More on Web3 & Crypto
Vitalik
4 years ago
An approximate introduction to how zk-SNARKs are possible (part 2)
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? But it turns out that there is a clever solution.
Polynomials
Polynomials are a special class of algebraic expressions of the form:
- x+5
- x^4
- x^3+3x^2+3x+1
- 628x^{271}+318x^{270}+530x^{269}+…+69x+381
i.e. they are a sum of any (finite!) number of terms of the form cx^k
There are many things that are fascinating about polynomials. But here we are going to zoom in on a particular one: polynomials are a single mathematical object that can contain an unbounded amount of information (think of them as a list of integers and this is obvious). The fourth example above contained 816 digits of tau, and one can easily imagine a polynomial that contains far more.
Furthermore, a single equation between polynomials can represent an unbounded number of equations between numbers. For example, consider the equation A(x)+ B(x) = C(x). If this equation is true, then it's also true that:
- A(0)+B(0)=C(0)
- A(1)+B(1)=C(1)
- A(2)+B(2)=C(2)
- A(3)+B(3)=C(3)
And so on for every possible coordinate. You can even construct polynomials to deliberately represent sets of numbers so you can check many equations all at once. For example, suppose that you wanted to check:
- 12+1=13
- 10+8=18
- 15+8=23
- 15+13=28
You can use a procedure called Lagrange interpolation to construct polynomials A(x) that give (12,10,15,15) as outputs at some specific set of coordinates (eg. (0,1,2,3)), B(x) the outputs (1,8,8,13) on thos same coordinates, and so forth. In fact, here are the polynomials:
- A(x)=-2x^3+\frac{19}{2}x^2-\frac{19}{2}x+12
- B(x)=2x^3-\frac{19}{2}x^2+\frac{29}{2}x+1
- C(x)=5x+13
Checking the equation A(x)+B(x)=C(x) with these polynomials checks all four above equations at the same time.
Comparing a polynomial to itself
You can even check relationships between a large number of adjacent evaluations of the same polynomial using a simple polynomial equation. This is slightly more advanced. Suppose that you want to check that, for a given polynomial F, F(x+2)=F(x)+F(x+1) with the integer range {0,1…89} (so if you also check F(0)=F(1)=1, then F(100) would be the 100th Fibonacci number)
As polynomials, F(x+2)-F(x+1)-F(x) would not be exactly zero, as it could give arbitrary answers outside the range x={0,1…98}. But we can do something clever. In general, there is a rule that if a polynomial P is zero across some set S=\{x_1,x_2…x_n\} then it can be expressed as P(x)=Z(x)*H(x), where Z(x)=(x-x_1)*(x-x_2)*…*(x-x_n) and H(x) is also a polynomial. In other words, any polynomial that equals zero across some set is a (polynomial) multiple of the simplest (lowest-degree) polynomial that equals zero across that same set.
Why is this the case? It is a nice corollary of polynomial long division: the factor theorem. We know that, when dividing P(x) by Z(x), we will get a quotient Q(x) and a remainder R(x) is strictly less than that of Z(x). Since we know that P is zero on all of S, it means that R has to be zero on all of S as well. So we can simply compute R(x) via polynomial interpolation, since it's a polynomial of degree at most n-1 and we know n values (the zeros at S). Interpolating a polynomial with all zeroes gives the zero polynomial, thus R(x)=0 and H(x)=Q(x).
Going back to our example, if we have a polynomial F that encodes Fibonacci numbers (so F(x+2)=F(x)+F(x+1) across x=\{0,1…98\}), then I can convince you that F actually satisfies this condition by proving that the polynomial P(x)=F(x+2)-F(x+1)-F(x) is zero over that range, by giving you the quotient:
H(x)=\frac{F(x+2)-F(x+1)-F(x)}{Z(x)}
Where Z(x) = (x-0)*(x-1)*…*(x-98).
You can calculate Z(x) yourself (ideally you would have it precomputed), check the equation, and if the check passes then F(x) satisfies the condition!
Now, step back and notice what we did here. We converted a 100-step-long computation into a single equation with polynomials. Of course, proving the N'th Fibonacci number is not an especially useful task, especially since Fibonacci numbers have a closed form. But you can use exactly the same basic technique, just with some extra polynomials and some more complicated equations, to encode arbitrary computations with an arbitrarily large number of steps.
see part 3
TheRedKnight
3 years ago
Say goodbye to Ponzi yields - A new era of decentralized perpetual
Decentralized perpetual may be the next crypto market boom; with tons of perpetual popping up, let's look at two protocols that offer organic, non-inflationary yields.
