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Transformation of Innovation (Notes from Aug 12 to Aug 18, 2019) September 4, 2019

Posted by Anthony in Blockchain, Digital, education, experience, finance, Founders, global, Hiring, Leadership, marketing, NLP, Politics, questions, Real estate, social, Uncategorized.
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Hello! Hope Labor Day treated everyone properly, whether you snuck in some time-and-a-half pay for work, avoided it altogether or vacationed. I am going to keep the brief at the start short today because there’s a common theme. And I have been considering longer form writing without the notes on other topics maybe once or twice a week.

From last week – I still am working on the 13 Minutes to the Moon podcast – excellent. And it’s engaging as they went through the building and prep work that went in to getting there before decade-end.

The new segment that a16z has produced with the 16 minutes on the news has been fun, especially if you like an audio version of what’s been popular in tech/news. Sonal has done a great job leading most of them. I found the two that I listened it related to the title – transforming innovation. Software as eating the world (any company/product/service that can be digital will force the company to become software company), along with digitizing many of the slowest movers because the pressure has become high enough (re: Fed with ACH Now). At some point, in order to command more control or to make sure you aren’t disrupted out of the market, companies have to compete and give the customers or users what they want – faster, easier transactions in Fed Now’s initiative.

There were also some fantastic investors / founders that are included. How they developed and framed their careers to step from one thing to the next. If you noticed, many of the 20min VC episodes I listen to are in order from 2015 to now 2016. Fascinating to hear the comments made at that time to update to 2019 (as many of the same bullish comments are made with caveats that have yet to come to fruition – and valuations increased accordingly).

Hope you enjoy the listens!

  • 13 Minutes to the Moon
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    • Ep 05 – “The fourth astronaut”
      • Intertial navigation – if you have your speed and know where you are, can control where you’re going
      • Self-guiding ballistic missiles that couldn’t get thrown off course via radio or otherwise – knew where it was
        • GPS, primitive computer received navigations and could adjust course if necessary
        • Charles Stark Draper who founded MIT’s guidance instrumentation lab
      • Had been a grad of Stanford and went to MIT and became leading expert in aircraft instrumentation / guidance
        • Dedicated to the astronaut program, so much so that he applied – was turned down
          • Practical application with such sensors to be useful was his expertise – size / practicality in flight control systems
      • Had to convince everyone that the computers would work and be trusted
      • Apollo bought 60% of the chips that were out and being manufactured – huge boost for computer industry
        • Good hardware required good software (an afterthought)
      • Called on programmers for building the software Margaret Ate Hamilton (started as programmer, then was in charge as program manager)
        • Developed a system to write software so that it would be reliable and she sought out the bugs/errors – no way to do it otherwise
          • Right times vs wrong time, wrong data, wrong priorities (interface errors) – we take for granted everything we have now
        • No rules or field at the time (akin to “Do you know these English words?” – yes, you’re qualified)
        • Don Isles – math graduate looking for something to do next who joined in 1966, software had been written initially – app code to fly was starting
          • Lunar landing phase commanding – in retrospect, huge – but it was a job at the time
      • Apollo Guidance Computer – 70 lbs in 1 cu ft, 55 W with 76kb, 16-bit words, 4 kb were RAM R/W memory, rest was hardwired
        • Got to the moon on punch cards – 100 people working on it at the end – submit in one run overnight and run simulations
        • 2 women that worked to keypunch before working as full-time – printed lines of code to turn into punch codes
      • Noun-verb inputs for flying – lunar landing, for instance
        • Built the computer interface with idea of “Go to moon” and “Take me home” but it instead had 500 buttons and was much more interactive
          • First system where people’s lives were at stake with it – fly by wire system. Astronauts didn’t control it, they controlled the joystick, etc…
    • Ep 06 – “Saving 1968”
      • Armstrong and Buzz Aldrin
  • Fed reaction (a16z, 16min on the News, 8/12/19)
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    • FedNow – 24/7 open service for access to checks faster to launch in a few years
      • Half the population lives paycheck to paycheck and should care for the $30 overdraft fees that a ton of people do
      • Massive amount of losses to banks here in the US
    • ACH batches all payments in a day or maybe twice vs instant
      • Realtime payment network – 26 banks but need all banks to be a part of this network
    • Against Fed would say to just run the regulatory part vs the operational side
      • Obligate banks to join ACH, etc…
      • Infrastructure for checks has not updated to the tech advantages that we’ve gotten to now
      • Catching up to rest of world, which is 10 years ahead
    • Death of retail – Barney’s filing for bankruptcy, closing 15 of 22 stores
      • Been around since Great Depression
      • Ecommerce coming and direct to consumer is going toward market share
      • Highly leveraged fixed costs, inventory but can go sales to hemorrhaging money and become unviable
    • Grocery is largest single category of US retail, more than apparel and personal – completely immune to digitization historically
      • Inventory is better served close to consumer, physical grocery as distributed warehouse
  • Philipp Moehring, Head of Angelist EU (20min VC 1/6/16)
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    • First European hire for Angelist since Jan 14, venture partner at 500 Partners and Principal at SeedCamp
    • Angelist Syndicate for his
    • Worked for a bunch of startups during his studies, but realized he didn’t want to work for a large company or consultancy like when he started
      • Worked for a professor that was doing research on VC – did his thesis on same topic, asked for data
      • Fulltime job came from a guy who went off on his own to start firm and he was asked to join
    • MBA in Tech Management and Tech Entrepreneurship, where management is very different there
      • Analyst and associate work can be a great job but it’s not a quick way to partner or anything
      • Seeing founders doing a second business after 7-8 years, even after do great and get raises
        • People don’t usually stay at their first job for 8 years but starting at VC, people will jump to a startup second
    • EU vs US scene – SV where VC started and is much more advanced, simply due to a lack of epicenter
      • Angelist looking to get into Series A (not necessarily leading, though) – movement
    • Certainly London for VC – number one ecosystem in Europe, as the largest metro area, tech and VC and money
      • Hard to copy for other places – culture, politics and what makes the city to be interesting
      • Berlin has the momentum as the number two, as well as Stockholm or in Finland, maybe Paris (inward), Lisbon and distribution of eastern Europe
    • $400mln funding for Angelist from CSC Upshot into syndicates – GPs investing directly
      • Does his 500 Partners role on the side – usually someone with investing on the side and has more firepower
      • Wants the deal flow or coverage in the areas they won’t have
      • Knows an entrepreneur and can get in the chance on seed or small amounts to invest in
    • Known the partners at 500 Startups for a bunch of years and could invest similarly to his Angelist style
      • Could be flexible and born out of the way the fund is positioned and investing
    • Most exciting for him is having people that he’s invested in hitting their stride and succeeding
    • William Gibson as a writer who influences his thinking, Snowcrash as a book that depicts the future
      • Looks more at science fiction for tech advances now
    • Most read blog – too many to count, Brad Feld – has a tool called SelfControl against social media
  • Phil Libin (@plibin), co-founder and CEO All-Turtles (Mastering Innovation, 8/8/19)
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    • Discussing real problems with AI

