More on Leadership

Bart Krawczyk
2 years ago
Understanding several Value Proposition kinds will help you create better goods.
Fixing problems isn't enough.
Numerous articles and how-to guides on value propositions focus on fixing consumer concerns.
Contrary to popular opinion, addressing customer pain rarely suffices. Win your market category too.
Core Value Statement
Value proposition usually means a product's main value.
Its how your product solves client problems. The product's core.
Answering these questions creates a relevant core value proposition:
What tasks is your customer trying to complete? (Jobs for clients)
How much discomfort do they feel while they perform this? (pains)
What would they like to see improved or changed? (gains)
After that, you create products and services that alleviate those pains and give value to clients.
Value Proposition by Category
Your product belongs to a market category and must follow its regulations, regardless of its value proposition.
Creating a new market category is challenging. Fitting into customers' product perceptions is usually better than trying to change them.
New product users simplify market categories. Products are labeled.
Your product will likely be associated with a collection of products people already use.
Example: IT experts will use your communication and management app.
If your target clients think it's an advanced mail software, they'll compare it to others and expect things like:
comprehensive calendar
spam detectors
adequate storage space
list of contacts
etc.
If your target users view your product as a task management app, things change. You can survive without a contact list, but not status management.
Find out what your customers compare your product to and if it fits your value offer. If so, adapt your product plan to dominate this market. If not, try different value propositions and messaging to put the product in the right context.
Finished Value Proposition
A comprehensive value proposition is when your solution addresses user problems and wins its market category.
Addressing simply the primary value proposition may produce a valuable and original product, but it may struggle to cross the chasm into the mainstream market. Meeting expectations is easier than changing views.
Without a unique value proposition, you will drown in the red sea of competition.
To conclude:
Find out who your target consumer is and what their demands and problems are.
To meet these needs, develop and test a primary value proposition.
Speak with your most devoted customers. Recognize the alternatives they use to compare you against and the market segment they place you in.
Recognize the requirements and expectations of the market category.
To meet or surpass category standards, modify your goods.
Great products solve client problems and win their category.

Alexander Nguyen
3 years ago
A Comparison of Amazon, Microsoft, and Google's Compensation
Learn or earn
In 2020, I started software engineering. My base wage has progressed as follows:
Amazon (2020): $112,000
Microsoft (2021): $123,000
Google (2022): $169,000
I didn't major in math, but those jumps appear more than a 7% wage increase. Here's a deeper look at the three.
The Three Categories of Compensation
Most software engineering compensation packages at IT organizations follow this format.
Minimum Salary
Base salary is pre-tax income. Most organizations give a base pay. This is paid biweekly, twice monthly, or monthly.
Recruiting Bonus
Sign-On incentives are one-time rewards to new hires. Companies need an incentive to switch. If you leave early, you must pay back the whole cost or a pro-rated amount.
Equity
Equity is complex and requires its own post. A company will promise to give you a certain amount of company stock but when you get it depends on your offer. 25% per year for 4 years, then it's gone.
If a company gives you $100,000 and distributes 25% every year for 4 years, expect $25,000 worth of company stock in your stock brokerage on your 1 year work anniversary.
Performance Bonus
Tech offers may include yearly performance bonuses. Depends on performance and funding. I've only seen 0-20%.
Engineers' overall compensation usually includes:
Base Salary + Sign-On + (Total Equity)/4 + Average Performance Bonus
Amazon: (TC: 150k)
Base Pay System
Amazon pays Seattle employees monthly on the first work day. I'd rather have my money sooner than later, even if it saves processing and pay statements.
The company upped its base pay cap from $160,000 to $350,000 to compete with other tech companies.
Performance Bonus
Amazon has no performance bonus, so you can work as little or as much as you like and get paid the same. Amazon is savvy to avoid promising benefits it can't deliver.
Sign-On Bonus
Amazon gives two two-year sign-up bonuses. First-year workers could receive $20,000 and second-year workers $15,000. It's probably to make up for the company's strange equity structure.
If you leave during the first year, you'll owe the entire money and a prorated amount for the second year bonus.