Decentralized derivatives exchanges' market share has increased tenfold in a year, but it's still 2% of CEXs'. DEXs have a long way to go before they can compete with centralized exchanges in speed, liquidity, user experience, and composability.
I'll cover gains.trade and GMX protocol in Polygon, Avalanche, and Arbitrum. Both protocols support leveraged perpetual crypto, stock, and Forex trading.
Why these protocols?
Decentralized GMX Gains protocol
Organic yield: path to sustainability
I've never trusted Defi's non-organic yields. Example: XYZ protocol. 20–75% of tokens may be set aside as farming rewards to provide liquidity, according to tokenomics.
Say you provide ETH-USDC liquidity. They advertise a 50% APR reward for this pair, 10% from trading fees and 40% from farming rewards. Only 10% is real, the rest is "Ponzi." The "real" reward is in protocol tokens.
Why keep this token? Governance voting or staking rewards are promoted services.
Most liquidity providers expect compensation for unused tokens. Basic psychological principles then? — Profit.
Nobody wants governance tokens. How many out of 100 care about the protocol's direction and will vote?
Staking increases your token's value. Currently, they're mostly non-liquid. If the protocol is compromised, you can't withdraw funds. Most people are sceptical of staking because of this.
"Free tokens," lack of use cases, and skepticism lead to tokens moving south. No farming reward protocols have lasted.
It may have shown strength in a bull market, but what about a bear market?
What is decentralized perpetual?
A perpetual contract is a type of futures contract that doesn't expire. So one can hold a position forever.
You can buy/sell any leveraged instruments (Long-Short) without expiration.
In centralized exchanges like Binance and coinbase, fees and revenue (liquidation) go to the exchanges, not users.
Users can provide liquidity that traders can use to leverage trade, and the revenue goes to liquidity providers.
Gains.trade and GMX protocol are perpetual trading platforms with a non-inflationary organic yield for liquidity providers.
GMX protocol
GMX is an Arbitrum and Avax protocol that rewards in ETH and Avax. GLP uses a fast oracle to borrow the "true price" from other trading venues, unlike a traditional AMM.
GLP and GMX are protocol tokens. GLP is used for leveraged trading, swapping, etc.
GLP is a basket of tokens, including ETH, BTC, AVAX, stablecoins, and UNI, LINK, and Stablecoins.
GLP composition on arbitrum
GLP composition on Avalanche
GLP token rebalances based on usage, providing liquidity without loss.
Protocol "runs" on Staking GLP. Depending on their chain, the protocol will reward users with ETH or AVAX. Current rewards are 22 percent (15.71 percent in ETH and the rest in escrowed GMX) and 21 percent (15.72 percent in AVAX and the rest in escrowed GMX). escGMX and ETH/AVAX percentages fluctuate.
Where is the yield coming from?
Swap fees, perpetual interest, and liquidations generate yield. 70% of fees go to GLP stakers, 30% to GMX. Organic yields aren't paid in inflationary farm tokens.
Escrowed GMX is vested GMX that unlocks in 365 days. To fully unlock GMX, you must farm the Escrowed GMX token for 365 days. That means less selling pressure for the GMX token.
GMX's status
These are the fees in Arbitrum in the past 11 months by GMX.
GMX works like a casino, which increases fees. Most fees come from Margin trading, which means most traders lose money; this money goes to the casino, or GLP stakers.
Strategies
My personal strategy is to DCA into GLP when markets hit bottom and stake it; GLP will be less volatile with extra staking rewards.
GLP YoY return vs. naked buying
Let's say I invested $10,000 in BTC, AVAX, and ETH in January.
BTC price: 47665$
ETH price: 3760$
AVAX price: $145
Current prices
BTC $21,000 (Down 56 percent )
ETH $1233 (Down 67.2 percent )
AVAX $20.36 (Down 85.95 percent )
Your $10,000 investment is now worth around $3,000.
How about GLP? My initial investment is 50% stables and 50% other assets ( Assuming the coverage ratio for stables is 50 percent at that time)
Without GLP staking yield, your value is $6500.
