More on Productivity

Asher Umerie
3 years ago
What is Bionic Reading?
Senses help us navigate a complicated world. They shape our worldview - how we hear, smell, feel, and taste. People claim a sixth sense, an intuitive capacity that extends perception.
Our brain is a half-pool of grey and white matter that stores data from our senses. Brains provide us context, so zombies' obsession makes sense.
Bionic reading uses the brain's visual information and context to simplify text comprehension.
Stay with me.
What is Bionic Reading?
Bionic reading is a software application established by Swiss typographic designer Renato Casutt. The term honors the brain (bio) and technology's collaboration to better text comprehension.
The image above shows two similar paragraphs with bionic reading.
Notice anything yet?
This Twitter user did.
I did too...
Image text describes bionic reading-
New method to aid reading by using artificial fixation points. The reader focuses on the highlighted starting letters, and the brain completes the word.
How is Bionic Reading possible?
Do you remember seeing social media posts asking you to stare at a black dot for 30 seconds (or more)? You blink and see an after-image on your wall.
Our brains are skilled at identifying patterns and'seeing' familiar objects, therefore optical illusions are conceivable.
Brain and sight collaborate well. Text comprehension proves it.
Considering evolutionary patterns, humans' understanding skills may be cosmic luck.
Scientists don't know why people can read and write, but they do know what reading does to the brain.
One portion of your brain recognizes words, while another analyzes their meaning. Fixation, saccade, and linguistic transparency/opacity aid.
Let's explain some terms.
-
Fixation is how the eyes move when reading. It's where you look. If the eyes fixate less, a reader can read quicker. [Eye fixation is a physiological process](Eye fixation is a naturally occurring physiological process) impacted by the reader's vocabulary, vision span, and text familiarity.
-
Saccade - Pause and look around. That's a saccade. Rapid eye movements that alter the place of fixation, as reading text or looking around a room. They can happen willingly (when you choose) or instinctively, even when your eyes are fixed.
-
Linguistic transparency and opacity analyze how well a composite word or phrase may be deduced from its constituents.
The Bionic reading website compares these tools.
Text highlights lead the eye. Fixation, saccade, and opacity can transfer visual stimuli to text, changing typeface.
## Final Thoughts on Bionic Reading
I'm excited about how this could influence my long-term assimilation and productivity.
This technology is still in development, with prototypes working on only a few apps. Like any new tech, it will be criticized.
I'll be watching Bionic Reading closely. Comment on it!

Dr Mehmet Yildiz
2 years ago
How I train my brain daily for clarity and productivity.
I use a conceptual and practical system I developed decades ago as an example.
Since childhood, I've been interested in the brain-mind connection, so I developed a system using scientific breakthroughs, experiments, and the experiences of successful people in my circles.
This story provides a high-level overview of a custom system to inform and inspire readers. Creating a mind gym was one of my best personal and professional investments.
Such a complex system may not be possible for everyone or appear luxurious at first. However, the process and approach may help you find more accessible and viable solutions.
Visualizing the brain as a muscle, I learned to stimulate it with physical and mental exercises, applying a new mindset and behavioral changes.
My methods and practices may not work for others because we're all different. I focus on the approach's principles and highlights so you can create your own program.
Some create a conceptual and practical system intuitively, and others intellectually. Both worked. I see intellect and intuition as higher selves.
The mental tools I introduce are based on lifestyle changes and can be personalized by anyone, barring physical constraints or underlying health conditions.
Some people can't meditate despite wanting to due to mental constraints. This story lacks exceptions.
People's systems may vary. Many have used my tools successfully. All have scientific backing because their benefits attracted scientists. None are unethical or controversial.
My focus is cognition, which is the neocortex's ability. These practices and tools can affect the limbic and reptilian brain regions.
A previous article discussed brain health's biological aspects. This article focuses on psychology.
Thinking, learning, and remembering are cognitive abilities. Cognitive abilities determine our health and performance.
Cognitive health is the ability to think, concentrate, learn, and remember. Cognitive performance boosting involves various tools and processes. My system and protocols address cognitive health and performance.
As a biological organ, the brain's abilities decline with age, especially if not used regularly. Older people have more neurodegenerative disorders like dementia.
As aging is inevitable, I focus on creating cognitive reserves to remain mentally functional as we age and face mental decline or cognitive impairment.
My protocols focus on neurogenesis, or brain growth and maintenance. Neurons and connections can grow at any age.
Metacognition refers to knowing our cognitive abilities, like thinking about thinking and learning how to learn.
In the following sections, I provide an overview of my system, mental tools, and protocols.
This system summarizes my 50-year career. Some may find it too abstract, so I give examples.
First, explain the system. Section 2 introduces activities. Third, how to measure and maintain mental growth.
1 — Developed a practical mental gym.
The mental gym is a metaphor for the physical fitness gym to improve our mental muscles.
This concept covers brain and mind functionality. Integrated biological and psychological components.