 

 

 

  • Andrew Chung, Founder and CEO Innovo Property Group (Marketing Matters, 8/7/19)
    • Partner at The Carlyle Group, US real estate
    • Started IPG in 2015
  • Stefan Thomke, professor at HBS (Wharton Knows, 8/13/19)
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    • Discussing his paper on magic stick of customers
    • Online experiments – running them quickly and decisively

 

 

 

 

 

  • Ivan Mazour, (@ivanmazour) founder and CEO of Ometria (20min VC FF 029)
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    • Serial entrepreneur, author, investor – Ometria: predictive/marketing analytics platform
    • Born in Moscow, parents PhDs – mom brought him to UK to study math @ Cambridge
    • Started his first thing in property since that was biggest, public industry to get involved
      • Around 26, didn’t utilize any of his studies and data-focused nature, so he leveraged proceeds with his cofounder to make angel investments
    • Wanted to become relevant and learn about tech industry – made 30 investments in 4 years, stopped prop dev, did a Masters in App Prob
      • Refreshed knowledge to build a data company
      • Founding after investing – wrote a blog post as his approach to investment and his dream
        • Build a truly world-leading tech company but accepts lack of experience
    • Thought about how much capital to allocate to invest and how much to invest to be taken seriously – needs to be able to learn from it
      • Angel investor as $20-30k pounds
      • Received a second seed or extension round with Ometria – significantly bigger than seed, but reality is not enough for Series A
        • Hire more engineers, increase team from 20-30. But Series A would be to set up internationally and expand S&M
    • One-sided barbell – huge amount of funding on early, early stage investing
      • Anyone can work to get funding at early, small stage – lots of companies are vying for more eyeballs from bigger ones they need
      • At late stage, if you have the metrics, you’ll have the funding – growing 300%, hit $1m ARR and no question you’d get round, SaaS-wise
    • Launched as an ecommerce analytics company, wanted massive market for data – $3tn ecommerce and retail
      • Launching 2013, analytics was hottest thing (KPMG raised $100mln fund for this only) – by 2015 for big round Ometria, analytics wasn’t relevant/interesting
      • Fascinating to experience – marketing was far more important – actions engaging revenue and data, leveraged
    • First ones to come in were validating – people who he worked/invested with previously
      • Angels that were amazing, AngelLab’s Rachel that was meeting best founders and seeing best companies
      • Had tried to sell Phil as a customer on Ometria and he ended up investing – Alex is on board as 2nd largest institutional investor
    • Pitching angels vs other investors
      • With angels, he had engagement metrics, not revenues – introduced team and had beta user metrics (logging in 7x a day and loving it)
      • Four founders and engagement of platform that allowed closing of round
      • For VCs, chart of MRR that was up and right – increasing growth
    • Several funds liked the company and wanted to consider investing – said he should’ve held off, probably – got excited and continued conversation
      • Waste of time for both sides – hadn’t moved far enough on VC metrics to get a big enough investing for what you’re raising
    • Offline retail – stores won’t go away – thinks there will be an entire platform that will be an ecommerce platform that is based on personalization
      • Product recs, change website and order them – complicated and difficult – best platforms aren’t designed to do that – $1bn company
    • His highlight: sitting in his boardroom after increasing it, Elizabeth Ying (PayPal, head of D/S), Mike Baxter, Allie Mitchel (Huddle founder)
      Looking around that they were talking about his company and making a few investments that he was CEO of and they had 10-20 years experience
    • Favorite productivity tools: ToDoIst, Google Keep for managing main reports, HangOuts
    • Favorite books: Rich Dad, Poor Dad as formulating a way of thinking, and Dale Carnegie’s How to Win Friends and Influence People
  • David Tisch (@davetisch), MP at BoxGroup, Inc (20min VC 1/11/16)
    site-logo-home

    • Also, cofounded Spring – brands to consumers via mobile with his brother, Allen
    • Coded as a kid, kept using the internet, entryway into internet and software – didn’t think of it as investor
      • Went to college and law school, became a lawyer and joined real estate finance in m&a but he did that for a year and wasn’t into it
      • Started a company, experimented and sucked – sold to a larger company and was there for 2 years at KGB
      • Went to TechStars – launched and run the NY program after he had made 3-4 investments
    • Cementing of the NY scene would be a magnet company like Amazon, Facebook, Apple, Google – huge magnet for talent
    • The Box in NY as a cool club that he hadn’t been to and his first investment was in a company called Boxy
    • A 20th employee is exponentially more valuable than a seed stage investor – tries to be an valuable investor, though
    • Magical utility or happiness for user or incredibly polished path to where you’re going – different from early days of mobile
      • Should happen soon – hasn’t happened since Snapchat/Tinder as consumer
    • Spring for him – exact opposite of sitting above the clouds as VC and strategy – incredible other side with his brother
      • Mall on your phone – 1200 brands directly (Etsy as maker’s story) – single mobile experience to make it better
      • Free shipping and free returns in 2015 for marketplace and working with their partners
      • VIP, customer service, making a single experience
      • Apparent that the opportunity was sitting there – he had told his brother “Don’t start a company”
    • Doesn’t read much – watches a lot of tv and consumes that as a way to learn
    • Finding his partner Adam at Techstars is probably the highlight
    • Reads online a lot – design blogs/architecture/city – Fred Wilson as successful VC in NY
    • Invested in SmartThings – sold to Samsung a couple years prior and built into products
      • Deep affinity for space, so he invested into Nucleus – video intercom in houses but it allows outbound, also
      • Uncomplicates the phone – primary thing on cell (voice, messenger and text bringing into house)
  • John Wirtz, CPO at Hudl (Wharton XM)
    hudl-logo.1de182540fb461fded02ad2cb75963d4945c560d

