After 10 years of working in scale-ups, I've embraced a few concepts for scaling Tech and Product teams.

First, cross-functionalize teams. Product Managers represent the business, Product Designers the consumer, and Engineers build.

I organize teams of 5-10 individuals, following AWS's two pizza teams guidelines, with a Product Trio guiding each.

If more individuals are needed to reach a goal, I group teams under a Product Trio.

With Engineering being the biggest group, Staff/Principal Engineers often support the Trio on cross-team technical decisions.

Product Managers, Engineering Managers, or Engineers in the team may manage projects (depending on the project or aim), but the trio is collectively responsible for the team's output and outcome.

Once the Product Trio model is created, roles, duties, team ceremonies, and cooperation models must be clarified.

Keep reporting lines by discipline. Line managers are accountable for each individual's advancement, thus it's crucial that they know the work in detail.

Cross-team collaboration becomes more important after 3 teams (15-30 people). Teams can easily diverge in how they write code, run ceremonies, and build products.

Establishing groups of people that are cross-team, but grouped by discipline and skills, sharing and agreeing on working practices becomes critical.

The “Spotify Guild” model has been where I’ve taken a lot of my inspiration from.

Last, establish a taxonomy for communication channels.

In Slack, I create one channel per team and one per guild (and one for me to have discussions with the team leads).

These are just some of the basic principles I follow to organize teams.

A book I particularly like about team types and how they interact with each other is https://teamtopologies.com/.

Here's the fastest way to validate company concepts.

I squandered a year after dropping out of Stanford designing a product nobody wanted.

But today, I’m at 100k!

Differences:

I was designing a consumer product when I dropped out.

I coded MVP, got 1k users, and got YC interview.

Nice, huh?

WRONG!

Still coding and getting users 12 months later

WOULD PEOPLE PAY FOR IT? was the riskiest assumption I hadn't tested.

When asked why I didn't verify payment, I said,

Not-ready products. Now, nobody cares. The website needs work. Include this. Increase usage…

I feared people would say no.

After 1 year of pushing it off, my team told me they were really worried about the Business Model. Then I asked my audience if they'd buy my product.

So?

No, overwhelmingly.

I felt like I wasted a year building a product no one would buy.

Founders Cafe was the opposite.

Before building anything, I requested payment.

40 founders were interviewed.

Then we emailed Stanford, YC, and other top founders, asking them to join our community.

BOOM! 10/12 paid!

Without building anything, in 1 day I validated my startup's riskiest assumption. NOT 1 year.

Asking people to pay is one of the scariest things.

I understand.

I asked Stanford queer women to pay before joining my gay sorority.

I was afraid I'd turn them off or no one would pay.

Gay women, like those founders, were in such excruciating pain that they were willing to pay me upfront to help.

You can ask for payment (before you build) to see if people have the burning pain. Then they'll pay!

Examples from Founders Cafe members:

😮 Using a fake landing page, a college dropout tested a product. Paying! He built it and made $3m!

😮 YC solo founder faked a Powerpoint demo. 5 Enterprise paid LOIs. $1.5m raised, built, and in YC!

😮 A Harvard founder can convert Figma to React. 1 day, 10 customers. Built a tool to automate Figma -> React after manually fulfilling requests. 1m+

Bad example:

😭 Stanford Dropout Spends 1 Year Building Product Without Payment Validation

Some people build for a year and then get paying customers.

What I'm sharing is my experience and what Founders Cafe members have told me about validating startup ideas.

Don't waste a year like I did.

After my first startup failed, I planned to re-enroll at Stanford/work at Facebook.

After people paid, I quit for good.

I've hit $100k!

Hope this inspires you to request upfront payment! It'll change your life

How I monetized and sold an abandoned side project for $20,000

The Origin Story

I've always wanted to be an entrepreneur but never succeeded. I often had business ideas, made a landing page, and told my buddies. Never got customers.

In April 2021, I decided to try again with a new strategy. I noticed that I had trouble acquiring an initial set of customers, so I wanted to start by acquiring a product that had a small user base that I could grow.

I found a SaaS marketplace called MicroAcquire.com where you could buy and sell SaaS products. I liked Shareit.video, an online Loom-like screen recorder.

Shareit.video didn't generate revenue, but 50 people visited daily to record screencasts.

Purchasing a Failed Side Project

I eventually bought Shareit.video for $12,000 from its owner.