I'll describe my mental gym so my other points make sense. My mental gym has physical and mental tools.
Mindfulness, meditation, visualization, self-conversations, breathing exercises, expressive writing, working in a flow state, reading, music, dance, isometric training, barefoot walking, cold/heat exposure, CBT, and social engagements are regular tools.
Dancing, walking, and thermogenesis are body-related tools. As the brain is part of the body and houses the mind, these tools can affect mental abilities such as attention, focus, memory, task switching, and problem-solving.
Different people may like different tools. I chose these tools based on my needs, goals, and lifestyle. They're just examples. You can choose tools that fit your goals and personality.
2 — Performed tasks regularly.
These tools gave me clarity. They became daily hobbies. Some I did alone, others with others.
Some examples: I meditate daily. Even though my overactive mind made daily meditation difficult at first, I now enjoy it. Meditation three times a day sharpens my mind.
Self-talk is used for self-therapy and creativity. Self-talk was initially difficult, but neurogenesis rewired my brain to make it a habit.
Cold showers, warm baths with Epsom salts, fasting, barefoot walks on the beach or grass, dancing, calisthenics, trampoline hopping, and breathing exercises increase my mental clarity, creativity, and productivity.
These exercises can increase BDNF, which promotes nervous system growth. They improve mental capacity and performance by increasing blood flow and brain oxygenation.
I use weekly and occasional activities like dry saunas, talking with others, and community activities.
These activities stimulate the brain and mind, improving performance and cognitive capacity.
3 — Measured progress, set growth goals.
Measuring progress helps us stay on track. Without data, it's hard to stay motivated. When we face inevitable setbacks, we may abandon our dreams.
I created a daily checklist for a spreadsheet with macros. I tracked how often and long I did each activity.
I measured my progress objectively and subjectively. In the progress spreadsheet, I noted my meditation hours and subjective feelings.
In another column, I used good, moderate, and excellent to get qualitative data. It took time and effort. Later, I started benefiting from this automated structure.
Creating a page for each activity, such as meditation, self-talk, cold showers, walking, expressive writing, personal interactions, etc., gave me empirical data I could analyze, modify, and graph to show progress.
Colored charts showed each area's strengths and weaknesses.
Strengths motivate me to continue them. Identifying weaknesses helped me improve them.
As the system matured, data recording became a habit and took less time. I saw the result immediately because I automated the charts when I entered daily data. Early time investment paid off later.
Mind Gym Benefits, Effective Use, and Progress Measuring
This concept helped me move from comfort to risk. I accept things as they are.
Turnarounds were made. I stopped feeling "Fight-Flight-Freeze" and maintained self-control.
I tamed my overactive amygdala by strengthening my brain. Stress and anxiety decreased. With these shifts, I accepted criticism and turned envy into admiration. Clarity improved.
When the cognitive part of the brain became stronger and the primitive part was tamed, managing thoughts and emotions became easier. My AQ increased. I learned to tolerate people, physical, mental, and emotional obstacles.
Accessing vast information sources in my subconscious mind through an improved RAS allowed me to easily tap into my higher self and recognize flaws in my lower self.
Summary
The brain loves patterns and routines, so habits help. Observing, developing, and monitoring habits mindfully can be beneficial. Mindfulness helps us achieve this goal systematically.
As body and mind are connected, we must consider both when building habits. Consistent and joyful practices can strengthen neurons and neural connections.
Habits help us accomplish more with less effort. Regularly using mental tools and processes can improve our cognitive health and performance as we age.
Creating daily habits to improve cognitive abilities can sharpen our minds and boost our well-being.
Some apps monitor our activities and behavior to help build habits. If you can't replicate my system, try these apps. Some smartwatches and fitness devices include them.
Set aside time each day for mental activities you enjoy. Regular scheduling and practice can strengthen brain regions and form habits. Once you form habits, tasks become easy.
Improving our minds is a lifelong journey. It's easier and more sustainable to increase our efforts daily, weekly, monthly, or annually.
Despite life's ups and downs, many want to remain calm and cheerful.
This valuable skill is unrelated to wealth or fame. It's about our mindset, fueled by our biological and psychological needs.
Here are some lessons I've learned about staying calm and composed despite challenges and setbacks.
1 — Tranquillity starts with observing thoughts and feelings.
2 — Clear the mental clutter and emotional entanglements with conscious breathing and gentle movements.
3 — Accept situations and events as they are with no resistance.
4 — Self-love can lead to loving others and increasing compassion.
5 — Count your blessings and cultivate gratitude.
Clear thinking can bring joy and satisfaction. It's a privilege to wake up with a healthy body and clear mind, ready to connect with others and serve them.
Thank you for reading my perspectives. I wish you a healthy and happy life.

Pen Magnet
3 years ago
Why Google Staff Doesn't Work
Sundar Pichai unveiled Simplicity Sprint at Google's latest all-hands conference.
To boost employee efficiency.