Equity
Most organizations prefer a 25%, 25%, 25%, 25% equity structure. Amazon takes a different approach with end-heavy equity:
the first year, 5%
15% after one year.
20% then every six months
We thought it was constructed this way to keep staff longer.
Microsoft (TC: 185k)
Base Pay System
Microsoft paid biweekly.
Gainful Performance
My offer letter suggested a 0%-20% performance bonus. Everyone will be satisfied with a 10% raise at year's end.
But misleading press where the budget for the bonus is doubled can upset some employees because they won't earn double their expected bonus. Still barely 10% for 2022 average.
Sign-On Bonus
Microsoft's sign-on bonus is a one-time payout. The contract can require 2-year employment. You must negotiate 1 year. It's pro-rated, so that's fair.
Equity
Microsoft is one of those companies that has standard 25% equity structure. Except if you’re a new graduate.
In that case it’ll be
25% six months later
25% each year following that
New grads will acquire equity in 3.5 years, not 4. I'm guessing it's to keep new grads around longer.
Google (TC: 300k)
Base Pay Structure
Google pays biweekly.
Performance Bonus
Google's offer letter specifies a 15% bonus. It's wonderful there's no cap, but I might still get 0%. A little more than Microsoft’s 10% and a lot more than Amazon’s 0%.
Sign-On Bonus
Google gave a 1-year sign-up incentive. If the contract is only 1 year, I can move without any extra obligations.
Not as fantastic as Amazon's sign-up bonuses, but the remainder of the package might compensate.
Equity
We covered Amazon's tail-heavy compensation structure, so Google's front-heavy equity structure may surprise you.
Annual structure breakdown
33% Year 1
33% Year 2
22% Year 3
12% Year 4
The goal is to get them to Google and keep them there.
Final Thoughts
This post hopefully helped you understand the 3 firms' compensation arrangements.
There's always more to discuss, such as refreshers, 401k benefits, and business discounts, but I hope this shows a distinction between these 3 firms.

Joe Procopio
2 years ago
Provide a product roadmap that can withstand startup velocities
This is how to build a car while driving.
Building a high-growth startup is compared to building a car while it's speeding down the highway.
How to plan without going crazy? Or, without losing team, board, and investor buy-in?
I just delivered our company's product roadmap for the rest of the year. Complete. Thorough. Page-long. I'm optimistic about its chances of surviving as everything around us changes, from internal priorities to the global economy.
It's tricky. This isn't the first time I've created a startup roadmap. I didn't invent a document. It took time to deliver a document that will be relevant for months.
Goals matter.
Although they never change, goals are rarely understood.
This is the third in a series about a startup's unique roadmapping needs. Velocity is the intensity at which a startup must produce to survive.
A high-growth startup moves at breakneck speed, which I alluded to when I said priorities and economic factors can change daily or weekly.
At that speed, a startup's roadmap must be flexible, bend but not break, and be brief and to the point. I can't tell you how many startups and large companies develop a product roadmap every quarter and then tuck it away.
Big, wealthy companies can do this. It's suicide for a startup.
The drawer thing happens because startup product roadmaps are often valid for a short time. The roadmap is a random list of features prioritized by different company factions and unrelated to company goals.
It's not because the goals changed that a roadmap is shelved or ignored. Because the company's goals were never communicated or documented in the context of its product.
In the previous post, I discussed how to turn company goals into a product roadmap. In this post, I'll show you how to make a one-page startup roadmap.
In a future post, I'll show you how to follow this roadmap. This roadmap helps you track company goals, something a roadmap must do.
Be vague for growth, but direct for execution.
Here's my plan. The real one has more entries and more content in each.
Let's discuss smaller boxes.
Product developers and engineers know that the further out they predict, the more wrong they'll be. When developing the product roadmap, this rule is ignored. Then it bites us three, six, or nine months later when we haven't even started.
Why do we put everything in a product roadmap like a project plan?
Yes, I know. We use it when the product roadmap isn't goal-based.
A goal-based roadmap begins with a document that outlines each goal's idea, execution, growth, and refinement.
Once the goals are broken down into epics, initiatives, projects, and programs, only the idea and execution phases should be modeled. Any goal growth or refinement items should be vague and loosely mapped.
