Key take aways from Trust me I am lying

Trust me I am lying

The publication eco-system

  • Every content creator within the publication ecosystem is under immense pressure to produce content under the tightest deadline.
    • renumeration is based on number of articles per period time
    • eye balls are converted to advertising revenue
    • lots of copying happens
  • Media was once about protecting a new, on the web it is about building one
    • well defined scope matters
    • content that dives deep into its vertical matters
  • Headlines are the most important
  • Tools of the trade
    • lavish pictures
    • impostors, frauds and fake interviews
    • support for the underdog causes
    • anonymous sources
    • prominent coverage of high society and events
    • different age but same old tricks
  • On monetization
    • Advertising is the main driver of revenue
    • Subscription model focus on trusted source as opposed to advertising source
    • RSS got killed because it went against the interest of Advertisers
  • On the online medium
    • The demands of the medium forces the bloggers to act they way they are
    • Tim Berners Lee stacked new content on the top and the rest of the internet thus follows
    • Thus the need to constantly create new content

On Virality

  • The most powerful predictor of virality is how much anger an article evokes.
  • The most powerful predictor of what spreads online is anger
    • sensationalism
    • extremism
    • sex
    • scandal
    • hatred
  • Things must be negative but not too negative so as to incite action
  • Media needs to get you feeling negative so that you are more likely to share
  • Empty vessels are incline to snark so as to feel unjustifiably good about themselves

On reality

  • Chris Hedges
    • is complicated and boring
    • the masses are incapable and unwilling to handle its confusion
    • In an age of images, entertainment and instant emotional gratification, no one seeks honesty and gratification
  • Cognitive biases
    • we are bad at being sketical
      • availability biases
      • narrative fallacy
    • we are worst at correcting our wrong beliefs
      • social proofing
      • consistency biases
  • First decide what you are intending to do with the information you collected

Related readings

Key take aways from the Blockchain revolution

The Blockchain revolution
  • ensuring the integrity of data exchanged among these billions of devices without the need for a trusted third party
  • allow people that do not have access to the service of these third part into the digital economy
  • easier ability to get compensated for your work or ownership of digital property
  • Ronald Coase on types of costs
    • Searching cost
    • Coordination cost
    • Contracting cost
  • Dimensions of search
    • horizontal search – wide search across the web
    • vertical search – within a specific website
    • sequence – blockchain?
  • Innovation typically comes from the edge
    • monopolies have a lot of resources but lack the culture and will to explore, Yochai Benkler
    • This can be attributed to high levels of bureaucracy within the core

Related references

Key take aways from Exit Strategies for Entrepreneurs and Angel Investors

Early Exits
Early Exits

Key advice for Startups and emerging companies

  • Start small
  • Stay lean
  • Raise only the funding you really need and grow judiciously.
  • Alignment from all parties on exit strategy is extremely important
  • Best time to sell a company is when the future has never looked brighter

On VCs

  • Interest of VCs might not be aligned with interest of founders and angel investors
  • VCs need to satisfy the needs of their LPs
    • Need their successful companies to generate a minimum of 10-30X return for their fund to perform respectably, taking into account overall failure rates
    • They thus need to wait longer to exit and work their investments harder.
    • They are ok to accelerate the growth of their investments with their capital or blow it up quick for a capital right off. The latter helps minimize management overheads.
    • They will block a sale if the return multiples do not meet their expectation
  • VC return multiples of term sheet valuation
    • Series A – 10X return
    • Series B – 4-7X returns
    • SEries C – 2-4X returns
  • VC funds have been getting bigger overtime. The need to deploy their capital forces them to seek for opportunities where likelihoods are slim.
  • Companies with VC money tend to exit at year 16 on the average

On Angels

  • Invest much less money than VCs
    • USD10,000 to USD250,000
  • Happy to exit in a few years with a 3-5X return
  • In the 50s and 60s
  • prior successful entrepreneurs or senior executives
  • allocate around 5-10% for angel investing
  • has experience and inclination to be great mentors and valuable directors
  • Companies with angel only money tend to exit at year 4 on the average