Let's assume the average APR for GLP staking is 23%, or $1500. So 8000$ total. It's 50% safer than holding naked assets in a bear market.
In a bull market, naked assets are preferable to GLP.
Short farming using GLP
Simple GLP short farming.
You use a stable asset as collateral to borrow AVAX. Sell it and buy GLP. Even if GLP rises, it won't rise as fast as AVAX, so we can get yields.
Let's do the maths
You deposit $10,000 USDT in Aave and borrow Avax. Say you borrow $8,000; you sell it, buy GLP, and risk 20%.
After a year, ETH, AVAX, and BTC rise 20%. GLP is $8800. $800 vanishes. 20% yields $1600. You're profitable. Shorting Avax costs $1600. (Assumptions-ETH, AVAX, BTC move the same, GLP yield is 20%. GLP has a 50:50 stablecoin/others ratio. Aave won't liquidate
In naked Avax shorting, Avax falls 20% in a year. You'll make $1600. If you buy GLP and stake it using the sold Avax and BTC, ETH and Avax go down by 20% - your profit is 20%, but with the yield, your total gain is $2400.
Issues with GMX
GMX's historical funding rates are always net positive, so long always pays short. This makes long-term shorts less appealing.
Oracle price discovery isn't enough. This limitation doesn't affect Bitcoin and ETH, but it affects less liquid assets. Traders can buy and sell less liquid assets at a lower price than their actual cost as long as GMX exists.
As users must provide GLP liquidity, adding more assets to GMX will be difficult. Next iteration will have synthetic assets.
Gains Protocol
Best leveraged trading platform. Smart contract-based decentralized protocol. 46 crypto pairs can be leveraged 5–150x and 10 Forex pairs 5–1000x. $10 DAI @ 150x (min collateral x leverage pos size is $1500 DAI). No funding fees, no KYC, trade DAI from your wallet, keep funds.
DAI single-sided staking and the GNS-DAI pool are important parts of Gains trading. GNS-DAI stakers get 90% of trading fees and 100% swap fees. 10 percent of trading fees go to DAI stakers, which is currently 14 percent!
Trade volume
When a trader opens a trade, the leverage and profit are pulled from the DAI pool. If he loses, the protocol yield goes to the stakers.
If the trader's win rate is high and the DAI pool slowly depletes, the GNS token is minted and sold to refill DAI. Trader losses are used to burn GNS tokens. 25%+ of GNS is burned, making it deflationary.
Due to high leverage and volatility of crypto assets, most traders lose money and the protocol always wins, keeping GNS deflationary.
Gains uses a unique decentralized oracle for price feeds, which is better for leverage trading platforms. Let me explain.
Gains uses chainlink price oracles, not its own price feeds. Chainlink oracles only query centralized exchanges for price feeds every minute, which is unsuitable for high-precision trading.
Gains created a custom oracle that queries the eight chainlink nodes for the current price and, on average, for trade confirmation. This model eliminates every-second inquiries, which waste gas but are more efficient than chainlink's per-minute price.
This price oracle helps Gains open and close trades instantly, eliminate scam wicks, etc.
Other benefits include:
Stop-loss guarantee (open positions updated)
No scam wicks
Spot-pricing
Highest possible leverage
Fixed-spreads. During high volatility, a broker can increase the spread, which can hit your stop loss without the price moving.
Trade directly from your wallet and keep your funds.
>90% loss before liquidation (Some platforms liquidate as little as -50 percent)
KYC-free
Directly trade from wallet; keep funds safe
Further improvements
GNS-DAI liquidity providers fear the impermanent loss, so the protocol is migrating to its own liquidity and single staking GNS vaults. This allows users to stake GNS without permanent loss and obtain 90% DAI trading fees by staking. This starts in August.
Their upcoming improvements can be found here.
Gains constantly add new features and change pairs. It's an interesting protocol.
Conclusion
Next bull run, watch decentralized perpetual protocols. Effective tokenomics and non-inflationary yields may attract traders and liquidity providers. But still, there is a long way for them to develop, and I don't see them tackling the centralized exchanges any time soon until they fix their inherent problems and improve fast enough.
Read the full post here.
Stephen Moore
3 years ago
Web 2 + Web 3 = Web 5.
Monkey jpegs and shitcoins have tarnished Web3's reputation. Let’s move on.
