.
 BUT…
 Money I worship!
 And I’ve got plenty of blow.
 Who needs birds anyway? I drive a Lambo.
  
 It wasn’t intentional. I didn’t want that.
 But bigger is better when wallets are fat.
 I biggered my bets. I biggered my tech.
 I biggered my campuses. I biggered my head.
 Our tech started shipping, all over the globe
 from Bangkok to Paris and back to Latrobe.
 So I kept on biggering… selling more tech.
 And I biggered my wealth, with each inbound check.
  
 Then there he was, the Lorax was back
 That angry old coot with more shit that was whack.
  
 “I am the Lorax,” he choked through a cough.
 Clearing his throat he readied a scoff.
 “Once-ler!” He roared, with the rasp of his age.
 “Once-ler! The air’s filled with smog. Disengage!
 My poor lotis butterfly, well they can’t see their way.
 At this rate we’ll lose sight of the sun through the day.
  
 “And so,” said the Lorax,
 “-please pardon my tone
 They can’t survive here.
 I’ve sent them off to places unknown.”
  
 “Where will they end?...
 I don’t comprehend.”
  
 “They may have to fly for week upon week
 To get away from you, and the smog that you leak.”
  
 “But worse,” cried the Lorax, his neck hair stood up.
 “Let me say a few words about this f’ng slop.
 Your plants are dumping this shit without stop.
 They build your chips and out this stuff pops.
 And what do you do with this poo smelling goo?
 I’ll show you, you self-entitled boy-man you!”
  
 “You’re killing the lakes where the Lake Splittail fish swims!
 No more can they frolic and live out their whims.
 So I’ve ordered them off. Their future is bleak.
 They’ll wander on land, flip-flopping and weak
 searching for water without oil streaks.”
  
 And then I got angry.
 So shakingly angry.
 I yelled at the Lorax, “Now listen here, Pops!
 All you do is whine, and scream Stop! Stop! Stop!
 Well, I have my liberty, sir, and I’ll tell you
 I intend to keep doing what I want to do!
 And! For your information, you Lorax, I’m going to keep biggering
               And BIGGERING
                             And BIGGERING
                                          And BIGGERING,
 Turning orchards into lots for engineers cars
 to build more tech we can trade for gold bars!”
  
 And at that very moment, we heard a loud sound!
 Outside in the orchards a tree hit the ground.
 The final fruit tree did finally fall.
 The orchards were gone, once and for all.
  
 No room. No more boom. No work to be done.
 So, in no time, my friends, nephews, cousins, every one,
 Threw up two fingers as they hopped in my cars,
 Peace out, they said as the tires burned tar. 
  
 Now all that was left was a bad smelling sky
 Office buildings, parking lots…
 the Lorax…
 and I.
  
 The Lorax said nothing. Stared through my soul…
 his stare said to me, what he saw wasn’t whole…
 as he rose to get going, his mood black as coal.
 I’ll never forget that look on his face
 when he stood one last time, to take leave of this place,
 this Garden of Eden, that I had erased.
  
 And all that the Lorax left here in this mess
 Was a pile of rocks, with one word…
 “Unless.”
 Whatever that meant, well, I just couldn’t guess.
  
 It’s ancient history now.
 But I’ve thought of it lots.
 Worried, and muddled
 to untangle the plot. 
 While Silicon Valley crumbled away
 I’ve tried to make sense
 I’ve worried, I’ve wondered,
 and not just for legal defense.
  
 “But now,” says the Once-ler,
 “Now that you’re here,
 The word of the Lorax seems perfectly clear.
 UNLESS someone like you
 Cares a whole awful lot,
 Nothing is going to get better.
 It’s not.
  
 “So…
 Listen!” cries the Once-ler
 “I’ve sent you a seed
 in it you’ll find the hope that you need.
 It’s the last of its kind, so treat it as such
 there’s no other thing, the world needs this much.
 Plant it somewhere bleak and dreary
 Feed it, water it, and in theory
 The hope will grow big and strong
 and one day the Lorax will come back along.
Oh, the Places You’ll Go! (A Cisco ACI Story)
Horton Hears Hadoop
The App on the Crap (An SDN Story)

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Driving Digital Transformation

Driving Digital Transformation

“Digital, Digitization, Digital, Digital, Digital Transformation. There, I've hit my mandatory quota of 5 digital mentions for my presentation, now we can get to something interesting.”