    • Coaching and products innovation – getting cameras at 50 yd line or in arenas
      • Not so much looking at point-to-point tracking or high speed for baseball, softball
    • More on tracking all high school players and colleges – uploading of highlights and working with coaches
    • 95% coverage now
  • Software has eaten the world (a16z 8/18/19)
    • Marc and Jorge Condo discussing computer science and its eating healthcare
    • Term from his essay in 2011 after starting firm, tech industry is 70+ years old after WWII, packing $500 that used to be $10-15mln
      • Pessimism after recession – Marc held opposite opinion as just starting (platform built)
      • 3 claims: any product/service that can be software product will be software (boomboxes, cameras, newspapers, etc…)
        every company in the world in those products will become a software co
        as a consequence of 1 and 2, long run the best software company will win
    • Incumbents in auto industry – cars are very dangerous, very hard and software companies think otherwise – value of car is in software (500 in 50 mi radius)
      • Surprising innovation fields: legal, insurance, real estate, education, health care
    • Never imagined investing in new car companies – new industry in 1890, 1920s Henry Ford
      • One new major car company attempt by Preston Tucker (Automotive – Tucker movie, catastrophe)
      • Went from hundreds in 1910s to 3 in 1920s and after
    • Profound technological revolutions as ML/DL/AI as incredibly innovative and cryptocurrency
      • Software founders for how to use and those that haven’t – can be quite transformative
    • Fundamental transformation with internet was music industry – triple whammy – people loved music (? Often dogs eat dog food? – not case in music)
      • Isn’t it great customers love music so much? They want the thing – showing consumption. Music executives said no. Suppliers refusing the demand increase.
      • Pricing issue – want 1 song vs 12 songs on label. Price-fixing collusion by the 4-5 labels. Could overcharge by factor of 10.
      • Consumers were breaking law but the correct reasons. Was immoral, illegal by price collusion.
      • Went from Napster, Kazaa, Limewire, Frostwire, BitTorrent (all investor catastrophes as too early since they couldn’t get pricing from labels)
        • Spotify as 15 years later where investors were scarred but time had come
    • When layer commoditizes, the next layer can become massively valuable – focus is on commoditized layer (contraction for recorded music purchases)
      • US market for live concerts grew 4x in aggregate demand – unlimited access to music, so fun is concert and experiences
    • Marc as serving on board of hospital – mission in terms of health care and medical research and school – nonprofit with highly motivated people
      • Design and build a new hospital – finally opening in 2019 (2005 green light)
      • Well-functioning boards that he sees as 7 people vs 25 or so in hospital
      • Quality problems in auto industry in 1950s / 1960s initially, unsafe at any speed – 70s/80s/90s was TQM – debug quality manufacturing
      • Medical compliance issues – 1/3 not filling prescriptions, 1/3 just take cocktails of them
        • Organ transplants are only 60% compliance
        • Assembly line requirements to motion – decode for running properly, maybe do that for hospitals and doctors – Purell, even
      • EMR at Stanford – $400mil one bid, $100mil to Epic and $300mil for implementation system Perot Systems
        • Interoperability and open source, building on everyone’s creativity (except Epic) and APIs
    • Eroom’s Law – price of bringing new device or drug to market doubles every 10 years – VCs in both decided the economic cycles were too different
      • Names now for VC are ones that aren’t the same big firms
      • Founders are different, as well – PhD in bio but programming since 10 or hybrid tech to pitch
      • Missing middle as converging of scientific domains and getting a16z’s new partner, former Stanford professor in the middle who helped spin it up
    • Digital therapeutics, cloud biology, IT applied to Healthcare
    • Defend market or advance innovate market but SV is starting from scratch – experiments in tech, or business (famous train wrecks)
      • Portfolio approach to experiments – 10 experiments in 10 different parts of biotech / industry – look at successes and asymmetric returns
      • If there are big companies that can do obvious things, they’ll be good at increment – industry does different ones
    • Need evangelical marketer or sales – Jobs’ saying how to envision the picture because consumers have no ability to project this
      • Elon’s Model S – no superchargers or charging at home – had to paint a picture to demonstrate it, get enough sales to build the chargers
  • Dan Granger, CEO founder of Oxford Road (Wharton XM)
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    • Advertising in LA helping acquire new customers and branding
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Refresh the Old and Tired (Notes from July 8 to 14, 2019) July 30, 2019

Posted by Anthony in Automation, Digital, experience, finance, Founders, Leadership, marketing, questions, social, Uncategorized, WomenInWork.
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For the abundant discussion on big tech, rise of tech and the valley’s obsession with all of it, there are quite a few industries that have had much longer staying power. They’ve proved their worth, decades and decades in. There are still railways. There are still cars. Manufacturing persists. CPG and everything that that entails last. Walmart, as much as people love (or don’t) Amazon, it’s still a lion’s share of commerce. Tech has improved and allowed them to have this staying power. Additionally, enabling improved efficiencies can allow new players in the industries to fundamentally change how they’re viewed.

Industries include tv – nonpartisan and bipartisan news with Carrie Sheffield. a16z gets into online from offline forms of services, restaurants to tech-enabled deliveries, as well as the rise of CAA and the agency fights. Then we have traffic and building with a consultant in that space. The next industry was making the legal space a little more transparent – provide a marketplace where information becomes symmetrical. I believe these are ways that simple pain points that can be improved through a technological lens give access to a value that wasn’t there before.

Hope you enjoy the shorter posting and the notes as more detailed. Check each of the wonderful people out!