Drivers of acquisition

  • trend has been dramatic shift towards earlier exits
  • huge amounts of cash on balance sheets of large corporation
  • growth in Private equity and buy out funds

Insights on Growth

  • The first USD10 to USD20 million valuation are the easiest and less challenge on the skills of the CEO
    • It is easy for young companies to maintain year on year compound annual growth rates of 100% or even 200%
  • Knowledge of how hard it is to be a CEO and lots of money in the bank is usually a huge deterrent for serial entrepreneurship.
  • VCs replace CEOs of 75% of companies within 18 months of their initial investments
    • Founder’s shares get trapped in an illiquid private company for another 5-10 years
  • Use a 2 year time horizon
    • year 1 develop technology
    • year 2 develop distribution

On valuation

  • A lot of factors that have the biggest impact on a company’s short term value fluctuation will be out of management’s control
  • The factors will also be unforeseen
  • General valuation multiples
    • SAAS companies are typically valued at 3-4 RR
    • Service body shops 0.5 of per staff revenue or PE ratio of 3-4

On sales process

  • Typically 4-5 months
  • CEOs must focus on the business to ensure metrics are at their best during the sales to maximize valuation
    • can add up to 10-20% more valuation
  • Until the very last phase of the sales, it is best to delegate the sales process to a professional
    • Business broker or M&A advisor – use them as the bad guy
      • big firms shoot for exit above USD100million
        • 2-3% of final value
      • boutique firms shoot for USD20-70 million
        • 4-6% of final exit value

Related references

  • Evolution and revolution as organizations grow, Larry Greiner Harvard Business School
  • Raising money: The canadian guide to successful business financing, Douglas Gray and Brian Nattrass
  • High Anxiety or Great Expectations, Bart Schachter and George Hoyem, Venture Capital Journal

Key take way from the Truth Machine, Michael J.Casey

The Truth Machine, Michael J.Casey
  • Blockchains are decentralized ledger systems
  • trust is a vital social resource, the truth lubricant of human interaction
  • human social organization comes from our ability to craft meaningful stories that we all believe, Yuval Noah Harrari
  • Engineering talent is still in severe shortage

Three great power centers in US

  • Technology, Silicon Valley
  • Finance, New York
  • Government, Washington

Use cases

  • Refugees are thrust into statelessness. Easy for criminal exploitation
  • Removing the central silos such Uber, Facebook and Twitter and replacing them with
  • barter trade, double entry
  • Support the scaling internet of things while avoiding one central controlling big brother
  • Self-sovereign identity
    • priorly done by government,
    • now done by Facebook Google and Twitter

Types of blockchains

  • private permissioned block chain to protect sensitive information
    • gate keeping prone to monopolies and oligopolies
  • permissionless block chain where management of data is done by individual themselves

Most popular chains

  • Ethereum
  • BitCoint

Moon shot scenario

  • Technology has freed humans from work
  • Human free to focus on creativity instead of the drudgery of work
  • Getting paid for creativity instead of it being captured by Facebook

Navigating the trough of sorrow

While I was reading through most of the success stories that were published on IndieHackers.com, it occurred to me that my project GetData.IO really took longer than most others to gain significant traction, a full 5 years actually.

The beginning

I first stumbled upon this project back in December 2012 when I was trying to solve two other problems of my own.

In my first problem, I was trying to identify the best stocks to buy on the Singapore Stock Exchange. While browsing through the stocks listed on their website, I soon realize that most stock exchanges as well as other financial websites gear their data presentation towards quick buy and sell behaviors. If you were looking to get data for granular analysis based on historical company performance as opposed to stock price movements, its like pulling teeth. Even then, important financial data I needed for decision making purposes were spread across multiple websites. This first problem lead me to write 2 web-scrappers, one for SGX.com and the other for Yahoo Finance, to extract data-sets which I later combined to help me with my investment decision-making process.