That was my opening line at a large data center and cloud conference in Rome. It wasn't the one I'd planned, but I had just spent a day listening to my executive colleagues from around the industry wax philosophically about 'digital' with no mention of how, why, or what. No call to action, no roadmap, no substance. The previous presenter was sitting front row center with his jaw wide open when I finished the sentence. He'd had digital-this, digital-that, as the title for every slide in his deck. Sorry, not sorry.

I haven't watched 'Game of Thrones' but I imagine 'Winter is Coming' might be similar to the way 'Digital Transformation' gets thrown around. 'Um yeah, it's this thing, it's on it's way, it's already happening in some places. Everyone knows what it is, definitely, for sure.' Let's agree that: it is a thing, it is happening, and it is coming in stronger waves. From there let's look at what it is, where it's coming from, and how it can be embraced.

Let's rewind to the beginning of widespread Information Technology adoption. We'll go back to the early days of networked computing and use the adoption of email systems as an example. As a company adopted email systems for the first time, they were dipping their toe into digital transformation. Paper based systems and analog based voice calls were converted to a digital medium. What that was doing under the surface was creating business value through technology adoption. That is the key to digital transformation.

Theoretically if there were two companies in the same industry and one was first to deploy and adopt an email system, they'd have a competitive advantage. The advantage of speed and agility. The hidden key phrase of the sentence being adopt. Deploying an email system wasn't enough. They had to drive adoption, incorporate it into their process and modify work flows to take advantage of it.

As technology became commonplace a shift occurred behind the scenes. Information Technology (IT) moved from a value-creation center to a cost-center. Technology purchase decisions moved from 'what can it do for the business' to how much money can we save doing the same thing. IT sales conversations shifted to circular conversations about return-on-investment (ROI), and sales cycles began incorporating any number of questionable ROI calculations.

Now comes Digital Transformation with all it's hype being treated as something new. It's not. Like most everything in technology it's circular. We're at a technology inflection point where IT can move back into the 'what can it do for the business' seat. Digital Transformation is simply using emerging technology and new IT operational models to drive new value streams for the business or mission. No more, no less.

Several things are coming together at once to form the catalyst of this shift. New technologies like big data, and AI. New consumption models like mobile first compute users. And new delivery models like cloud which provide an extremely low compute entry cost and a scale up model as a company grows. Uber is one of the most touted examples of combining these things to create market disruption, which is just silicon valley's term of the week for transformation.

Uber is an example I like, and not in the doom and gloom 'disrupt or be disrupted' way people love to use them. The question I ask my customers is different: 'If you were the taxi companies three years before Uber launched, and you had the idea for an Uber like app, could you have executed on it? Would your IT infrastructure and organization been able to build and adopt the new model?' Universally the answer is no.

The first stage of digital transformation is modernizing the technology delivery stack into a system that provides agility. Agility to test out new ideas, agility to fail and try again. Agility to deploy the bright ideas that your organization comes up with. The world moves fast, the longer it takes to process an idea, and get it stood up, the higher the chance of missing the market and being out maneuvered.

The dirty secret in all of this is that the technology is easy. There are hundreds of great options to choose from when it comes to the right technology. You can cloud it, automate it, DevOps it, etc. Alone or in tandem all of these things can work perfectly from a technology perspective to achieve your goals. The tech is easy, but most still fail.

The hard part is choosing the technology stack that fits your organization, then remodeling your people and process to take full advantage of it. Nobody likes to admit that getting new technology running is the easy part. The hard part is getting it adopted to it's fullest potential within your organization. Successfully launching a product or project internally is as important as picking the right tech and standing it up.

I look at this like Marine Corps boot camp. As a recruit we spend all of boot camp hating it and waiting to graduate, thinking boot camp is the hard part. Our drill instructors assure us boot camp is the easiest part of being a Marine. Years later we find out they were right. Boot camp, like a technology install, is fairly color by the numbers, if you follow the instructions things work as expected. Being in the fleet, post boot camp is like technology adoption. You're up and running but now it's your responsibility to apply the skills and capabilities the right way every day.

When looking at making technology shifts be ready to tackle the people and process with as much energy as you do the technology. You'll need leaders, champions, early adopters. You'll need to provide a clear sense of direction, intended outcome, and a sense of 'why'. If your team is bought in, and all moving towards the same goal the technology stack becomes a supporting character in the transformation you'll drive.