  • Carrie Sheffield (@carriesheffield), co-founder of Bold TV (Wharton XM)
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    • Discussing bipartisan vs nonpartisan
    • Growing up in very conservative areas and then going to the coast – seeing both sides, especially media
      • How it was to be in media
    • Fake news as non-fact-checked as well as actually fake – ~70%+ considering bias
    • Intellectual diversity along with everything else – thinking differently vs looking diverse
      • Used example of Google AI conference canceling on a colleague who was a conservative, black woman
  • Chia Chin Lee, CEO of BigBox VR (Wharton XM)
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  • Initially trying VR and finding it sickening – didn’t work (Oculus)
    • Tried HTC Vive and fell in love – had a room set up and felt enthralled
    • Hardware and platform may get cheaper with tech
      • Opportunity lies in the software side – connecting to others and industries

 

  • Entrepreneurs, Then and Now (a16z 6/29/19)
    • With Marc, Ben, Stewart Butterfield (@stewart)
    • 10 year anniversary for a16z in late June – how has the environment changed?
    • Class of 2009 entrepreneurs were some of the most special: Todd McKinnon, Martin, Brian Czesky
      • To get to that point, needed to earn your stripes
    • O2O – online to offline (AirBNB, Uber, DoorDash, Postmates, etc….)
      • Founders that may be more operationally-focused since those require that
        • Maybe more similar to semiconductor founders from the 1970s, start of 80s
    • Dual discipline people as they got more involved in healthcare or bio-related
      • 10 years ago, Bio PhD wouldn’t know much on computers but now, dual PhD’s
    • Economics + CS – discussion of field of economics with empirical / quantitative economics compared to physics or formulas
      • New inventions by economists with machine learning and data
    • New ideas – thought venture firms had lost way, founders/operators that built businesses who would help out on boards
      • GPs started to get more abstract ideas, professionalized
      • Institution and ecosystem, network and fundamental staffing model – pay at a16z is different than other VC’s
    • If priority was to find best founders at the best opportunities, shouldn’t matter which stage they’re at – miss things, maybe
      • Skype deal early, multiple entry points – working with entrepreneur and being stage-agnostic
      • Tech bubble bursting – “can’t possibly start fund” – 2009 was Khosla and them
        • Mentioned ‘crusty’ or ‘grouchy’ VC’s
    • Much of the tech was at an inflection point – Salesforce as only SaaS, iPhone not quite there yet, Uber, Airbnb
      • Maybe the main response should be “No, this thing is stupid” as more accurate
      • Never thought it was a bubble – prices of companies are always incorrect (future performance, which nobody knows)
      • East coast vs West coast – not obvious, find what each argue about
    • How high is up? Online pet delivery, all actually happening
      • What are the exploratory bets? Are markets ready? Are people ready? Regulators?
        • Sometimes it’s the pioneer, sometimes it’s the last – time and effort for founders, personality, other
    • No individual company gets 25 years to prove something – maybe 5 years for a hypothesis
      • Morale issue losing faith or architecture issue – prior architecture (ex: mobile dev in 2002, system on archaic and aging-in-place)
      • VC’s will do the same thing – kid doesn’t know about failed experiments – VC freeze themselves out (ones who don’t know will often invest)
        • Can you learn lessons from failure – maybe you should learn nothing – “That doesn’t work.”
        • Edison as trying 3000 combinations before the filament, Wright brothers trying many
    • Copying the model from CAA – Michael Lovitz and describing the whole thing – not a collection of individuals
      • Operating platform, system and infrastructure with professionals across the network
      • Compounding advantage year over year – but why can’t they copy? They were paying themselves all the money
        • Nobody wanted to take pay cuts – 80% to hire everyone at such a scale
    • Top end venture investment – need something working (product-market fit, product)
      • Do they know what they’re doing? Can they do their job scaling?
      • Second-time or later founders – can do what they want and figure stuff out?
        • Problem may be with the good idea – investments on that idea or otherwise (fragmented idea with nothing)
      • Idea maze to find out what the ideas are – haven’t gone through that
    • VCs can’t invest more than 20% of funds that aren’t primary equity investments – crypto, for instance (vs RIA)
    • Deadwood as creation of city or state – horrifying obstacles
      • Why History is Always Wrong? (Taleb’s narrative fallacy, for instance – often more complex)
        • Don’t even know body, climate still (too complex) – can converge on science to Newton’s laws, others
      • Can’t Hurt Me by David Goggins
  • Scott Kuznicki, Pres and Managing Engineer at Modern Traffic Consultants (Wharton XM)
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    • Traffic control tech – California high speed rail vs autobahn style
      • Autonomous lanes?
    • Designated autonomous – level V vs others, depends on density and adoption
    • Thinks parking structures with flat tops could be converted or pay for cost
      • Multipurpose, solar, green or plants etc…
  • Risk, Incentive and Opportunity in Starting Co (FF 027, 20min VC)
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    • Daniel van Binsbergen, CEO and co-founder of Lexoo
      • Online marketplace connecting businesses and lawyers
    • Founded it in 2014, got an investment for $1.7mil
    • Friends always asking for referrals – kept a short list of them
      • Seemed great, “quoted $X – is that good?” – perception of complexities
      • Could put make a marketplace together for transparency
    • Kept 100% of his income boosts – got used to his training salary so it wasn’t as big a risk
      • No kids meant it may have been easier – really disappointed if you didn’t give it a go – decision already made
    • Legal space’s lack of progression in tech – incentives in wrong place
      • Hourly model still for law – if you spend less time on work, you would make less money
      • Risk-spotting for lawyers
      • Senior partners have heaviest voice – not exactly lining up for retirement in the near term vs long term
    • Highest goal may not be senior partner – fixed fee, sharing risk, more open to innovating with own practice
    • Lexoo initially – didn’t have tech skills for it, had a vision in his head but didn’t know best way
      • Didn’t build full-scale solution, did a forum for $15 website, form to fill in
      • Arrived in his email – he would then contact lawyers and fill in Word template – get their responses and quotes
      • Attached the lawyers’ quote and response to a doc and pdf and send back to clients
      • Automated only when he couldn’t handle the workload – hit limit on evenings and quit
        • Lawyers paid 10% commission on the quotes
    • Focus on business ideas – tech isn’t the big solution – market innovation (access to litigators)
    • Investors at Forward Investors – introduced through a friend who knew them through squash partner
      • Difference between FOMO on being convinced vs other investors who have a sense of opportunity
    • Fav book: The Mob Test – how to ask questions to get useful feedback, asking questions to customers in the wrong way
      • Would you use the product if it does X, Y, Z – most definitely? Instead of asking what the customer problems are.
    • A lot of work in Trello, for goals, and Sunrise app – Microsoft’s indispensable for calendar meetings
  • Facebook Bargaining Bots Invented a Language (Data Skeptic 6/21/19)
    • Auction theory and econometrics – equilibrium strategy
    • Neither agent is incentivized to change strategy if the other stays the same
    • Plateau of events in real life – baby, marriage, life changes, job, lease ends in time
    • Discount is a single floating-point decimal, ex 0.99 ^ t
      • Everything known – can calculate based on common knowledge and discounts
    • Gaussian distribution, mean 100k, 10k – ignore tail in negative and renormalize
      • Rubenstein one-sided incomplete
    • Game: don’t know private value now, but can have probability distribution
      • Update with Bayesian with behavior
      • Classic ML: corpus of examples of negotiation, mark up conveniently, objective function to maximize reward (post-agree)
      • Opportunity for RL – patterns for language utterances, insult or compliment or neither – recognizing strategy
        • Character level or nothing to ask it
        • Conversations for language you don’t understand and the reward – can you do this optimally?
    • RL + Roll-out with 8.3 to agent and 4.3 to other algorithms (94.4% agreement)
      • Roll-out was 7.3 and then RL – 7.1 and last place was 5.4 for likelihood model
    • Training data was in English, negotiating over 3 items – shortcut its job, RL wants the short path to reward
      • His example – loses points if you went to pits but to reward – chance at falling
      • Wasn’t worth it to move, so he had to do a penalty for not moving
      • Penalty for Facebook example was agents continued to communicate in English
      • Put a time constraint, maybe
  • Transfer Learning with Sebastian Ruder (@seb_ruder), D/S at DeepMind (Data Skeptic 7/8/19)
    deepmind-1