Why? First, any idea or execution-phase goal will result in growth initiatives that are unimaginable today. Second, internal priorities and external factors will change, but the goals won't. Locking items into calendar slots reduces flexibility and forces deviation from the single source of truth.
No soothsayers. Predicting the future is pointless; just prepare.
A map is useless if you don't know where you're going.
As we speed down the road, the car and the road will change. Goals define the destination.
This quarter and next quarter's roadmap should be set. After that, you should track destination milestones, not how to get there.
When you do that, even the most critical investors will understand the roadmap and buy in. When you track progress at the end of the quarter and revise your roadmap, the destination won't change.
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Cammi Pham
3 years ago
7 Scientifically Proven Things You Must Stop Doing To Be More Productive
Smarter work yields better results.
17-year-old me worked and studied 20 hours a day. During school breaks, I did coursework and ran a nonprofit at night. Long hours earned me national campaigns, A-list opportunities, and a great career. As I aged, my thoughts changed. Working harder isn't necessarily the key to success.
In some cases, doing less work might lead to better outcomes.
Consider a hard-working small business owner. He can't beat his corporate rivals by working hard. Time's limited. An entrepreneur can work 24 hours a day, 7 days a week, but a rival can invest more money, create a staff, and put in more man hours. Why have small startups done what larger companies couldn't? Facebook paid $1 billion for 13-person Instagram. Snapchat, a 30-person startup, rejected Facebook and Google bids. Luck and efficiency each contributed to their achievement.
The key to success is not working hard. It’s working smart.
Being busy and productive are different. Busy doesn't always equal productive. Productivity is less about time management and more about energy management. Life's work. It's using less energy to obtain more rewards. I cut my work week from 80 to 40 hours and got more done. I value simplicity.
Here are seven activities I gave up in order to be more productive.
1. Give up working extra hours and boost productivity instead.
When did the five-day, 40-hour work week start? Henry Ford, Ford Motor Company founder, experimented with his workers in 1926.
He decreased their daily hours from 10 to 8, and shortened the work week from 6 days to 5. As a result, he saw his workers’ productivity increase.
According to a 1980 Business Roundtable report, Scheduled Overtime Effect on Construction Projects, the more you work, the less effective and productive you become.
“Where a work schedule of 60 or more hours per week is continued longer than about two months, the cumulative effect of decreased productivity will cause a delay in the completion date beyond that which could have been realized with the same crew size on a 40-hour week.” Source: Calculating Loss of Productivity Due to Overtime Using Published Charts — Fact or Fiction
AlterNet editor Sara Robinson cited US military research showing that losing one hour of sleep per night for a week causes cognitive impairment equivalent to a.10 blood alcohol level. You can get fired for showing up drunk, but an all-nighter is fine.
Irrespective of how well you were able to get on with your day after that most recent night without sleep, it is unlikely that you felt especially upbeat and joyous about the world. Your more-negative-than-usual perspective will have resulted from a generalized low mood, which is a normal consequence of being overtired. More important than just the mood, this mind-set is often accompanied by decreases in willingness to think and act proactively, control impulses, feel positive about yourself, empathize with others, and generally use emotional intelligence. Source: The Secret World of Sleep: The Surprising Science of the Mind at Rest
To be productive, don't overwork and get enough sleep. If you're not productive, lack of sleep may be to blame. James Maas, a sleep researcher and expert, said 7/10 Americans don't get enough sleep.
Did you know?
Leonardo da Vinci slept little at night and frequently took naps.
Napoleon, the French emperor, had no qualms about napping. He splurged every day.
Even though Thomas Edison felt self-conscious about his napping behavior, he regularly engaged in this ritual.
President Franklin D. Roosevelt's wife Eleanor used to take naps before speeches to increase her energy.
The Singing Cowboy, Gene Autry, was known for taking regular naps in his dressing area in between shows.
Every day, President John F. Kennedy took a siesta after eating his lunch in bed.
Every afternoon, oil businessman and philanthropist John D. Rockefeller took a nap in his office.
It was unavoidable for Winston Churchill to take an afternoon snooze. He thought it enabled him to accomplish twice as much each day.