As a parting thought on Digital Transformation try and think big. I've been privileged to travel the world working with customers of all types in some very interesting places. I've gotten to see first hand the positive transformative power technology can have. From banks in Africa using cell-phone usage statistics to assess credit worthiness and provide small-business loans to people with no credit history, to hospitals in India using tele-medicine to provide advanced patient care on-site in remote villages.

Digital transformation is as much about change and a better future as it is about profit lines. Even better, the two don't have to be separate goals. This is why I wake up every morning excited to see what I can help my customers achieve that day.

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Best Practices of Women in Tech

The following is a guest post by Sara (Ms. Digital Diva)

Today’s tech industry has a new face, and that face is female. Though traditionally male dominated, more and more women are making their mark as leaders in the tech field. Contributing not only to the continuous advancements we’re seeing in technology, these women are making a point to build up one another and the young women who look up to them. Progress has been made, but there’s still work to be done. Here are some of the ways these women are doing it.

Hit the Ground Running
Just as important as the women who are already working in the tech field, are the young girls who aspire to be like them. Supporting these young women and girls to follow their passion and providing them with the necessary resources to reach their goals, is key to the future of tech. An example of these efforts comes from founder of Girls Who Code, Reshma Saujani, who aims to close the gender gap by providing an outlet for girls to explore their abilities and pursue interests computer science. Similarly with Women Who Code, Alaina Percival empowers women by offering services to assist in building successful careers in technology. Breaking out of the stereotypical boxes and utilizing these sorts of programs not only builds confidence, but helps those just starting out find their niche. This can have a important impact on professional development when it becomes time to specialize.

Pursue What’s Most Beneficial to You
There’s no stopping a woman with goals. Once you have that goal set, it’s up to you to do everything it takes to get it done. In this industry, technology is constantly advancing. To stay current, you must maintain a hunger for learning. Staying up-to-date with trends, and qualities that are most in-demand by employers, will keep you ahead of the game and closer to reaching your goals. This quality fortunately seems to come natural to women. According to HackerRank's Women in Tech Report, women are incredibly practical in this sense, and tend to pursue proficiency in whichever languages are most valued at the moment.

Succeed Together
It’s tough to admit, but getting more women in tech is still a work in progress, and in order to continue progressing we must work together. Rarely does anyone succeed in life without mentorship, guidance or at least support from others. There’s nothing wrong with asking for help. Taking the time to network with women who have earned a position you hope to achieve someday is essential in overcoming workplace challenges and clarifying questions. Even if you can’t get in physical contact with a role model of yours, keeping up with what their writing, saying and working on, can help you expand your own interests and continue learning. The process of working towards your ultimate potential is a long one, but embracing advice can help you get there efficiently.

Lessons Learned
Like anything in life, developing your professional career comes with lots of trial and error. You’ll succeed and you’ll fail, you’ll try things you like and try things you hate. It’s all a part of the process. When you’re the only woman in an office full of men it can be difficult to speak up or put yourself out there in fear of making a mistake. But if I’ve learned anything in my career, it’s that staying silent signifies acceptance and not involving yourself in situations that can help you grow only hurts you. Getting involved in groups, committees, projects, anything that interests you is the biggest piece of advice I can give. Not only will you expand your knowledge and experience, but it’s a great way to get to know others in the tech community. Building relationships is a key part of any profession, but especially in environments where you want to build confidence.

A final thought to take with you is, to always be advancing. So much of the technology industry is self development and striving to discover the next best thing. Curiosity is what will keep you afloat. Utilizing programs, and keeping up with verticals that interest you can help in develop strong points of view on emerging technologies. This is crucial as you grow in your career, as people generally listen to those who have something to say. What you don’t want to do is get swept up in the crowd and lose your voice. If tech is what you’re interested in than it’s where you belong, whether you’ve been studying it your whole life or just getting started. Never underestimate yourself and don’t confuse experience with ability. There are so many incredible women doing incredible things in the tech industry. All they need to be even greater, is you.

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Intent-Driven Data Center: A Brief Video Overview

Here's a brief video overview of Intent-Driven data center. More blogs to come.