Once I happily parked my cash, I went back to working on my side project then. It was a travel portal which aggregates all the travel packages from tour agencies located in Southeast Asia. It was not long before I encountered my second problem… I had to write a bunch of web-scrapers again to pull data from vendor sites which do not have the APIs! Being forced to write my 3rd, 4th and maybe 5th web-scraper within a single week lead me to put on hold all work and step back to look at the bigger picture.

The insight

Being a web developer, and understanding how other web developers think, it quickly occurred to me the patterns that repeat themselves across webpage listings as well as nested webpages. This is especially true for naming conventions when it came to CSS styling. Developers tend to name their CSS classes the way they would actual physical objects in the world.

I figured if there existed a Semantic Query Language that is program independent, it would provide the benefit of querying webpages as if they were database tables while providing for clean abstraction of schema from the underlying technology. These two insights still prove true today after 6 years into the project.

The trough of sorrow

While the first 5 years depicted in the trend line above seem peaceful due to a lack of activity, it felt anything but peaceful. During this time, I was privately struggling with a bunch of challenges.

Team management mistakes and pre-mature scaling

First and foremost was team management. During the inception of the project my ex-schoolmate from years ago approached me to ask if there was any project that he could get involved in. Since I was working on this project, it was a natural that I would invited him to join the project. We soon got ourselves into an incubator in Singapore called JFDI.

In hindsight, while the experience provided us with general knowledge and friends, it really felt like going through a whirlwind. The most important piece of knowledge I came across during the incubation period was this book recommendation?—?The Founder’s dilemma. I wished I read the book before I made all of the mistakes I did.

There was a lot of hype (see the blip in mid-2013), tension and stress during the period between me and my ex-schoolmate. We went our separate ways due to differences in vision of how the project should proceed shortly after JDFI Demo Day. It was not long before I grew the team to a size of 6 and had it disbanded, realizing it was naive to scale in size before figuring out the monetization model.

Investor management mistakes

During this period of time, I also managed to commit a bunch of grave mistakes which I vow never to repeat again.

Mistake #1 was being too liberal with the stock allocation. When we incorporated the company, I was naive to believe the team would stay intact in its then configuration all the way through to the end. The cliff before vesting were to begin was only 3 months with full vesting occurring in 2 years. When my ex-schoolmate departed, the cap table was in a total mess with a huge chunk owned by a non-operator and none left for future employees without significant dilution of existing folks. This was the first serious red-flag when it came to fund raising.

Mistake #2 was giving away too much of the company for too little, too early in the project before achieving critical milestones. This was the second serious red-flag that really turned off follow up would-be investors.

Mistake #3 was not realizing the mindset difference of investors in Asia versus Silicon Valley, and thereafter picking the wrong geographical location (a.k.a network) to incubate the project. Incubating the project in the wrong network can be really detrimental to its future growth. Asian investors are inclined towards investing in applications that have a clear path to monetization while Silicon Valley investors are open towards investing in deep technology of which the path to monetization is yet apparent. During the subsequent period, I saw two similar projects incubated and successfully launched via Ycombinator.

The way I managed to fix the three problems above was to acquire funds I didn’t yet have by taking up a day job while relocating the project to back to the Valley’s network. I count my blessings for having friends who lend a helping hand when I was in a crunch.

Self-doubt

I remembered having the conversation with the head of the incubator two years into the project during my visit back to Singapore when he tried to convince me the project was going nowhere and I should just throw in the towel. I managed to convince him and more importantly myself to give it go for another 6 months till the end of the year.

I remember the evenings and weekends alone in my room while not working on my day job. In between spurts of coding, I would browse through the web or sit staring at the wall trying to envision how product market fit would look like. As what Steve Jobs mentioned once in his lecture, it felt like pushing against a wall with no signs of progress or movement whatever so. If anything, it was a lot of frustration, self-doubt and dejection. A few times, I felt like throwing in the towel and just giving up. For a period of 6 months in 2014, I actually stopped touching the code in total exasperation and just left the project running on auto-pilot, swearing to never look at it again.