Every afternoon around 3:30, President Lyndon B. Johnson took a nap to divide his day into two segments.
Ronald Reagan, the 40th president, was well known for taking naps as well.
Source: 5 Reasons Why You Should Take a Nap Every Day — Michael Hyatt
Since I started getting 7 to 8 hours of sleep a night, I've been more productive and completed more work than when I worked 16 hours a day. Who knew marketers could use sleep?
2. Refrain from accepting too frequently
Pareto's principle states that 20% of effort produces 80% of results, but 20% of results takes 80% of effort. Instead of working harder, we should prioritize the initiatives that produce the most outcomes. So we can focus on crucial tasks. Stop accepting unproductive tasks.
“The difference between successful people and very successful people is that very successful people say “no” to almost everything.” — Warren Buffett
What should you accept? Why say no? Consider doing a split test to determine if anything is worth your attention. Track what you do, how long it takes, and the consequences. Then, evaluate your list to discover what worked (or didn't) to optimize future chores.
Most of us say yes more often than we should, out of guilt, overextension, and because it's simpler than no. Nobody likes being awful.
Researchers separated 120 students into two groups for a 2012 Journal of Consumer Research study. One group was educated to say “I can't” while discussing choices, while the other used “I don't”.
The students who told themselves “I can’t eat X” chose to eat the chocolate candy bar 61% of the time. Meanwhile, the students who told themselves “I don’t eat X” chose to eat the chocolate candy bars only 36% of the time. This simple change in terminology significantly improved the odds that each person would make a more healthy food choice.
Next time you need to say no, utilize I don't to encourage saying no to unimportant things.
The 20-second rule is another wonderful way to avoid pursuits with little value. Add a 20-second roadblock to things you shouldn't do or bad habits you want to break. Delete social media apps from your phone so it takes you 20 seconds to find your laptop to access them. You'll be less likely to engage in a draining hobby or habit if you add an inconvenience.
Lower the activation energy for habits you want to adopt and raise it for habits you want to avoid. The more we can lower or even eliminate the activation energy for our desired actions, the more we enhance our ability to jump-start positive change. Source: The Happiness Advantage: The Seven Principles of Positive Psychology That Fuel Success and Performance at Work
3. Stop doing everything yourself and start letting people help you
I once managed a large community and couldn't do it alone. The community took over once I burned out. Members did better than I could have alone. I learned about community and user-generated content.
Consumers know what they want better than marketers. Octoly says user-generated videos on YouTube are viewed 10 times more than brand-generated videos. 51% of Americans trust user-generated material more than a brand's official website (16%) or media coverage (22%). (14 percent). Marketers should seek help from the brand community.
Being a successful content marketer isn't about generating the best content, but cultivating a wonderful community.
We should seek aid when needed. We can't do everything. It's best to delegate work so you may focus on the most critical things. Instead of overworking or doing things alone, let others help.
Having friends or coworkers around can boost your productivity even if they can't help.
Just having friends nearby can push you toward productivity. “There’s a concept in ADHD treatment called the ‘body double,’ ” says David Nowell, Ph.D., a clinical neuropsychologist from Worcester, Massachusetts. “Distractable people get more done when there is someone else there, even if he isn’t coaching or assisting them.” If you’re facing a task that is dull or difficult, such as cleaning out your closets or pulling together your receipts for tax time, get a friend to be your body double. Source: Friendfluence: The Surprising Ways Friends Make Us Who We Are
4. Give up striving for perfection
Perfectionism hinders professors' research output. Dr. Simon Sherry, a psychology professor at Dalhousie University, did a study on perfectionism and productivity. Dr. Sherry established a link between perfectionism and productivity.
Perfectionism has its drawbacks.
They work on a task longer than necessary.
They delay and wait for the ideal opportunity. If the time is right in business, you are already past the point.
They pay too much attention to the details and miss the big picture.
Marketers await the right time. They miss out.
The perfect moment is NOW.
5. Automate monotonous chores instead of continuing to do them.
A team of five workers who spent 3%, 20%, 25%, 30%, and 70% of their time on repetitive tasks reduced their time spent to 3%, 10%, 15%, 15%, and 10% after two months of working to improve their productivity.