Web3 was called "the internet's future."
Well, 'crypto bros' shouted about it loudly.
As quickly as it arrived to be the next internet, it appears to be dead. It's had scandals, turbulence, and crashes galore:
Web 3.0's cryptocurrencies have crashed. Bitcoin's all-time high was $66,935. This month, Ethereum fell from $2130 to $1117. Six months ago, the cryptocurrency market peaked at $3 trillion. Worst is likely ahead.
Gas fees make even the simplest Web3 blockchain transactions unsustainable.
Terra, Luna, and other dollar pegs collapsed, hurting crypto markets. Celsius, a crypto lender backed by VCs and Canada's second-largest pension fund, and Binance, a crypto marketplace, have withheld money and coins. They're near collapse.
NFT sales are falling rapidly and losing public interest.
Web3 has few real-world uses, like most crypto/blockchain technologies. Web3's image has been tarnished by monkey profile pictures and shitcoins while failing to become decentralized (the whole concept is controlled by VCs).
The damage seems irreparable, leaving Web3 in the gutter.
Step forward our new saviour — Web5
Fear not though, as hero awaits to drag us out of the Web3 hellscape. Jack Dorsey revealed his plan to save the internet quickly.
Dorsey has long criticized Web3, believing that VC capital and silicon valley insiders have created a centralized platform. In a tweet that upset believers and VCs (he was promptly blocked by Marc Andreessen), Dorsey argued, "You don't own "Web3." VCs and LPs do. Their incentives prevent it. It's a centralized organization with a new name.
Dorsey announced Web5 on June 10 in a very Elon-like manner. Block's TBD unit will work on the project (formerly Square).
Web5's pitch is that users will control their own data and identity. Bitcoin-based. Sound familiar? The presentation pack's official definition emphasizes decentralization. Web5 is a decentralized web platform that enables developers to write decentralized web apps using decentralized identifiers, verifiable credentials, and decentralized web nodes, returning ownership and control over identity and data to individuals.
Web5 would be permission-less, open, and token-less. What that means for Earth is anyone's guess. Identity. Ownership. Blockchains. Bitcoin. Different.
Web4 appears to have been skipped, forever destined to wish it could have shown the world what it could have been. (It was probably crap.) As this iteration combines Web2 and Web3, simple math and common sense add up to 5. Or something.
Dorsey and his team have had this idea simmering for a while. Daniel Buchner, a member of Block's Decentralized Identity team, said, "We're finishing up Web5's technical components."
Web5 could be the project that decentralizes the internet. It must be useful to users and convince everyone to drop the countless Web3 projects, products, services, coins, blockchains, and websites being developed as I write this.
Web5 may be too late for Dorsey and the incoming flood of creators.
Web6 is planned!
The next months and years will be hectic and less stable than the transition from Web 1.0 to Web 2.0.
Web1 was around 1991-2004.
Web2 ran from 2004 to 2021. (though the Web3 term was first used in 2014, it only really gained traction years later.)
Web3 lasted a year.
Web4 is dead.
Silicon Valley billionaires are turning it into a startup-style race, each disrupting the next iteration until they crack it. Or destroy it completely.
Web5 won't last either.
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Amelia Winger-Bearskin
3 years ago
Reasons Why AI-Generated Images Remind Me of Nightmares
AI images are like funhouse mirrors.
Google's AI Blog introduced the puppy-slug in the summer of 2015.
Puppy-slug isn't a single image or character. "Puppy-slug" refers to Google's DeepDream's unsettling psychedelia. This tool uses convolutional neural networks to train models to recognize dataset entities. If researchers feed the model millions of dog pictures, the network will learn to recognize a dog.
DeepDream used neural networks to analyze and classify image data as well as generate its own images. DeepDream's early examples were created by training a convolutional network on dog images and asking it to add "dog-ness" to other images. The models analyzed images to find dog-like pixels and modified surrounding pixels to highlight them.
Puppy-slugs and other DeepDream images are ugly. Even when they don't trigger my trypophobia, they give me vertigo when my mind tries to reconcile familiar features and forms in unnatural, physically impossible arrangements. I feel like I've been poisoned by a forbidden mushroom or a noxious toad. I'm a Lovecraft character going mad from extradimensional exposure. They're gross!