    • Generally, TL is leveraging knowledge from different tasks or domains to do better on another task
    • Not a lot of training data, may want to pretrain – models to train on imagenet, for instance
      • Language modeling to train on large corpora and use that on a bunch of other tasks
      • Source vs target data: task stays the same but can adapt between source and target, say sentiment of reviews
    • Classic benchmarking, may have ImageNet moments over last year – features of pretrained models applied on more powerful NLP
    • Google XLNet’s most current, BERT and ELMo as others – pace of improvement has been great
    • Difficulty of target tasks – can be good for 100 samples in target source on binary tasks, maybe, 50 even?
      • 200 examples per label, question-answering or reasoning, examples must be increased
      • If we can express target task as a conditional language modeling, can do fewer or even inference
    • Pretraining is costly due to large clusters on your own, but now can be public pretraining where you can finetune quickly
    • Area of common sense reasoning – infer what a question means or expressed depends on what may not be said
      • Grass is green, entity facts (son of a son), inquiries for language model – incorporate to modeling

Experimentation & Testing (Notes from March 25 – March 31, 2019) April 17, 2019

Posted by Anthony in Digital, experience, finance, global, Hiring, questions, social, training, TV, Uncategorized.
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I know, I know. It’s a bit of a cop out to use a Game of Thrones image on the back of the Season 8 premiere from Sunday. Sue me [please don’t]. And I’ll give credit to the image creator: Instagram @chartrdaily for the fun visualization. However, after listening to Pinnacle Sports’ Marco Blume, I couldn’t help after hearing deployment strategies for their prop bets on popular TV shows, such as who will be left on the Iron Throne or the ever popular “Who dies first?” props. They experiment, hypothesize, post a line with a limit (hedge risk) and let the market decide from there. And boom – we have the theme of the week!

Antoine Nussenbaum, of Felix Capital at the time, mentioned going from private equity to start-ups and venture funding where they had to decide between backing people or belief in the company. He got first-hand experience by starting a company with his wife, successfully gaining funding, and then exiting – only to fail with a different company that wasn’t scaling. How did he go through frameworks to decide on startups to fund or help?

Mark Suster gave his take on how he comes to investment funding – sales, technical skills and being aware of each. How did his entrepreneurship experience influence his framework for funding new start ups? Why is it that there is a sweet spot for amounts based on run rate? Experimenting, failing and adjusting.

Then I had listened to 2 data scientist / researchers in their discussions of NLP parts – what to test, what they assumed to be true, how to approach new methodology and testing this methodology. Is there a limit to the progression that can be made with NLP? Why might it be relevant to decide on testing state-of-the-art further? Then, ultimately, what’s the applications for how we can use that optimization to improve the current status quo?

I hope everyone checks out what may interest them – this was a fascinating and fun week. So much so, that I suggested to a few different students for them to check out different parts (granted, I do this often, but I was quite excited to share these ones).

Cheers!