Last week, I wrote a 15-minute Python program. I wanted to generate content utilizing Twitter API data and Hootsuite to bulk schedule it. Automation has cut this task from a day to five minutes. Whenever I do something more than five times, I try to automate it.
Automate monotonous chores without coding. Skills and resources are nice, but not required. If you cannot build it, buy it.
People forget time equals money. Manual work is easy and requires little investigation. You can moderate 30 Instagram photographs for your UGC campaign. You need digital asset management software to manage 30,000 photographs and movies from five platforms. Filemobile helps individuals develop more user-generated content. You may buy software to manage rich media and address most internet difficulties.
Hire an expert if you can't find a solution. Spend money to make money, and time is your most precious asset.
Visit GitHub or Google Apps Script library, marketers. You may often find free, easy-to-use open source code.
6. Stop relying on intuition and start supporting your choices with data.
You may optimize your life by optimizing webpages for search engines.
Numerous studies might help you boost your productivity. Did you know individuals are most distracted from midday to 4 p.m.? This is what a Penn State psychology professor found. Even if you can't find data on a particular question, it's easy to run a split test and review your own results.
7. Stop working and spend some time doing absolutely nothing.
Most people don't know that being too focused can be destructive to our work or achievements. The Boston Globe's The Power of Lonely says solo time is excellent for the brain and spirit.
One ongoing Harvard study indicates that people form more lasting and accurate memories if they believe they’re experiencing something alone. Another indicates that a certain amount of solitude can make a person more capable of empathy towards others. And while no one would dispute that too much isolation early in life can be unhealthy, a certain amount of solitude has been shown to help teenagers improve their moods and earn good grades in school. Source: The Power of Lonely
Reflection is vital. We find solutions when we're not looking.
We don't become more productive overnight. It demands effort and practice. Waiting for change doesn't work. Instead, learn about your body and identify ways to optimize your energy and time for a happy existence.

Adam Frank
3 years ago
Humanity is not even a Type 1 civilization. What might a Type 3 be capable of?
The Kardashev scale grades civilizations from Type 1 to Type 3 based on energy harvesting.
How do technologically proficient civilizations emerge across timescales measuring in the tens of thousands or even millions of years? This is a question that worries me as a researcher in the search for “technosignatures” from other civilizations on other worlds. Since it is already established that longer-lived civilizations are the ones we are most likely to detect, knowing something about their prospective evolutionary trajectories could be translated into improved search tactics. But even more than knowing what to seek for, what I really want to know is what happens to a society after so long time. What are they capable of? What do they become?
This was the question Russian SETI pioneer Nikolai Kardashev asked himself back in 1964. His answer was the now-famous “Kardashev Scale.” Kardashev was the first, although not the last, scientist to try and define the processes (or stages) of the evolution of civilizations. Today, I want to launch a series on this question. It is crucial to technosignature studies (of which our NASA team is hard at work), and it is also important for comprehending what might lay ahead for mankind if we manage to get through the bottlenecks we have now.
The Kardashev scale
Kardashev’s question can be expressed another way. What milestones in a civilization’s advancement up the ladder of technical complexity will be universal? The main notion here is that all (or at least most) civilizations will pass through some kind of definable stages as they progress, and some of these steps might be mirrored in how we could identify them. But, while Kardashev’s major focus was identifying signals from exo-civilizations, his scale gave us a clear way to think about their evolution.
The classification scheme Kardashev employed was not based on social systems of ethics because they are something that we can probably never predict about alien cultures. Instead, it was built on energy, which is something near and dear to the heart of everybody trained in physics. Energy use might offer the basis for universal stages of civilisation progression because you cannot do the work of establishing a civilization without consuming energy. So, Kardashev looked at what energy sources were accessible to civilizations as they evolved technologically and used those to build his scale.
From Kardashev’s perspective, there are three primary levels or “types” of advancement in terms of harvesting energy through which a civilization should progress.
Type 1: Civilizations that can capture all the energy resources of their native planet constitute the first stage. This would imply capturing all the light energy that falls on a world from its host star. This makes it reasonable, given solar energy will be the largest source available on most planets where life could form. For example, Earth absorbs hundreds of atomic bombs’ worth of energy from the Sun every second. That is a rather formidable energy source, and a Type 1 race would have all this power at their disposal for civilization construction.