$12,000 was probably too much for a website without revenue or registered users.

I thought time was most important. I could have recreated the website, but it would take months. $12,000 would give me an organized code base and a working product with a few users to monetize.

I considered buying a screen recording website and trying to grow it versus buying a new car or investing in crypto with the $12K.

Buying the website would make me a real entrepreneur, which I wanted more than anything.

Putting down so much money would force me to commit to the project and prevent me from quitting too soon.

A Year of Development

I rebranded the website to be called RecordJoy and worked on it with my cousin for about a year. Within a year, we made $5000 and had 3000 users.

We spent $3500 on ads, hosting, and software to run the business.

AppSumo promoted our $120 Life Time Deal in exchange for 30% of the revenue.

We put RecordJoy on maintenance mode after 6 months because we couldn't find a scalable user acquisition channel.

We improved SEO and redesigned our landing page, but nothing worked.

Despite not being able to grow RecordJoy any further, I had already learned so much from working on the project so I was fine with putting it on maintenance mode. RecordJoy still made $500 a month, which was great lunch money.

Getting Taken Over

One of our customers emailed me asking for some feature requests and I replied that we weren’t going to add any more features in the near future. They asked if we'd sell.

We got on a call with the customer and I asked if he would be interested in buying RecordJoy for 15k. The customer wanted around $8k but would consider it.

Since we were negotiating with one buyer, we put RecordJoy on MicroAcquire to see if there were other offers.

We quickly received 10+ offers. We got 18.5k. There was also about $1000 in AppSumo that we could not withdraw, so we agreed to transfer that over for $600 since about 40% of our sales on AppSumo usually end up being refunded.

Lessons Learned

First, create an acquisition channel

We couldn't discover a scalable acquisition route for RecordJoy. If I had to start another project, I'd develop a robust acquisition channel first. It might be LinkedIn, Medium, or YouTube.

Purchase Power of the Buyer Affects Acquisition Price

Some of the buyers we spoke to were individuals looking to buy side projects, as well as companies looking to launch a new product category. Individual buyers had less budgets than organizations.

Customers of AppSumo vary.

AppSumo customers value lifetime deals and low prices, which may not be a good way to build a business with recurring revenue. Designed for AppSumo users, your product may not connect with other users.

Try to increase acquisition trust

Acquisition often fails. The buyer can go cold feet, cease communicating, or run away with your stuff. Trusting the buyer ensures a smooth asset exchange. First acquisition meeting was unpleasant and price negotiation was tight. In later meetings, we spent the first few minutes trying to get to know the buyer’s motivations and background before jumping into the negotiation, which helped build trust.

Operating expenses can reduce your earnings.

Monitor operating costs. We were really happy when we withdrew the $5000 we made from AppSumo and Stripe until we realized that we had spent $3500 in operating fees. Spend money on software and consultants to help you understand what to build.

Don't overspend on advertising

We invested $1500 on Google Ads but made little money. For a side project, it’s better to focus on organic traffic from SEO rather than paid ads unless you know your ads are going to have a positive ROI.

I've never seen this before.

Focus on native crypto development, not price activity or turmoil.

CT is boring now. Either folks are still angry about FTX or they're distracted by AI. Plus, it's year-end, and people rest for the holidays. 2022 was rough.

So DeFi fans can get inspired by something fresh. Who's building? As I read the Defillama daily roundup, many updates are still on FTX and its contagion.

I've used the same method on their Raises page. Not much happened :(. Maybe my high standards are to fault, but the business may be resting. OK.

The handful I locate might last us till the end of the year. (If another big blowup occurs.)

Hashflow

An on-chain monitor account I follow reported a huge transfer of $HFT from Binance to Jump Tradings.

I was intrigued. Stacking? So I checked and discovered out the project was launched through Binance Launchpad, which has introduced many 100x tokens (although momentarily) in the past, such as GALA and STEPN.

Hashflow appears to be pumpable. Binance launchpad, VC backers, CEX listing immediately. What's the protocol?

Hasflow is intriguing and timely, I discovered. After the FTX collapse, people looked more at DEXs.

Hashflow is a decentralized exchange that connects traders with professional market makers, according to its Binance launchpad description. Post-FTX, market makers lost their MM-ing chance with the collapse of the world's third-largest exchange. Jump and Wintermute back them?