  • Antoine Nussenbaum (@Nussenbaum), Principal and cofounder of Felix Capital (20min VC 084)
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    • Partner at Atlas Global prior, p/e fund that was part of GLG Partners
      • Working on digital early-stage, venture fund and helped startups bootstrap after missing the tech side
      • Miraki, Jellynote, Pave, Reedsy, and 31Dover as some of his best investments
      • Helped start Huckletree with his wife
        • Looked for investment of $80mln but got $120mln
    • Backing someone vs backing the company initially in early stage funds
    • Raised in Paris in international environment, lived in UK as well
    • Launched 2004 software-on-demand business with 2 friends “that was not scalable at all”
    • Did M&A in the UK after leaving software
    • Felix Capital at intersection of creativity + technology, lifestyle brands: ecommerce and media, enabling tech
      • Stages – flexible capital, but have made investments from $200k – $6mln, focus on Series A + B
      • Geographic – agnostic, as long as backing entrepreneurs
      • Advisory services and focused on helping their investment companies
    • More entrepreneurs that know the playbook and how they can build, grow and scale
      • Looking for more companies that can scale globally or expanding outside with proper funding
    • Using Triangle as an example – bathing suits on Instagram strategy and launching millions of product via digital
    • ProductHunt as a blog he gets lost in – 15 min of destruction
    • Lifestyle-related excitement: food side, better life, marketplaces
    • Hard Thing about Hard Things and Capital in the 21st Century – relationship of wealth and economic wealth
  • Mark Suster (@msuster), MP @ Upfront Ventures (20min VC 085)
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    • Was VP of PM at Salesforce.com before Upfront
    • Late 80s – had an interest in development as a student in college in the UK
      • Worked initially as a programmer at Anderson (Accenture) for 8 years
      • Entrepreneurship isn’t for everyone – better to start earlier, need to have a fundamental understanding of systems (coding)
        • Python, PHP, Ruby, JavaScript – not trying to become best developer – just knowing the systems
        • Sales experience would be second – telesales or customer support – ask CEO to do an hour a week of calls
    • Started 2 software companies – one in England and then Silicon Valley, selling both – backer brought him in to VC
      • Fred Wilson wasn’t an entrepreneur, but does give you the insight
    • Don’t get the sense of urgency with too long a time – 3 months vs 12 months
      • Too much capital creates laziness and shortcuts that lead to mistakes
      • 18 month run rate for capital – takes 3-4 months to raise (start with 6 months plus)
    • Wants to see early stage companies once a month, roughly.
    • $240mln fund – invest half into companies and reserve the other half for follow-ons
      • 3 year timeframe, $40mln with 5 partners – $8mln per partner
        • Series A, B rounds where each partner is doing 2-3 deals per year when avg is $3-5mln investment
    • On his blog, has the “11 Attributes of Entrepreneurs”
      • Best known post would be “Invest in Lines, not Dots” – x-axis as time, y-axis is performance (any given day, your dot)
        • Interactions create a line that matches a pattern and he can decide if he wants to do business
      • Not a big fan of deal days or investor days where you hype up a company because of this
    • 50 coffee meetings a year – once a week, if you meet 50 entrepreneurs a year, maybe you’ll become close with 5-10 of them
      • Single best introduction is from a portfolio company CEO for an investor
    • He knows and built software company – SaaS-space since he knows how to be helpful
      • Data and video tech industry (has 11 personal investments and 5 are video)
      • AgTech as an underappreciated industry so far – stays quiet until a few investments before hyping
    • Too much company, too much money and entrepreneurs clouding the market for everyone else
    • Book “Accidental Superpower”, how demographics and topology will drive the future and how areas grow
  • Marco Blume, Trading Director at Pinnacle Sports (DataFramed #54 2/18/19)
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    • Got into data science by “sheer force”, building quant team out from Excel going to R
      • Efficiency was by orders of magnitude since R was better than Excel
      • Could do anything with risk management, trading, sports
    • Pricing GoT, hot dog eating contest, pope election and making the lines
      • Use pricing and market analytics to let the people set prices
    • Risk management in general – maximize probability and hedging risk
      • Does the bottom line change? Does it affect anything? Regulations.
    • NBA where all teams have played each other – have a good idea of strength of teams
      • Soccer or world cup – not as much certainty with teams not always playing each other
      • Start of season has a lot more volatility and responsiveness to bets because of uncertainty
        • By end of season, bookmarkers have the price and knowledge, so they’re likely to increase risk
      • Bayesian updating
    • Goals to improve models, open new betting options to clients
      • Low margin, high volume bookmaker – little bit with a lot of options
      • Book of Superforecasting – group of people who are better at forecasting
        • Pays them already at Pinnacle – consultants, betting and paying the price
    • Much bigger R shop than Python at Pinnacle, active in the R community
      • R becoming more of an interfacing language and production language (vs C# or other), can use R-keras or plumbr
      • Teaching dplyr, rmarkdown and ggplot cover 95% of their work outside of specialists
    • GoT as one of his favorite bets
  • Matthew Peters (@mattthemathman), Research Scientist at AI2 – ElMo (Data Skeptic 3/29/2019)
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    • Research for the common good, Seattle, WA research
    • Language understanding tasks – ELMo (embeddings from Language Models)
    • PhD in Applied Math at UW, climate modeling and large scale data analysis
      • Went to mortgage modeling, tech industry with ML and Prod dev in Seattle
    • Trying to solve with very little human-annotated data, technical articles or peer-reviewed
      • Very difficult, very expensive to annotate – can you do NLP to help?
    • Word2vec as method for text to run ML on text, context meanings of say, bank
    • ELMo as training on lots of unlabeled data
      • Given a partial language fragment, language modeling predicts what can come next
      • Forward direction or backward direction (end of context), neural network architecture
    • Research community may want to use ELMo, commercial use to improve models already in prod
      • Pre-trained models available and open source
    • In the paper, evaluated NLP models on 6 tasks – sentiment, Q&A, info extraction, co-reference resolution, NL inference
      • Got significant improvements on results from the prior state-of-the-art models
      • Character-based vs word approach
        • Single system should process as much text as possible (morphology of the word, for instance)
    • Paper over a year old now but Bert was put up on ArXiv to improve upon ELMo (transformer architecture for efficiency)
      • Scaled the model that could be trained by many X’s, quality is tied to the size / capacity
      • Language modeling loss changed, as well (word removed from middle of sentence and predict before/after)
      • Large Bert models have computational restrictions – how far can you get by scaling the model
  • Kyle and early Data Science Hiring Processes (Data Skeptic 12/28/18)
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    • Success isn’t correlated with ability to give good advice
    • Conversion funnel for businesses: website that sells t-shirts, for instance
      • Tons of ways to bring people into the door / website (ads, social media campaign, ad clicks)
      • Register an account or put into cart (what %, track it, a/b test and improve)
      • Cart to checkout process (how many ppl? Credit card entered, goes through, etc…)
    • Do any sites convert faster than others? Keep track, find out why / focus on continuing it
    • Steps for job hire: video chat / task / phone screens / on-site next / offer
    • Resume should be pdf (doc may not open nicely on Mac or otherwise) – include GitHub
    • SVM – should have margins or kernel trick on resume (otherwise, don’t include it)
      •  Ex: ARIMA (auto-regressive integrated moving average) – time series data

Across the Board! Digitization, Health, Systems, and Strategy (Notes from Dec. 10 to 16) January 3, 2019

Posted by Anthony in Automation, experience, finance, global, medicine, Politics, questions, social, WomenInWork.
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Happy New Year’s, everyone! Hope people had a safe, relaxing and fun holiday. I also hope it provided some time to pause, reflect and wondering for what has happened and what may come in the next year.