Not surprising. Few envisioned Google declaring a productivity drive.
Sunder Pichai's speech:
“There are real concerns that our productivity as a whole is not where it needs to be for the head count we have. Help me create a culture that is more mission-focused, more focused on our products, more customer focused. We should think about how we can minimize distractions and really raise the bar on both product excellence and productivity.”
The primary driver driving Google's efficiency push is:
Google's efficiency push follows 13% quarterly revenue increase. Last year in the same quarter, it was 62%.
Market newcomers may argue that the previous year's figure was fuelled by post-Covid reopening and growing consumer spending. Investors aren't convinced. A promising company like Google can't afford to drop so quickly.
Google’s quarterly revenue growth stood at 13%, against 62% in last year same quarter.
Google isn't alone. In my recent essay regarding 2025 programmers, I warned about the economic downturn's effects on FAAMG's workforce. Facebook had suspended hiring, and Microsoft had promised hefty bonuses for loyal staff.
In the same article, I predicted Google's troubles. Online advertising, especially the way Google and Facebook sell it using user data, is over.
FAAMG and 2nd rung IT companies could be the first to fall without Post-COVID revival and uncertain global geopolitics.
Google has hardly ever discussed effectiveness:
Apparently openly.
Amazon treats its employees like robots, even in software positions. It has significant turnover and a terrible reputation as a result. Because of this, it rarely loses money due to staff productivity.
Amazon trumps Google. In reality, it treats its employees poorly.
Google was the founding father of the modern-day open culture.
Larry and Sergey Google founded the IT industry's Open Culture. Silicon Valley called Google's internal democracy and transparency near anarchy. Management rarely slammed decisions on employees. Surveys and internal polls ensured everyone knew the company's direction and had a vote.
20% project allotment (weekly free time to build own project) was Google's open-secret innovation component.
After Larry and Sergey's exit in 2019, this is Google's first profitability hurdle. Only Google insiders can answer these questions.
Would Google's investors compel the company's management to adopt an Amazon-style culture where the developers are treated like circus performers?
If so, would Google follow suit?
If so, how does Google go about doing it?
Before discussing Google's likely plan, let's examine programming productivity.
What determines a programmer's productivity is simple:
How would we answer Google's questions?
As a programmer, I'm more concerned about Simplicity Sprint's aftermath than its economic catalysts.
Large organizations don't care much about quarterly and annual productivity metrics. They have 10-year product-launch plans. If something seems horrible today, it's likely due to someone's lousy judgment 5 years ago who is no longer in the blame game.
Deconstruct our main question.
How exactly do you change the culture of the firm so that productivity increases?
How can you accomplish that without affecting your capacity to profit? There are countless ways to increase output without decreasing profit.
How can you accomplish this with little to no effect on employee motivation? (While not all employers care about it, in this case we are discussing the father of the open company culture.)
How do you do it for a 10-developer IT firm that is losing money versus a 1,70,000-developer organization with a trillion-dollar valuation?
When implementing a large-scale organizational change, success must be carefully measured.
The fastest way to do something is to do it right, no matter how long it takes.
You require clearly-defined group/team/role segregation and solid pass/fail matrices to:
You can give performers rewards.
Ones that are average can be inspired to improve
Underachievers may receive assistance or, in the worst-case scenario, rehabilitation
As a 20-year programmer, I associate productivity with greatness.
Doing something well, no matter how long it takes, is the fastest way to do it.
Let's discuss a programmer's productivity.
Why productivity is a strange term in programming:
Productivity is work per unit of time.
Money=time This is an economic proverb. More hours worked, more pay. Longer projects cost more.
As a buyer, you desire a quick supply. As a business owner, you want employees who perform at full capacity, creating more products to transport and boosting your profits.
All economic matrices encourage production because of our obsession with it. Productivity is the only organic way a nation may increase its GDP.
Time is money — is not just a proverb, but an economical fact.
Applying the same productivity theory to programming gets problematic. An automating computer. Its capacity depends on the software its master writes.
Today, a sophisticated program can process a billion records in a few hours. Creating one takes a competent coder and the necessary infrastructure. Learning, designing, coding, testing, and iterations take time.
Programming productivity isn't linear, unlike manufacturing and maintenance.
Average programmers produce code every day yet miss deadlines. Expert programmers go days without coding. End of sprint, they often surprise themselves by delivering fully working solutions.
Reversing the programming duties has no effect. Experts aren't needed for productivity.
These patterns remind me of an XKCD comic.
Programming productivity depends on two factors:
The capacity of the programmer and his or her command of the principles of computer science
His or her productive bursts, how often they occur, and how long they last as they engineer the answer
At some point, productivity measurement becomes Schrödinger’s cat.
Product companies measure productivity using use cases, classes, functions, or LOCs (lines of code). In days of data-rich source control systems, programmers' merge requests and/or commits are the most preferred yardstick. Companies assess productivity by tickets closed.