Type 2: These civilizations can extract the whole energy resources of their home star. Nobel Prize-winning scientist Freeman Dyson famously anticipated Kardashev’s thinking on this when he imagined an advanced civilization erecting a large sphere around its star. This “Dyson Sphere” would be a machine the size of the complete solar system for gathering stellar photons and their energy.
Type 3: These super-civilizations could use all the energy produced by all the stars in their home galaxy. A normal galaxy has a few hundred billion stars, so that is a whole lot of energy. One way this may be done is if the civilization covered every star in their galaxy with Dyson spheres, but there could also be more inventive approaches.
Implications of the Kardashev scale
Climbing from Type 1 upward, we travel from the imaginable to the god-like. For example, it is not hard to envisage utilizing lots of big satellites in space to gather solar energy and then beaming that energy down to Earth via microwaves. That would get us to a Type 1 civilization. But creating a Dyson sphere would require chewing up whole planets. How long until we obtain that level of power? How would we have to change to get there? And once we get to Type 3 civilizations, we are virtually thinking about gods with the potential to engineer the entire cosmos.
For me, this is part of the point of the Kardashev scale. Its application for thinking about identifying technosignatures is crucial, but even more strong is its capacity to help us shape our imaginations. The mind might become blank staring across hundreds or thousands of millennia, and so we need tools and guides to focus our attention. That may be the only way to see what life might become — what we might become — once it arises to start out beyond the boundaries of space and time and potential.
This is a summary. Read the full article here.

Ajay Shrestha
2 years ago
Bitcoin's technical innovation: addressing the issue of the Byzantine generals
The 2008 Bitcoin white paper solves the classic computer science consensus problem.
Issue Statement
The Byzantine Generals Problem (BGP) is called after an allegory in which several generals must collaborate and attack a city at the same time to win (figure 1-left). Any general who retreats at the last minute loses the fight (figure 1-right). Thus, precise messengers and no rogue generals are essential. This is difficult without a trusted central authority.
In their 1982 publication, Leslie Lamport, Robert Shostak, and Marshall Please termed this topic the Byzantine Generals Problem to simplify distributed computer systems.
Consensus in a distributed computer network is the issue. Reaching a consensus on which systems work (and stay in the network) and which don't makes maintaining a network tough (i.e., needs to be removed from network). Challenges include unreliable communication routes between systems and mis-reporting systems.
Solving BGP can let us construct machine learning solutions without single points of failure or trusted central entities. One server hosts model parameters while numerous workers train the model. This study describes fault-tolerant Distributed Byzantine Machine Learning.
Bitcoin invented a mechanism for a distributed network of nodes to agree on which transactions should go into the distributed ledger (blockchain) without a trusted central body. It solved BGP implementation. Satoshi Nakamoto, the pseudonymous bitcoin creator, solved the challenge by cleverly combining cryptography and consensus mechanisms.
Disclaimer
This is not financial advice. It discusses a unique computer science solution.
Bitcoin
Bitcoin's white paper begins:
“A purely peer-to-peer version of electronic cash would allow online payments to be sent directly from one party to another without going through a financial institution.” Source: https://www.ussc.gov/sites/default/files/pdf/training/annual-national-training-seminar/2018/Emerging_Tech_Bitcoin_Crypto.pdf
Bitcoin's main parts:
The open-source and versioned bitcoin software that governs how nodes, miners, and the bitcoin token operate.
The native kind of token, known as a bitcoin token, may be created by mining (up to 21 million can be created), and it can be transferred between wallet addresses in the bitcoin network.
Distributed Ledger, which contains exact copies of the database (or "blockchain") containing each transaction since the first one in January 2009.
distributed network of nodes (computers) running the distributed ledger replica together with the bitcoin software. They broadcast the transactions to other peer nodes after validating and accepting them.
Proof of work (PoW) is a cryptographic requirement that must be met in order for a miner to be granted permission to add a new block of transactions to the blockchain of the cryptocurrency bitcoin. It takes the form of a valid hash digest. In order to produce new blocks on average every 10 minutes, Bitcoin features a built-in difficulty adjustment function that modifies the valid hash requirement (length of nonce). PoW requires a lot of energy since it must continually generate new hashes at random until it satisfies the criteria.