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Intent Driven Architecture Part II: Policy Analytics

*** Disclaimer: Yes I work for a company that sells products in this category. You are welcome to assume that biases me and disregard this article completely. ***

In my first post on Intent-Driven Architectures (http://www.definethecloud.net/intent-driven-architectures-wtf-is-intent/) I attempted to explain the basics of an Intent-Based, or Intent-driven approach. I also explained the use of Intent-Driven architecture in a network perspective. The next piece of building a fully Intent-Driven architecture is analytics. This post will focus there.

Let's assume you intend to deploy, or have deployed a network, server, storage, etc. system that can consume intent and automate provisioning based on that. How do you identify your policy, or intent for your existing workloads? This is a tough question, and a common place for policy automation, micro-segmentation, and other projects to stall or fail. This is less challenging for that shiny new app your about to deploy (because you're defining requirements, the policy/intent), it's all of those existing apps that create the nightmare. How do you automate the infrastructures based on the applications intent, if you don't know the applications intent?

This is one of the places where analytics becomes a key piece of an intent-driven architecture. You not only need a tool to discover the existing policy, but one that can keep that up-to-date as things change. Was policy implemented correctly on day 0? Is policy still being adhered to on day 5, 50, 500? This is where real-time, or near real-time analytics will come into play for intent-driven architectures.

I'm going to go back to the network and security as my primary example, I'm a one-trick pony that way. These same concepts are applicable to compute, storage and other parts of the architecture. Using the network example the diagram below shows a very generalized version of a typical policy enforcement example in traditional architectures.

Network Policy

 

Using the example above we see that most policy is pushed to the distribution layer of the network and enforced in the routing, firewalls, load-balancers etc. The other thing to note is that most policy is very broad deny rules. This is what's known as a blacklist model; anything is allowed unless explicitly denied. This loose level of policy creates large security gaps, and is very rigid and fragile. Additionally, because the intent or policy is described so loosely it's nearly impossible to use existing infrastructure to discover application intent.

In order to gather intent and automate the policy requirements based on that intent, we need to look at the actual traffic, not the existing rules. We need a granular look at how the applications communicate, this shows us what needs to be allowed, and can be used to gather what should be blocked. It can also show us policies that enforce user-experience, app-priority, traffic-load requirements, etc. Generally this information can be gathered from one of two locations: the operating system/app-stack, or the network, even better would be using both. With this data we can see much more detail. The figure below shows moving from a broad subnet allow rule, to granular knowledge of the TCP/UDP ports that need to be open between specific points.

Old policy vs new policy

These granular rule-sets are definitely not intent, but they are the infrastructures implementation of that intent. This first step of analytics assists with tightening security through micro-segmentation, but also allows agility in that tightened security. For example if you waved a magic wand and it implemented perfect micro-segmentation, that micro-segmentation would quickly start to create problems without analytics. Developers open a new port? A software patch change the connections ports for an app? Downtime, and slow remediation will be unavoidable. With real, or near-real-time analytics the change can be detected immediately, and possibly remediated with a click.

Analytics plays a much bigger role than just policy/intent discovery. The analytics engine of an Intent-based system should also provide visibility into the policy enforcement. Some examples:

All of this should be done by looking at the actual communication between apps or devices, not by looking at infrastructure configuration. For example, I can look at a firewall rule and determine that it is properly configured to segment traffic a, from traffic b. There is nothing in the firewall config to show me that the rest of the network is properly configured to ensure all traffic passes through that firewall. If traffic is somehow bypassing the firewall, all the rules in the world make no difference.

Analytics engines designed for, or as part of, an intent-based networking system provide two critical things: policy discovery, and policy verification. Even with a completely green-filed environment where the policy can be designed fresh, you'll want analytics to ensure it is deployed correctly and keep you up-to-date on changes.

There are three major components of an intent-driven architecture. I've discussed intent-based automation in the previous post, and analytics in this post. I'll discuss the third piece in the near future: assurance, knowing your system can consume the new intent.

*** Disclaimer: See disclaimer above. ***

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Intent Driven Architectures: WTF is Intent?

*** Disclaimer: I work for a vendor who has several offerings in the world of intent-based infrastructure. If you choose to assume that makes my opinion biased and irrelevant, that's your mistake to make, and you can save time by skipping the rest of this post. ***

*** Update at the end of the blog (10/20/2017)***

In the ever evolving world of data center and cloud buzzwords, the word 'intent' is slowly gaining momentum: Intent-based x, intent-driven y, etc. What is 'intent' and how does that apply to networks, storage, servers, or infrastructure as a whole, or better yet to automation? Let's take a look.