I’ll preface my notes by informing you that they are short snippets, as you’ll observe. This was not necessarily by design, but necessity. I listened to a higher number than I should have in this week, as I needed to procrastinate – for what, you may ask? – for my MBA Final exam. Knowing how much drop-off in any online programs there is, I was hesitant in sharing this with others. Hate to tell someone you started something and then pause it, right? I sit here, now after receiving my Smartly Institute email saying I’ve completed the program and should receive the MBA Degree shortly!

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For those curious about the online program, reach out! Or maybe I’ll sure the exit survey that I am supposed to complete here.

Getting to my notes / snippets of what I listened to during that week, check below! I do think I’ll go back and listen to a couple of the segments fully because I found them very interesting. Whether it was strategy for Hasbro and eSports’ future or the author of Loneliest Generation or the Brightseed founder – some very interesting research and data being collected and reported on for whatever tickles your fancy. Whatever you may in interested in, there are plenty of overlaps. Know this.

  • Hasbro/Wizards strategy for esports, how DnD came about, Magic, (Work of Tomorrow, Wharton XM)
    • Magic was a request on finding a game between DnD games – revolutionized with trading card game
  • HBR article – business models for healthcare: https://hbr.org/2018/11/3-business-models-that-could-bring-million-dollar-cures-to-everyone
    • Business model needs to be reinvented if we’re to have million dollar treatments/cures
      • Ensure that insurance co’s are willing to cover expensive therapy – provide outcome-based results
      • Economics tend to be difficult if consumers are switching every 2 – 3 years with employer switches
    • HealthCoin securitizing improvements in health that can be passed from one stakeholder to another
      • Generates credit like a bond, can sell later to recoup cost
    • Annuity-based model for diseases/costly procedures, collect dividends after monthly premium investments
  • Million Dollar Women, Julia Pimsleur, (Women @ Work, WhartonXM)
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    • Changing mindset, upping skillset, expanding network
      • Trying to get them to think bigger and get rid of imposter syndrome
      • Develop their 8 pillars
      • Network by talking 1 on 1 with established mentors in the program
  • Mene founder (Wharton XM)
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    • Talking about the gold standard – Reagan’s temporary mission, haven’t come off
      • Inflation has been resigned to just sticking with the faux environment we’re in now – printing money
      • If gold wasn’t a store of value, it wouldn’t have risen from $30 – $1200+
  • Cotopaxi Founder, Davis Smith (Wharton XM)
    • Why SLC? He and his wife were deciding between Seattle and Salt Lake City – she chose SLC (having grown up in Seattle)
    • Created tribe / community of supporters
      • In Korea, someone shouted across the way Cotopaxi – to which he informed them he was the founder
      • Validation for what he had been working to create (although network effect bigger than anticipated)
    • Owning the omni-channels and why he chose D2C (virtual presence a la Warby Parker, Away, etc…)
      • Online and then a retail presence to own their own brand, before moving out to partner with places that help them reach others
      • Had to sell via Amazon as well to own that channel (otherwise someone would definitely be selling on that channel)
      • Partner with REI and other retailers in order to gain visible traction with places that had strong digital presence
        • Not the full catalog, but a few of the higher margin SKUs
      • Talked about how Vans originally rolled out to skaters/surf shops – top of pyramid before moving down to Zumies (frequented by those)
        • After a long while, they’re finally selling in JC Penny’s and others like it (well-established brand first)
    • Vertical digitalization above and then has a very lean business on the other side (outsources much of the fillers, suppliers, distribution)
      • He knows what he knows and then learns from those he works for – lets them do their thing
  • Author of Future Politics, Jamie Susskind (Wharton XM)
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    • Why do we insist on allowing politicians to not be knowledgeable in digital age
    • Odd that these are legislators attempting to update the digital companies
    • Should be obvious that we ask the people creating regulation should be involved in the technology that they’re attempting to design around (apparently our votes say otherwise)

 

 

 

  • Loneliest Generation author (not wsj one)
    • Costs an estimate $7bn, more than arthritis or high blood pressure combined
  • Brightseed founder, (Wharton XM, Thurs Dec 13)
    • Search engine with thousands of plants to identify empirical evidence of eastern medicine
      • Which plant consumption triggers improved physical / health properties?
      • Headed to market with one that improves liver toxin fat breakdown
    • Cheaper aspect because they’re plants compared to new drugs which can take hundreds of millions of 7+ years
    • Features of plants aligning with human function

Life is Global October 23, 2017

Posted by Anthony in education, experience, finance, global, Politics, questions, social.
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In just returning from Chile and having my 29th birthday, I did a ton of reflection over the last 2 weeks. Long flights, new places, peaceful heights & coming of age will force you to do this, if you don’t pause on your own to do it anyhow.

A word:
metacognition – dictionary.com has this as “higher-order thinking that enables understanding, analysis, and control of one’s cognitive processes, especially when engaged in learning.” I prefer a simpler “thinking about one’s own mental processes” .

Why do we do what we do? Some just act instinctively. Others act and then question why they acted. Yet there are some who will think, then act. There is a process by which everyone goes about their actions and thoughts – very few reflect on this process. Even fewer that look to change it for the better. Learning to think, approaching problems, coming up with solutions. Producing insights that can push forward or analyze why processes should be different.

In visiting with neighbors on my flights, shoulder-to-shoulder in immigration lines, Chilean natives, South American transplants from neighboring countries and visitors from across the world, there was a different consensus among the lot of them. Everyone had someplace else to be. Each person as different as the next. It was peaceful to not catch a news segment, comedy remark, or overhear a conversation about the active politics of the day. It’s overwhelming in the states, needlessly – and more importantly, rampant with misinformation which makes the deluge of politics ripe with uninformed, unintelligent thoughts. 7 days away – I believe I caught a single newspaper that had Trump on the cover and CNN one morning at the hotel mentioning a brief, 2 minute segment. Granted, I wasn’t looking for the conversations or seeking newspapers/tv’s, but still – there was some peace. Friends who have traveled abundantly over the past year to Europe/Canada/others have anecdotally mentioned that as one of the first things that arise in taxis/Ubers/people that become aware of a US citizen in their presence. No such bad luck in Mexico (my layover) or in Chile once I was there. There were more entertaining or productive discussions to be had. I’m sure this is a part of where one can direct a conversation, as well. People should be more cognizant of this, though I’m afraid politics have now dropped into the pantheon of ‘effortless’ conversation along with “how’s the weather?”, “did you see X” and a general “how’s work”?