Every organization eventually has trouble measuring productivity. Finer measurements create more chaos. Every measure compares apples to oranges (or worse, apples with aircraft.) On top of the measuring overhead, the endeavor causes tremendous and unnecessary stress on teams, lowering their productivity and defeating its purpose.
Macro productivity measurements make sense. Amazon's factory-era management has done it, but at great cost.
Google can pull it off if it wants to.
What Google meant in reality when it said that employee productivity has decreased:
When Google considers its employees unproductive, it doesn't mean they don't complete enough work in the allotted period.
They can't multiply their work's influence over time.
Programmers who produce excellent modules or products are unsure on how to use them.
The best data scientists are unable to add the proper parameters in their models.
Despite having a great product backlog, managers struggle to recruit resources with the necessary skills.
Product designers who frequently develop and A/B test newer designs are unaware of why measures are inaccurate or whether they have already reached the saturation point.
Most ignorant: All of the aforementioned positions are aware of what to do with their deliverables, but neither their supervisors nor Google itself have given them sufficient authority.
So, Google employees aren't productive.
How to fix it?
Business analysis: White suits introducing novel items can interact with customers from all regions. Track analytics events proactively, especially the infrequent ones.
SOLID, DRY, TEST, and AUTOMATION: Do less + reuse. Use boilerplate code creation. If something already exists, don't implement it yourself.
Build features-building capabilities: N features are created by average programmers in N hours. An endless number of features can be built by average programmers thanks to the fact that expert programmers can produce 1 capability in N hours.
Work on projects that will have a positive impact: Use the same algorithm to search for images on YouTube rather than the Mars surface.
Avoid tasks that can only be measured in terms of time linearity at all costs (if a task can be completed in N minutes, then M copies of the same task would cost M*N minutes).
In conclusion:
Software development isn't linear. Why should the makers be measured?
Notation for The Big O
I'm discussing a new way to quantify programmer productivity. (It applies to other professions, but that's another subject)
The Big O notation expresses the paradigm (the algorithmic performance concept programmers rot to ace their Google interview)
Google (or any large corporation) can do this.
Sort organizational roles into categories and specify their impact vs. time objectives. A CXO role's time vs. effect function, for instance, has a complexity of O(log N), meaning that if a CEO raises his or her work time by 8x, the result only increases by 3x.
Plot the influence of each employee over time using the X and Y axes, respectively.
Add a multiplier for Y-axis values to the productivity equation to make business objectives matter. (Example values: Support = 5, Utility = 7, and Innovation = 10).
Compare employee scores in comparable categories (developers vs. devs, CXOs vs. CXOs, etc.) and reward or help employees based on whether they are ahead of or behind the pack.
After measuring every employee's inventiveness, it's straightforward to help underachievers and praise achievers.
Example of a Big(O) Category:
If I ran Google (God forbid, its worst days are far off), here's how I'd classify it. You can categorize Google employees whichever you choose.
The Google interview truth:
O(1) < O(log n) < O(n) < O(n log n) < O(n^x) where all logarithmic bases are < n.
O(1): Customer service workers' hours have no impact on firm profitability or customer pleasure.
CXOs Most of their time is spent on travel, strategic meetings, parties, and/or meetings with minimal floor-level influence. They're good at launching new products but bad at pivoting without disaster. Their directions are being followed.
Devops, UX designers, testers Agile projects revolve around deployment. DevOps controls the levers. Their automation secures results in subsequent cycles.
UX/UI Designers must still prototype UI elements despite improved design tools.
All test cases are proportional to use cases/functional units, hence testers' work is O(N).
Architects Their effort improves code quality. Their right/wrong interference affects product quality and rollout decisions even after the design is set.
Core Developers Only core developers can write code and own requirements. When people understand and own their labor, the output improves dramatically. A single character error can spread undetected throughout the SDLC and cost millions.
Core devs introduce/eliminate 1000x bugs, refactoring attempts, and regression. Following our earlier hypothesis.
The fastest way to do something is to do it right, no matter how long it takes.
Conclusion:
Google is at the liberal extreme of the employee-handling spectrum
Microsoft faced an existential crisis after 2000. It didn't choose Amazon's data-driven people management to revitalize itself.
Instead, it entrusted developers. It welcomed emerging technologies and opened up to open source, something it previously opposed.
Google is too lax in its employee-handling practices. With that foundation, it can only follow Amazon, no matter how carefully.
Any attempt to redefine people's measurements will affect the organization emotionally.
The more Google compares apples to apples, the higher its chances for future rebirth.
You might also like

Mircea Iosif
3 years ago
How To Start An Online Business That Will Be Profitable Without Investing A Lot Of Time
Don't know how to start an online business? Here's a guide. By following these recommendations, you can build a lucrative and profitable online business.
What Are Online Businesses Used For?
Most online businesses are websites. A self-created, self-managed website. You may sell things and services online.
To establish an internet business, you must locate a host and set up accounts with numerous companies. Once your accounts are set up, you may start publishing content and selling products or services.