First, let's peek at status quo automation. Traditional automation systems for technology infrastructure (switches, servers, storage, etc.) utilize low level commands to configure multiple points at once. For example the diagram below shows a network management system being used to provision VLAN 20 onto 15 switches from a single point of control.

Basic Automation

The issue here is the requirement for low level policy rendering, meaning getting down to the: VLAN, RAID pool, firewall rule level to automate the deployment of a higher level business policy. Higher level business policy is the 'intent' and it can be definied in terms of: security, SLA, compliance, geo-dependancy, user-experience, etc. With a traditional automation method a lot of human interaction is required to translate from an applications business requirements, intent, and the infrastructure configuration. Worse, this communication typically occurs between groups that speak very different languages: engineers, developers, lines-of-business. The picture below deipicts this.

App Deployment Chain

This 'telephone game' of passing app requirments is not only slow, it is also risk prone because a lot gets lost in the multiple layers of communication.

Hopefully you now have a slight grasp on the way traditional automation works, basically the overall problem statement. Now let's take a dive into using intent to alleviate this issue.

I'm going to use the network as my example for the remainder of this post. The same concepts are applicable to any infrastructure, or the whole infrastructure, I just want to simplify the explanation. Starting at the top, a network construct like a VLAN is a low-level representation of some type of business policy. A great example might be compliance regulations. An app processes financial data that is regulated to be segmented from all other data. A VLAN is a Layer 2 segment, that in-part, helps to support this. The idea of an intent-driven architecture is to automate the infrastructure based on the high level business policy, and skip the middle layers of translation. Ideally you'd define how you implement policy/intent for something like financial data one time. From them on, simply tagging an app as financial data ensures the system provisions that policy. The diagram below shows this process.

Intent Driven Workflow

One common misnomer is that the network, or infrastructure must be intelligent enough to interpret intent. This is absolutely false. The infrastructure needs to be able to consume intent, not interpret or define it. Intent is already understood in business logic. The infrstructure should be able to consume that, and automate configuration based on that business logic intent. In the example in the diagram business logic has already been defined for the given organizations compliance requirments. Once it has been defined, it is a resuable object allowing automation of that policy for any app tagged requiring it. Another note is that the example uses a 'dev' referencing custom built software, the same methodology can be used with off the shelf software.

There are many reasons for not trying to build intent based systems that can automatically detect and consume intent. One, non-minimal reason is the cost of those systems. More important is the ability to actually execute on that vision. Using a network example, it would be fairly simple to build a network that can automatically detect an Oracle application using standard ports and connectivity. What the network alone would not be able to detect is whether that workload was a dev, test, or production environment. Each environment would require different policies or intent. Another example would be difference in policy enforcement. One company may consider a VLAN to be adequate segmentation for different traffic types, another would require a firewall, and a third might require 'air-gap.' These differences would not be able to be automatically understood by the infrastructure. Intent based systems should instead consume the existing business logic, and automate provisioning based on that, not attempt to reinterpret that business logic themselves.

The other major misnomer regarding intent based systems is that they must be 'open' and able to incorporate any underlying hardware and software. This is definitely not a requirement of intent based systems. There are pros, and cons to open portability across hardware and software platforms. Those should always be weighed when purchasing a system, intent-based or otherwise. One pro for an open system supporting heterogeneity might be the avoidance of 'vendor lock-in.' The opposing con, would be the additional engineering, QA costs as well as fragility of the system. There are many more pros/cons to both. To see some of my old, yet still relevant thoughts on 'lock-in' see this post: http://www.definethecloud.net/the-difference-between-foothold-and-lock-in/.

Overall intent-based systems are emerging and creating a lot of buzz, both within the vendor space and the analyst space. There are examples of intent-based automation for networking in products like Cisco's Application Centric Infrastructure (ACI). System like these are one piece of a fully intent-driven architecture. I'll discuss the other two pieces, assurance and analytics, in future posts, if I'm not simply too lazy to care.

** Update: Out of ignorance I neglected to mention another Intent-Based Networking system. Doug Gourlay was kind enough to point out Apstra to me (http://www.apstra.com/). After taking a look, I wanted to mention that they offer a vendor agnostic Intent-based networking solution. The omission was unintentional and I'm happy to add other examples brought to my attention. **

*** These thoughts are mine, not sponsored, paid for, or influenced by a paycheck. Take them as you will. ***

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