The hiatus was not to last long though. A calling is just like the siren, even if somewhat faint sometimes, it calls out to you in the depths of night or when just strolling along on the serene beaches of California. It was not long before I was back on my MacBook plowing through the project again with renewed vigor.

First signs of life

It was mid-2015, the project was still not showing signs of any form of traction. I had by then stockpiled some cash from my day job and was starting to get interested in acquiring a piece of real estate with the hope of generating some cashflow to bootstrap the project while freeing up my own time. It was during this period of time that I got introduced to my friend’s room mate who also happened to be interested in real estate.

We started meeting on weekends and utilizing GetData.IO to gather real estate data for our real estate investment purposes. We were gonna perform machine learning for real estate. The scope of the project was really demanding. It was during this period of dog fooding that I started understanding how users would use GetData.IO. It was also then when I realized how shitty and unsuited the infrastructure was for the kind and scale of data harvesting required for projects like ours. It catalyzed a full rewrite of the infrastructure over the course of the next two years as well as brought the semantic query language to maturity.

Technical challenges

Similar to what Max Levchin mentioned in the book Founder’s at work, during this period of time there was always this fear in the back of my mind that I would encounter technical challenges which would be unsolvable.

The site would occasionally go down as we started scaling the volume of daily crawls. I would spend hours on the weekends digging through the logs to attempt at reproducing the error so as to understand the root cause. The operations was like a (data) pipeline, scaling one section of the pipeline without addressing further down sections would inevitably cause fissures and breakage. Some form of manual calculus in the head would always need to be performed to figure out the best configuration to balance the volume and the costs.

The number 1 hardest problem I had to tackle during this period of time was the problem of caching and storage. As the volume of data increase, storage cost increase and so did wait time required before data could be downloaded. This problem brought down the central database a few times.

After procrastinating for a while as the problem festered in mid-2016, I decided that it was to be the number 1 priority to be solved. I spend a good 4 months going to big-data and artificial intelligence MeetUps in the Bay Area to check out the types of solutions available for the problem faced. While no suitable solutions were found, the 4 months helped elicit corner cases to the problem which I did not previously thought of. I ended up building my own in-house solution.

Traction and Growth

An unforeseen side effect of solving the storage and caching problem was its effect on SEO. The effects on SEO would not be visible until mid-2017 when I started seeing increased volume of organic traffic to the site. As load times got reduced from more than a minute in some cases to less than 400 milliseconds seconds, the volume of pages indexed by bots would increase, accompanied by increase in volume of visitors and reduction in bounce rates.

Continued education

It was in early-2016 that I came across an article expounding the benefits of reading widely and deeply by Paul Graham which prompted me to pick up my hobby of reading again. A self-hack demonstrated to me by the same friend, who helped relocated me here to the Bay Area, which I pursued vehemently got me reading up to 1.5 books a week. These are books which I summarized on my personal blog for later reference. All the learnings developed my mental model of the world and greatly aided in the way I tackled the project.

Edmodo’s VP of engineering hammered in the importance of not boiling the ocean when attempting to solve a technical problem, of always being judicious with the use of resource during my time working as a tech-lead under his wing.  Another key lesson learned from him is that in some circumstances being liked and being effective do not go hand in hand. As the key decision maker, it is important to steadfastly practice the discipline of being effective.

Head of Design, Tim and Lukas helped me appreciate the significance of UX during my time working with them and how it ties to user psychology.

Edmodo’s CEO introduced us to mindfulness meditation late-2016 to help us weather through the turbulent times that was happening within the company then. It was rough. The practice which I have adopted till to date has helped keep my mind balance while navigating the uncertainties of the path I am treading.