The competing parties known as miners carry out continuous computing processing to address recurrent cryptography issues. Transaction fees and some freshly minted (mined) bitcoin are the rewards they receive. The amount of hashes produced each second—or hash rate—is a measure of mining capacity.
Cryptography, decentralization, and the proof-of-work consensus method are Bitcoin's most unique features.
Bitcoin uses encryption
Bitcoin employs this established cryptography.
Hashing
digital signatures based on asymmetric encryption
Hashing (SHA-256) (SHA-256)
Hashing converts unique plaintext data into a digest. Creating the plaintext from the digest is impossible. Bitcoin miners generate new hashes using SHA-256 to win block rewards.
A new hash is created from the current block header and a variable value called nonce. To achieve the required hash, mining involves altering the nonce and re-hashing.
The block header contains the previous block hash and a Merkle root, which contains hashes of all transactions in the block. Thus, a chain of blocks with increasing hashes links back to the first block. Hashing protects new transactions and makes the bitcoin blockchain immutable. After a transaction block is mined, it becomes hard to fabricate even a little entry.
Asymmetric Cryptography Digital Signatures
Asymmetric cryptography (public-key encryption) requires each side to have a secret and public key. Public keys (wallet addresses) can be shared with the transaction party, but private keys should not. A message (e.g., bitcoin payment record) can only be signed by the owner (sender) with the private key, but any node or anybody with access to the public key (visible in the blockchain) can verify it. Alex will submit a digitally signed transaction with a desired amount of bitcoin addressed to Bob's wallet to a node to send bitcoin to Bob. Alex alone has the secret keys to authorize that amount. Alex's blockchain public key allows anyone to verify the transaction.
Solution
Now, apply bitcoin to BGP. BGP generals resemble bitcoin nodes. The generals' consensus is like bitcoin nodes' blockchain block selection. Bitcoin software on all nodes can:
Check transactions (i.e., validate digital signatures)
2. Accept and propagate just the first miner to receive the valid hash and verify it accomplished the task. The only way to guess the proper hash is to brute force it by repeatedly producing one with the fixed/current block header and a fresh nonce value.
Thus, PoW and a dispersed network of nodes that accept blocks from miners that solve the unfalsifiable cryptographic challenge solve consensus.
Suppose:
Unreliable nodes
Unreliable miners
Bitcoin accepts the longest chain if rogue nodes cause divergence in accepted blocks. Thus, rogue nodes must outnumber honest nodes in accepting/forming the longer chain for invalid transactions to reach the blockchain. As of November 2022, 7000 coordinated rogue nodes are needed to takeover the bitcoin network.
Dishonest miners could also try to insert blocks with falsified transactions (double spend, reverse, censor, etc.) into the chain. This requires over 50% (51% attack) of miners (total computational power) to outguess the hash and attack the network. Mining hash rate exceeds 200 million (source). Rewards and transaction fees encourage miners to cooperate rather than attack. Quantum computers may become a threat.
Visit my Quantum Computing post.
Quantum computers—what are they? Quantum computers will have a big influence. towardsdatascience.com
Nodes have more power than miners since they can validate transactions and reject fake blocks. Thus, the network is secure if honest nodes are the majority.
Summary
Table 1 compares three Byzantine Generals Problem implementations.
Bitcoin white paper and implementation solved the consensus challenge of distributed systems without central governance. It solved the illusive Byzantine Generals Problem.
Resources
Resources
Source-code for Bitcoin Core Software — https://github.com/bitcoin/bitcoin
Bitcoin white paper — https://bitcoin.org/bitcoin.pdf
https://www.microsoft.com/en-us/research/publication/byzantine-generals-problem/
https://www.microsoft.com/en-us/research/uploads/prod/2016/12/The-Byzantine-Generals-Problem.pdf
Genuinely Distributed Byzantine Machine Learning, El-Mahdi El-Mhamdi et al., 2020. ACM, New York, NY, https://doi.org/10.1145/3382734.3405695