How to Make Money from Your Online Business
Advertising and marketing are the best ways to make money online. You must develop strategies to contact new customers and generate leads. Make sure your website is search engine optimized so people can find you online.
Top 5 Online Business Tips for Startups:
1. Know your target audience's needs.
2. Make your website as appealing as possible.
3. Generate leads and sales with marketing.
4. Track your progress and learn from your mistakes to improve.
5. Be prepared to expand into new markets or regions.
How to Launch a Successful Online Business Without Putting in a Lot of Work
Build with a solid business model to start a profitable online business. By using these tips, you can start your online business without paying much.
First, develop a user-friendly website. You can use an internet marketing platform or create your own website. Once your website is live, optimize it for search engines and add relevant content.
Second, sell online. This can be done through ads or direct sales to website visitors. Finally, use social media to advertise your internet business. By accomplishing these things, you'll draw visitors to your website and make money.
When launching a business, invest long-term. This involves knowing your goals and how you'll pay for them. Volatility can have several effects on your business. If you offer things online, you may need to examine if the market is ready for them.
Invest wisely
Investing all your money in one endeavor can lead to too much risk and little ROI. Diversify your investments to take advantage of all available chances. So, your investments won't encounter unexpected price swings and you'll be immune to economic upheavals.
Financial news updates
When launching or running a thriving online business, financial news is crucial. By knowing current trends and upcoming developments, you can keep your business lucrative.
Keeping up with financial news can also help you avoid potential traps that could harm your bottom line. If you don't know about new legislation that could affect your industry, potential customers may choose another store when they learn about your business's problems.
Volatility ahead
You should expect volatility in the financial sector. Without a plan for coping with volatility, you could run into difficulty. If your organization relies on client input, you may not be able to exploit customer behavior shifts.
Your company could go bankrupt if you don't understand how fickle the stock market can be. By preparing for volatility, you can ensure your organization survives difficult times and market crashes.
Conclusion
Many internet businesses can be profitable. Start quickly with a few straightforward steps. Diversify your investments, follow financial news, and be prepared for volatility to develop a successful business.
Thanks for reading!

Vitalik
3 years ago
An approximate introduction to how zk-SNARKs are possible (part 1)
You can make a proof for the statement "I know a secret number such that if you take the word ‘cow', add the number to the end, and SHA256 hash it 100 million times, the output starts with 0x57d00485aa". The verifier can verify the proof far more quickly than it would take for them to run 100 million hashes themselves, and the proof would also not reveal what the secret number is.
In the context of blockchains, this has 2 very powerful applications: Perhaps the most powerful cryptographic technology to come out of the last decade is general-purpose succinct zero knowledge proofs, usually called zk-SNARKs ("zero knowledge succinct arguments of knowledge"). A zk-SNARK allows you to generate a proof that some computation has some particular output, in such a way that the proof can be verified extremely quickly even if the underlying computation takes a very long time to run. The "ZK" part adds an additional feature: the proof can keep some of the inputs to the computation hidden.
You can make a proof for the statement "I know a secret number such that if you take the word ‘cow', add the number to the end, and SHA256 hash it 100 million times, the output starts with 0x57d00485aa". The verifier can verify the proof far more quickly than it would take for them to run 100 million hashes themselves, and the proof would also not reveal what the secret number is.
In the context of blockchains, this has two very powerful applications:
- Scalability: if a block takes a long time to verify, one person can verify it and generate a proof, and everyone else can just quickly verify the proof instead
- Privacy: you can prove that you have the right to transfer some asset (you received it, and you didn't already transfer it) without revealing the link to which asset you received. This ensures security without unduly leaking information about who is transacting with whom to the public.
But zk-SNARKs are quite complex; indeed, as recently as in 2014-17 they were still frequently called "moon math". The good news is that since then, the protocols have become simpler and our understanding of them has become much better. This post will try to explain how ZK-SNARKs work, in a way that should be understandable to someone with a medium level of understanding of mathematics.
Why ZK-SNARKs "should" be hard
Let us take the example that we started with: we have a number (we can encode "cow" followed by the secret input as an integer), we take the SHA256 hash of that number, then we do that again another 99,999,999 times, we get the output, and we check what its starting digits are. This is a huge computation.
A "succinct" proof is one where both the size of the proof and the time required to verify it grow much more slowly than the computation to be verified. If we want a "succinct" proof, we cannot require the verifier to do some work per round of hashing (because then the verification time would be proportional to the computation). Instead, the verifier must somehow check the whole computation without peeking into each individual piece of the computation.
One natural technique is random sampling: how about we just have the verifier peek into the computation in 500 different places, check that those parts are correct, and if all 500 checks pass then assume that the rest of the computation must with high probability be fine, too?