Edmodo’s VP of product sent me for a course late-2017 which helped consolidate all the knowledge I have acquired till then into a coherent whole. The knowledge gained has helped greatly accelerated the progress of GetData.IO. During the same period, I was also introduced by him the Vipasanna mediation practice which coincidentally a large percentage of the management team practices.

One very significant paradigm shift I observed in myself during this period of continued education is the observed relationship between myself and the project. It has changed from an attitude of urgently needing to succeed at all cost to an attitude of open curiosity and fascination as one would an open ended science project.

Moving forward

To date, I have started working full time on the project again. GetData.IO has the support of more than 1,500 community members worldwide. Our mission is to turn the Web into the fully functional Giant Graph Database of Human Knowledge. Financially, with the help of our community members, the project is now self-sustaining. I feel grateful for all the support and lessons gained during this 6 year journey. I look forward to the journey ahead as I continue along my path.

Analysis of Saudi Arabia’s revenue model disruption and technology trends within Jordan

While speaking with a Saudi traveler in the desert of Wadi Rum, Jordan, its been observed that disruption of Saudi Arabia’s revenue model has forced much domestic changes within the country.

The prince has brought about drastic reforms in response to the disruption much to the chagrin of traditionalist hardliners. Women are now given the rights to drive vehicles and also work. For the first time ever Saudi’s were able to see Circ Du Soleil within their country. It can be speculated that these reforms are intended to double the total number of potential workforce in the country and get the thought process of the workforce more in sync with the rest of the world as Saudi Arabia gears its economy for a world that is no longer dependent on oil for energy.

Disruption examined using Micheal Porter’s 5 forces framework

Substitutes

The shale oil innovation has put a max cap on oil prices around the world at USD80 per barrel. Traditionally oil dependent countries within the OPEC could artificially restrict oil supply to drive up oil prices. However, post the era of innovation when such strategy employed, shale oil producers will immediately start pumping supplies into the market when price becomes viable.

New entrants

The Paris Climate agreement has catalyst a movement to shift away from oil to renewable sources of energy. Already China and India have became large players of solar energy. With innovation within this sector continuously driving down costs, it is likely the world will see an inflection point whereby solar energy becomes cheaper to produce than fossil fuel based energy.

Implications

A paradigm shift will occur amongst Saudi’s in relation to their attitude towards women as independent individuals with economic autonomy as opposed to individuals whose sole function is to be on the receiving side of male attention and care.

It remains unclear the impact of social media on the the upcoming shift within population.

Its also been observed via various sources within the Bay Area that Saudi Arabia is increasingly turning to investments in technology to drive the next stage of their economic growth.

Saudi Arabia is seen as the economic trend leader within region. It is likely their eventual model will get mimicked by other oil-dependent middle eastern countries.

Other notable observations within Jordan

Asian companies like Hyundai, Toyota, Kia, Nissan have been observed to dominate the region in terms of manufactured cars. The only other notable brands that are not Asian are Mercedes and Ford.

Android and Asian companies like Samsung, Huawei and Sony have been observed to dominate the region in terms of mobile computing.

Facebook is the only social network that has been observed to deeply penetrate the region. Majority of folks utilize WatsApp. Facebook is less commonly seen on phones of users.

User huddled over Android device in Wadi Rum. To understand their needs, technologist need to become more keenly familiar with the Android OS.

Related references

  • Only the paranoid survives, Andy Grove

Israel Hostels network – acquisition and engagement loops

Loop 1 – backpackers

When backpackers first arrive they are asked to stay at other hostels in the network by booking direct instead of via Booking.com

Backpackers can arrange for free boarding in exchange for volunteering to work. Working hours are typically work 7-8 hours for 5 days a week.

Backpackers get to stay for free in other hostels within the network.

Loop 2 – hostel operators

Hostel operators exchange cheaper inventory for what would have been more expensive staff head counts when they tap into this network of highly motivated network of volunteers who by nature of their demographic empathize the needs of their guests.

They are cobranded along with other hostels within the network. They are also cross promoted by other hostels within the network.