Is this really how AIs see the world? This is possibly an even more unsettling topic that DeepDream raises than the blatant abjection of the images.
When these photographs originally circulated online, many friends were startled and scandalized. People imagined a computer's imagination would be literal, accurate, and boring. We didn't expect vivid hallucinations and organic-looking formations.
DeepDream's images didn't really show the machines' imaginations, at least not in the way that scared some people. DeepDream displays data visualizations. DeepDream reveals the "black box" of convolutional network training.
Some of these images look scary because the models don't "know" anything, at least not in the way we do.
These images are the result of advanced algorithms and calculators that compare pixel values. They can spot and reproduce trends from training data, but can't interpret it. If so, they'd know dogs have two eyes and one face per head. If machines can think creatively, they're keeping it quiet.
You could be forgiven for thinking otherwise, given OpenAI's Dall-impressive E's results. From a technological perspective, it's incredible.
Arthur C. Clarke once said, "Any sufficiently advanced technology is indistinguishable from magic." Dall-magic E's requires a lot of math, computer science, processing power, and research. OpenAI did a great job, and we should applaud them.
Dall-E and similar tools match words and phrases to image data to train generative models. Matching text to images requires sorting and defining the images. Untold millions of low-wage data entry workers, content creators optimizing images for SEO, and anyone who has used a Captcha to access a website make these decisions. These people could live and die without receiving credit for their work, even though the project wouldn't exist without them.
This technique produces images that are less like paintings and more like mirrors that reflect our own beliefs and ideals back at us, albeit via a very complex prism. Due to the limitations and biases that these models portray, we must exercise caution when viewing these images.
The issue was succinctly articulated by artist Mimi Onuoha in her piece "On Algorithmic Violence":
As we continue to see the rise of algorithms being used for civic, social, and cultural decision-making, it becomes that much more important that we name the reality that we are seeing. Not because it is exceptional, but because it is ubiquitous. Not because it creates new inequities, but because it has the power to cloak and amplify existing ones. Not because it is on the horizon, but because it is already here.
The Secret Developer
3 years ago
What Elon Musk's Take on Bitcoin Teaches Us
Tesla Q2 earnings revealed unethical dealings.
As of end of Q2, we have converted approximately 75% of our Bitcoin purchases into fiat currency
That’s OK then, isn’t it?
Elon Musk, Tesla's CEO, is now untrustworthy.
It’s not about infidelity, it’s about doing the right thing
And what can we learn?
The Opening Remark
Musk tweets on his (and Tesla's) future goals.
Don’t worry, I’m not expecting you to read it.
What's crucial?
Tesla will not be selling any Bitcoin
The Situation as It Develops
2021 Tesla spent $1.5 billion on Bitcoin. In 2022, they sold 75% of the ownership for $946 million.
That’s a little bit of a waste of money, right?
Musk predicted the reverse would happen.
What gives? Why would someone say one thing, then do the polar opposite?
The Justification For Change
Tesla's public. They must follow regulations. When a corporation trades, they must record what happens.
At least this keeps Musk some way in line.
We now understand Musk and Tesla's actions.
Musk claimed that Tesla sold bitcoins to maximize cash given the unpredictability of COVID lockdowns in China.
Tesla may buy Bitcoin in the future, he said.
That’s fine then. He’s not knocking the NFT at least.
Tesla has moved investments into cash due to China lockdowns.
That doesn’t explain the 180° though
Musk's Tweet isn't company policy. Therefore, the CEO's change of heart reflects the organization. Look.
That's okay, since
Leaders alter their positions when circumstances change.
Leaders must adapt to their surroundings. This isn't embarrassing; it's a leadership prerequisite.
Yet
The Man
Someone stated if you're not in the office full-time, you need to explain yourself. He doesn't treat his employees like adults.
This is the individual mentioned in the quote.
If Elon was not happy, you knew it. Things could get nasty
also, He fired his helper for requesting a raise.
This public persona isn't good. Without mentioning his disastrous performances on Twitter (pedo dude) or Joe Rogan. This image sums up the odd Podcast appearance:
Which describes the man.
I wouldn’t trust this guy to feed a cat
What we can discover
When Musk's company bet on Bitcoin, what happened?
Exactly what we would expect
The company's position altered without the CEO's awareness. He seems uncaring.
This article is about how something happened, not what happened. Change of thinking requires contrition.