Such a procedure could even be turned into a non-interactive proof using the Fiat-Shamir heuristic: the prover computes a Merkle root of the computation, uses the Merkle root to pseudorandomly choose 500 indices, and provides the 500 corresponding Merkle branches of the data. The key idea is that the prover does not know which branches they will need to reveal until they have already "committed to" the data. If a malicious prover tries to fudge the data after learning which indices are going to be checked, that would change the Merkle root, which would result in a new set of random indices, which would require fudging the data again... trapping the malicious prover in an endless cycle.
But unfortunately there is a fatal flaw in naively applying random sampling to spot-check a computation in this way: computation is inherently fragile. If a malicious prover flips one bit somewhere in the middle of a computation, they can make it give a completely different result, and a random sampling verifier would almost never find out.
It only takes one deliberately inserted error, that a random check would almost never catch, to make a computation give a completely incorrect result.
If tasked with the problem of coming up with a zk-SNARK protocol, many people would make their way to this point and then get stuck and give up. How can a verifier possibly check every single piece of the computation, without looking at each piece of the computation individually? There is a clever solution.
see part 2

Sanjay Priyadarshi
2 years ago
Using Ruby code, a programmer created a $48,000,000,000 product that Elon Musk admired.
Unexpected Success
Shopify CEO and co-founder Tobias Lutke. Shopify is worth $48 billion.
World-renowned entrepreneur Tobi
Tobi never expected his first online snowboard business to become a multimillion-dollar software corporation.
Tobi founded Shopify to establish a 20-person company.
The publicly traded corporation employs over 10,000 people.
Here's Tobi Lutke's incredible story.
Elon Musk tweeted his admiration for the Shopify creator.
30-October-2019.
Musk praised Shopify founder Tobi Lutke on Twitter.
Happened:
Explore this programmer's journey.
What difficulties did Tobi experience as a young child?
Germany raised Tobi.
Tobi's parents realized he was smart but had trouble learning as a toddler.
Tobi was learning disabled.
Tobi struggled with school tests.
Tobi's learning impairments were undiagnosed.
Tobi struggled to read as a dyslexic.
Tobi also found school boring.
Germany's curriculum didn't inspire Tobi's curiosity.
“The curriculum in Germany was taught like here are all the solutions you might find useful later in life, spending very little time talking about the problem…If I don’t understand the problem I’m trying to solve, it’s very hard for me to learn about a solution to a problem.”
Studying computer programming
After tenth grade, Tobi decided school wasn't for him and joined a German apprenticeship program.
This curriculum taught Tobi software engineering.
He was an apprentice in a small Siemens subsidiary team.
Tobi worked with rebellious Siemens employees.
Team members impressed Tobi.
Tobi joined the team for this reason.
Tobi was pleased to get paid to write programming all day.
His life could not have been better.
Devoted to snowboarding
Tobi loved snowboarding.
He drove 5 hours to ski at his folks' house.
His friends traveled to the US to snowboard when he was older.
However, the cheap dollar conversion rate led them to Canada.
2000.
Tobi originally decided to snowboard instead than ski.
Snowboarding captivated him in Canada.
On the trip to Canada, Tobi encounters his wife.
Tobi meets his wife Fiona McKean on his first Canadian ski trip.
They maintained in touch after the trip.
Fiona moved to Germany after graduating.
Tobi was a startup coder.
Fiona found work in Germany.
Her work included editing, writing, and academics.
“We lived together for 10 months and then she told me that she need to go back for the master's program.”
With Fiona, Tobi immigrated to Canada.
Fiona invites Tobi.
Tobi agreed to move to Canada.
Programming helped Tobi move in with his girlfriend.
Tobi was an excellent programmer, therefore what he did in Germany could be done anywhere.
He worked remotely for his German employer in Canada.
Tobi struggled with remote work.
Due to poor communication.
No slack, so he used email.
Programmers had trouble emailing.
Tobi's startup was developing a browser.
After the dot-com crash, individuals left that startup.
It ended.
Tobi didn't intend to work for any major corporations.
Tobi left his startup.
He believed he had important skills for any huge corporation.
He refused to join a huge corporation.
Because of Siemens.
Tobi learned to write professional code and about himself while working at Siemens in Germany.
Siemens culture was odd.
Employees were distrustful.
Siemens' rigorous dress code implies that the corporation doesn't trust employees' attire.
It wasn't Tobi's place.
“There was so much bad with it that it just felt wrong…20-year-old Tobi would not have a career there.”
Focused only on snowboarding
Tobi lived in Ottawa with his girlfriend.
Canada is frigid in winter.
Ottawa's winters last.
Almost half a year.
Tobi wanted to do something worthwhile now.
So he snowboarded.
Tobi began snowboarding seriously.
He sought every snowboarding knowledge.
He researched the greatest snowboarding gear first.
He created big spreadsheets for snowboard-making technologies.
Tobi grew interested in selling snowboards while researching.
He intended to sell snowboards online.
He had no choice but to start his own company.
A small local company offered Tobi a job.
Interested.
He must sign papers to join the local company.