Hopefully, as people grow and become more successful and comfortable in their lives, they would want to contribute something back – knowledge, money, mentorships and more. Often, there’s a line drawn between impact and how large of one can be made. This is less important, however, than making an impact regardless. We can make an impact in your core community – neighborhood, town or city, business community. Expand that out to affect multiple cities or a region – think Elon with LA’s tunnels, subway/metro/public transportation, bag ordinances or green movements – smart cities will eventually become a larger look as we go forward, as well. Outside of bigger projects like mentioned above, we can start a group or meet-up that gains members from the community in question – contribution of ideas that can go beyond infrastructural concepts.

Thinking larger (but not in the sense that it has to be bigger impact-wise), connection across counties, states, or the nation is important but more difficult to scale. Industries or sectors can be defined and aided by any one group or person that makes an impact beyond the immediate cases and permeates the outreaches from there. Then we have global scales – whether it’s advancing some technology or standard and bringing it to areas that may be impacted greatly with progression. There are tons of examples of all of these scales. People have different passions and shouldn’t be restricted or forced into doing something that doesn’t spark a fire in them to improve their lives (and hopefully, helping some others that they have a connection to in the process).

We live in a world where information is at our fingertips, a swipe and drag away on our phones. Barriers to entry continue to fall across all spectra. Get excited, people! Help yourself to help others.

Some things that I am jumping into and ones that I would love to hear ideas/talk to others about:
– mentorship with high school / college-level students with finding a passion or question ideas for how to progress forward
– a fun application to make it easier to connect local restaurants/bars with customers about their happy hours using OCR / Image-to-text from menu photos to populate database
– starting an investment fund that focuses on avoiding the nearly unavoidable ‘home bias’ as well as matching risk tolerance with proper returns – focusing on international availability and risk profile of uncorrelated assets
– new thought: possible website/application that will take multiple starting points (friends that live apart from each other) meeting at some location / flight destination in between for reasonable prices — multi-optimized Skyscanner/Hopper
– Payments/Vendors/AP/AR organizing software that will reduce burden and difficulty for companies with nontechnical backgrounds / capacity for process to be so intuitive that it won’t require more personnel or capital invested

 

Notes from Hirschhorn & Cuban March 27, 2017

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Listening to the Jason Hirschhorn interview with Mark Cuban  from the end of February (just pre-$SNAP IPO) —

Many great resources in all the current tech-hubs: SF & Silicon Valley, Los Angeles, Austin, and expanding those. Cuban makes a good point that people and ideas are easily created now in almost every area. There are places in the country that have MORE resources — events, companies, VC’s, funds, but building can be done everywhere (Cuban mentioned when he visits IU, he can stay in contact with them).

With less and less companies going public (mentioned ~9000 publicly listed in 2008, but < 4000 now), people are either scared of going public, or are getting their payouts directly from bigger companies (Cisco, Facebook, Amazon, Microsoft, Google, etc…).

Digital ad revenue for FB and Google – 85%+ market share. NFLX and AMZN are 2 biggest shares – hasn’t sold yet. Content providers – Disney, Netflix, and Amazon…. not many others. CONTENT is very difficult (Cuban mentioned Enron doc and winning awards, along with Good Night and Good Luck — hasn’t done any successful since). Content is the most difficult to maintain – very difficult to get past that giant hurdle, and these companies have the money to get above it.

Eventually got into a political discussion – using news / reactions / tweets to respond. HOW do we respond? Communicate and be patient – tough to change minds or reason – noted 52% of eligible voters didn’t vote. Trolls and dealing with internet comments – control public/private responses on twitter? Twitter must be hard-coded otherwise. Cuban mentioned an app that he’s going with – soon, machine-learning or machines will deal with the curation of information and conversation in digital platforms.

Talking about video – 7 year old son wanting to play flag football / baseball and how different it is now. Esports / watching vs watching tv (sports). His son didn’t want to watch sports / baseball / football, but wanted to play. There’s no indoctrination or religion for it anymore as we grew up on (and Cuban’s era earlier). Gaming as a big advantage in expanding NBA reach – NBA 2k and professional aspect of them since players have a deeper involvement / knowledge of the league with gaming.

The overall theme for today (not just this interview) – how can we get more young people interested in building out great ideas? The future of technology is rapidly accelerating but ideas will still be needed from the smartest people. Education seems to nerf expansive ideas – boxes people in that may be more capable, restricting opportunities. In my opinion, this is a huge flaw in the system overall.

Who Cares for Lip Service? May 23, 2016

Posted by Anthony in experience, Politics, questions, social, Uncategorized.
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There are hundreds of thousands of people that have good & great ideas.  Many of them work for someone else and don’t take action on those ideas. Some of the ones who have good ideas take them and try to build something. Not all succeed. The ones that do often had plans or people they could reach out to help them with a plan. Then they attempted/carried it out.  The ones that succeed often add value many times over.

Why is it different for elected office? Running for office should not simply be based on the platform of ideas you wish to change / better / create, but HOW candidates plan to put that in action. Actual plans. Business plan. Who is needed to help enact them / what is done / how to put it plan in motion / stakeholders / pros / cons. Sure, this would take time up front, but I believe that it could reduce the time to impact once someone was elected.

 
Let’s take an example. “Infrastructure must be improved” is a general positive thought and I don’t believe any candidates are against that. However, the latest research I’ve read said that of the funds designated as infrastructure-related, only 5% actually are used for ACTION in that frame. The rest is spent on funding boosters / change orders / unions (not exclusively).

Now, do I believe that a majority of voters would read through these plans? No, but of anyone that does, they would be better well-informed. And, debates or interviews could bring up the questions from people that did read through them and see holes or improvements or issues, to hopefully allow for a publicized process into the plans presented.

 
Until I see a candidate for ANY office lay something out like this, I’ll refrain from giving any vote of confidence or otherwise. Oh, and for any Bernie supporters that believe his site lays this out – it’s a step in the right direction, but not to the detail that elicits true action.

What do you think? Or is all of this just lip service?

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