This situation is about a lack of respect- although you might argue that followers on Twitter don’t deserve any
Tesla fans call the sale a great move.
It's absurd.
As you were, then.
Conclusion
Good luck if you gamble.
When they pay off, congrats!
When wrong, admit it.
You must take chances if you want to succeed.
Risks don't always pay off.
Mr. Musk lacks insight and charisma to combine these two attributes.
I don’t like him, if you hadn’t figured.
It’s probably all of the cheating.
Ben "The Hosk" Hosking
3 years ago
The Yellow Cat Test Is Typically Failed by Software Developers.
Believe what you see, what people say
It’s sad that we never get trained to leave assumptions behind. - Sebastian Thrun
Many problems in software development are not because of code but because developers create the wrong software. This isn't rare because software is emergent and most individuals only realize what they want after it's built.
Inquisitive developers who pass the yellow cat test can improve the process.
Carpenters measure twice and cut the wood once. Developers are rarely so careful.
The Yellow Cat Test
Game of Thrones made dragons cool again, so I am reading The Game of Thrones book.
The yellow cat exam is from Syrio Forel, Arya Stark's fencing instructor.
Syrio tells Arya he'll strike left when fencing. He hits her after she dodges left. Arya says “you lied”. Syrio says his words lied, but his eyes and arm told the truth.
Arya learns how Syrio became Bravos' first sword.
“On the day I am speaking of, the first sword was newly dead, and the Sealord sent for me. Many bravos had come to him, and as many had been sent away, none could say why. When I came into his presence, he was seated, and in his lap was a fat yellow cat. He told me that one of his captains had brought the beast to him, from an island beyond the sunrise. ‘Have you ever seen her like?’ he asked of me.
“And to him I said, ‘Each night in the alleys of Braavos I see a thousand like him,’ and the Sealord laughed, and that day I was named the first sword.”
Arya screwed up her face. “I don’t understand.”
Syrio clicked his teeth together. “The cat was an ordinary cat, no more. The others expected a fabulous beast, so that is what they saw. How large it was, they said. It was no larger than any other cat, only fat from indolence, for the Sealord fed it from his own table. What curious small ears, they said. Its ears had been chewed away in kitten fights. And it was plainly a tomcat, yet the Sealord said ‘her,’ and that is what the others saw. Are you hearing?” Reddit discussion.
Development teams should not believe what they are told.
We created an appointment booking system. We thought it was an appointment-booking system. Later, we realized the software's purpose was to book the right people for appointments and discourage the unneeded ones.
The first 3 months of the project had half-correct requirements and software understanding.
Open your eyes
“Open your eyes is all that is needed. The heart lies and the head plays tricks with us, but the eyes see true. Look with your eyes, hear with your ears. Taste with your mouth. Smell with your nose. Feel with your skin. Then comes the thinking afterwards, and in that way, knowing the truth” Syrio Ferel
We must see what exists, not what individuals tell the development team or how developers think the software should work. Initial criteria cover 50/70% and change.
Developers build assumptions problems by assuming how software should work. Developers must quickly explain assumptions.
When a development team's assumptions are inaccurate, they must alter the code, DevOps, documentation, and tests.
It’s always faster and easier to fix requirements before code is written.
First-draft requirements can be based on old software. Development teams must grasp corporate goals and consider needs from many angles.
Testers help rethink requirements. They look at how software requirements shouldn't operate.
Technical features and benefits might misdirect software projects.
The initiatives that focused on technological possibilities developed hard-to-use software that needed extensive rewriting following user testing.
Software development
High-level criteria are different from detailed ones.
The interpretation of words determines their meaning.
Presentations are lofty, upbeat, and prejudiced.
People's perceptions may be unclear, incorrect, or just based on one perspective (half the story)
Developers can be misled by requirements, circumstances, people, plans, diagrams, designs, documentation, and many other things.
Developers receive misinformation, misunderstandings, and wrong assumptions. The development team must avoid building software with erroneous specifications.
Once code and software are written, the development team changes and fixes them.
Developers create software with incomplete information, they need to fill in the blanks to create the complete picture.
Conclusion
Yellow cats are often inaccurate when communicating requirements.
Before writing code, clarify requirements, assumptions, etc.
Everyone will pressure the development team to generate code rapidly, but this will slow down development.
Code changes are harder than requirements.