He needed a work permit when he signed the documents.
Tobi had no work permit.
He was allowed to stay in Canada while applying for permanent residency.
“I wasn’t illegal in the country, but my state didn’t give me a work permit. I talked to a lawyer and he told me it’s going to take a while until I get a permanent residency.”
Tobi's lawyer told him he cannot get a work visa without permanent residence.
His lawyer said something else intriguing.
Tobis lawyer advised him to start a business.
Tobi declined this local company's job offer because of this.
Tobi considered opening an internet store with his technical skills.
He sold snowboards online.
“I was thinking of setting up an online store software because I figured that would exist and use it as a way to sell snowboards…make money while snowboarding and hopefully have a good life.”
What brought Tobi and his co-founder together, and how did he support Tobi?
Tobi lived with his girlfriend's parents.
In Ottawa, Tobi encounters Scott Lake.
Scott was Tobis girlfriend's family friend and worked for Tobi's future employer.
Scott and Tobi snowboarded.
Tobi pitched Scott his snowboard sales software idea.
Scott liked the idea.
They planned a business together.
“I was looking after the technology and Scott was dealing with the business side…It was Scott who ended up developing relationships with vendors and doing all the business set-up.”
Issues they ran into when attempting to launch their business online
Neither could afford a long-term lease.
That prompted their online business idea.
They would open a store.
Tobi anticipated opening an internet store in a week.
Tobi seeks open-source software.
Most existing software was pricey.
Tobi and Scott couldn't afford pricey software.
“In 2004, I was sitting in front of my computer absolutely stunned realising that we hadn’t figured out how to create software for online stores.”
They required software to:
to upload snowboard images to the website.
people to look up the types of snowboards that were offered on the website. There must be a search feature in the software.
Online users transmit payments, and the merchant must receive them.
notifying vendors of the recently received order.
No online selling software existed at the time.
Online credit card payments were difficult.
How did they advance the software while keeping expenses down?
Tobi and Scott needed money to start selling snowboards.
Tobi and Scott funded their firm with savings.
“We both put money into the company…I think the capital we had was around CAD 20,000(Canadian Dollars).”
Despite investing their savings.
They minimized costs.
They tried to conserve.
No office rental.
They worked in several coffee shops.
Tobi lived rent-free at his girlfriend's parents.
He installed software in coffee cafes.
How were the software issues handled?
Tobi found no online snowboard sales software.
Two choices remained:
Change your mind and try something else.
Use his programming expertise to produce something that will aid in the expansion of this company.
Tobi knew he was the sole programmer working on such a project from the start.
“I had this realisation that I’m going to be the only programmer who has ever worked on this, so I don’t have to choose something that lots of people know. I can choose just the best tool for the job…There is been this programming language called Ruby which I just absolutely loved ”
Ruby was open-source and only had Japanese documentation.
Latin is the source code.
Tobi used Ruby twice.
He assumed he could pick the tool this time.
Why not build with Ruby?
How did they find their first time operating a business?
Tobi writes applications in Ruby.
He wrote the initial software version in 2.5 months.
Tobi and Scott founded Snowdevil to sell snowboards.
Tobi coded for 16 hours a day.
His lifestyle was unhealthy.
He enjoyed pizza and coke.
“I would never recommend this to anyone, but at the time there was nothing more interesting to me in the world.”
Their initial purchase and encounter with it
Tobi worked in cafes then.
“I was working in a coffee shop at this time and I remember everything about that day…At some time, while I was writing the software, I had to type the email that the software would send to tell me about the order.”
Tobi recalls everything.
He checked the order on his laptop at the coffee shop.
Pennsylvanian ordered snowboard.
Tobi walked home and called Scott. Tobi told Scott their first order.
They loved the order.
How were people made aware about Snowdevil?
2004 was very different.
Tobi and Scott attempted simple website advertising.
Google AdWords was new.
Ad clicks cost 20 cents.
Online snowboard stores were scarce at the time.
Google ads propelled the snowdevil brand.
Snowdevil prospered.
They swiftly recouped their original investment in the snowboard business because to its high profit margin.
Tobi and Scott struggled with inventories.
“Snowboards had really good profit margins…Our biggest problem was keeping inventory and getting it back…We were out of stock all the time.”
Selling snowboards returned their investment and saved them money.
They did not appoint a business manager.
They accomplished everything alone.
Sales dipped in the spring, but something magical happened.
Spring sales plummeted.
They considered stocking different boards.
They naturally wanted to add boards and grow the business.
However, magic occurred.
Tobi coded and improved software while running Snowdevil.
He modified software constantly. He wanted speedier software.
He experimented to make the software more resilient.
Tobi received emails requesting the Snowdevil license.
They intended to create something similar.
“I didn’t stop programming, I was just like Ok now let me try things, let me make it faster and try different approaches…Increasingly I got people sending me emails and asking me If I would like to licence snowdevil to them. People wanted to start something similar.”
Software or skateboards, your choice
Scott and Tobi had to choose a hobby in 2005.
They might sell alternative boards or use software.
The software was a no-brainer from demand.
Daniel Weinand is invited to join Tobi's business.
Tobis German best friend is Daniel.
Tobi and Scott chose to use the software.
Tobi and Scott kept the software service.
Tobi called Daniel to invite him to Canada to collaborate.
Scott and Tobi had quit snowboarding until then.
How was Shopify launched, and whence did the name come from?
The three chose Shopify.
Named from two words.
First:
Shop
Final part:
Simplify
Shopify
Shopify's crew has always had one goal:
creating software that would make it simple and easy for people to launch online storefronts.
Launched Shopify after raising money for the first time.
Shopify began fundraising in 2005.
First, they borrowed from family and friends.
They needed roughly $200k to run the company efficiently.
$200k was a lot then.
When questioned why they require so much money. Tobi told them to trust him with their goals. The team raised seed money from family and friends.
Shopify.com has a landing page. A demo of their goal was on the landing page.
In 2006, Shopify had about 4,000 emails.
Shopify rented an Ottawa office.
“We sent a blast of emails…Some people signed up just to try it out, which was exciting.”
How things developed after Scott left the company
Shopify co-founder Scott Lake left in 2008.
Scott was CEO.
“He(Scott) realized at some point that where the software industry was going, most of the people who were the CEOs were actually the highly technical person on the founding team.”
Scott leaving the company worried Tobi.
Tobis worried about finding a new CEO.
To Tobi:
A great VC will have the network to identify the perfect CEO for your firm.
Tobi started visiting Silicon Valley to meet with venture capitalists to recruit a CEO.
Initially visiting Silicon Valley
Tobi came to Silicon Valley to start a 20-person company.
This company creates eCommerce store software.
Tobi never wanted a big corporation. He desired a fulfilling existence.
“I stayed in a hostel in the Bay Area. I had one roommate who was also a computer programmer. I bought a bicycle on Craiglist. I was there for a week, but ended up staying two and a half weeks.”
Tobi arrived unprepared.
When venture capitalists asked him business questions.
He answered few queries.
Tobi didn't comprehend VC meetings' terminology.
He wrote the terms down and looked them up.
Some were fascinated after he couldn't answer all these queries.
“I ended up getting the kind of term sheets people dream about…All the offers were conditional on moving our company to Silicon Valley.”
Canada received Tobi.
He wanted to consult his team before deciding. Shopify had five employees at the time.
2008.
A global recession greeted Tobi in Canada. The recession hurt the market.
His term sheets were useless.
The economic downturn in the world provided Shopify with a fantastic opportunity.
The global recession caused significant job losses.
Fired employees had several ideas.
They wanted online stores.
Entrepreneurship was desired. They wanted to quit work.
People took risks and tried new things during the global slump.
Shopify subscribers skyrocketed during the recession.
“In 2009, the company reached neutral cash flow for the first time…We were in a position to think about long-term investments, such as infrastructure projects.”
Then, Tobi Lutke became CEO.
How did Tobi perform as the company's CEO?
“I wasn’t good. My team was very patient with me, but I had a lot to learn…It’s a very subtle job.”
2009–2010.
Tobi limited the company's potential.
He deliberately restrained company growth.
Tobi had one costly problem:
Whether Shopify is a venture or a lifestyle business.
The company's annual revenue approached $1 million.
Tobi battled with the firm and himself despite good revenue.
His wife was supportive, but the responsibility was crushing him.
“It’s a crushing responsibility…People had families and kids…I just couldn’t believe what was going on…My father-in-law gave me money to cover the payroll and it was his life-saving.”
Throughout this trip, everyone supported Tobi.
They believed it.
$7 million in donations received
Tobi couldn't decide if this was a lifestyle or a business.
Shopify struggled with marketing then.
Later, Tobi tried 5 marketing methods.
He told himself that if any marketing method greatly increased their growth, he would call it a venture, otherwise a lifestyle.
The Shopify crew brainstormed and voted on marketing concepts.
Tested.
“Every single idea worked…We did Adwords, published a book on the concept, sponsored a podcast and all the ones we tracked worked.”
To Silicon Valley once more
Shopify marketing concepts worked once.
Tobi returned to Silicon Valley to pitch investors.
He raised $7 million, valuing Shopify at $25 million.
All investors had board seats.
“I find it very helpful…I always had a fantastic relationship with everyone who’s invested in my company…I told them straight that I am not going to pretend I know things, I want you to help me.”
Tobi developed skills via running Shopify.
Shopify had 20 employees.
Leaving his wife's parents' home
Tobi left his wife's parents in 2014.
Tobi had a child.
Shopify has 80,000 customers and 300 staff in 2013.
Public offering in 2015
Shopify investors went public in 2015.
Shopify powers 4.1 million e-Commerce sites.
Shopify stores are 65% US-based.
It is currently valued at $48 billion.