Why is that the case? Hashflow doesn't use bonding curves like standard AMM. On AMMs, you pay more for the following trade because the prior trade reduces liquidity (supply and demand). With market maker quotations, you get a CEX-like experience (fewer coins in the pool, higher price). Stable prices, no MEV frontrunning.

Hashflow is innovative because...

DEXs gained from the FTX crash, but let's be honest: DEXs aren't as good as CEXs. Hashflow will change this.

Hashflow offers MEV protection, which major dealers seek in DEXs. You can trade large amounts without front running and sandwich assaults.

Hasflow offers a user-friendly swapping platform besides MEV. Any chain can be traded smoothly. This is a benefit because DEXs lag CEXs in UX.

Status, timeline:

Wintermute wrote in August that prominent market makers will work on Hashflow. Binance launched a month-long farming session in December. Jump probably participated in this initial sell, therefore we witnessed a significant transfer after the introduction.

Binance began trading HFT token on November 11 (the day FTX imploded). coincidence?)

Tokens are used for community rewards. Perhaps they'd copy dYdX. (Airdrop?). Read their documents about their future plans. Tokenomics doesn't impress me. Governance, rewards, and NFT.

Their stat page details their activity. First came Ethereum, then Arbitrum. For a new protocol in a bear market, they handled a lot of unique users daily.

It’s interesting to see their future. Will they be thriving? Not only against DEXs, but also among the CEXs too.

STFX

I forget how I found STFX. Possibly a Twitter thread concerning Arbitrum applications. STFX was the only new protocol I found interesting.

STFX is a new concept and trader problem-solver. I've never seen this protocol.

STFX allows you copy trades. You give someone your money to trade for you.

It's a marketplace. Traders are everywhere. You put your entry, exit, liquidation point, and trading theory. Twitter has a verification system for socials. Leaderboards display your trading skill.

This service could be popular. Staying disciplined is the hardest part of trading. Sometimes you take-profit too early or too late, or sell at a loss when an asset dumps, then it soon recovers (often happens in crypto.) It's hard to stick to entry-exit and liquidation plans.

What if you could hire someone to run your trade for a little commission? Set-and-forget.

Trading money isn't easy. Trust how? How do you know they won't steal your money?

Smart contracts.

STFX's trader is a vault maker/manager. One trade=one vault. User sets long/short, entrance, exit, and liquidation point. Anyone who agrees can exchange instantly. The smart contract will keep the fund during the trade and limit the manager's actions.

Here's STFX's transaction flow.

Managers and the treasury receive fees. It's a sustainable business strategy that benefits everyone.

I'm impressed by $STFX's planned use. Brilliant priority access. A crypto dealer opens a vault here. Many would join. STFX tokens offer VIP access over those without tokens.

STFX provides short-term trading, which is mind-blowing to me. I agree with their platform's purpose. Crypto market pricing actions foster short-termism. When you trade, the turnover could be larger than long-term holding or trading. 2017 BTC buyers waited 5 years to complete their holdings.

STFX teams simply adapted. Volatility aids trading.

All things about STFX scream Degen. The protocol fully embraces the degen nature of some, if not most, crypto natives.

An enjoyable dApp. Leaderboards are fun for reputation-building. FLEXING COMPETITIONS. You can join for as low as $10. STFX uses Arbitrum, therefore gas costs are low. Alpha procedure completes the degen feeling.

Despite looking like they don't take themselves seriously, I sense a strong business plan below. There is a real demand for the solution STFX offers.

And why we must keep arming Ukraine

Russian expatriates write about horrific news from home.

Read this from Nadin Brzezinski. She's not a native English speaker, so there are grammar errors, but her tale smells true.

Terrible truth.

There's much more that reveals Russia's grim reality.

Non-leadership. Millions of missing supplies are presumably sold for profit, leaving untrained troops without food or gear. Missile attacks pause because they run out. Fake schemes to hold talks as a way of stalling while they scramble for solutions.

Street men were mobilized. Millions will be ground up to please a crazed despot. Fear, wrath, and hunger pull apart civilization.

It's the most dystopian story, but Ukraine is worse. Destruction of a society, country, and civilization. Only the invaders' corruption and incompetence save the Ukrainians.

Rochester, NY. My suburb had many Soviet-era Ukrainian refugees. Their kids were my classmates. Fifty years later, many are still my friends. I loved their food and culture. My town has 20,000 Ukrainians.

Grieving but determined. They don't quit. They won't quit. Russians are eternal enemies.

It's the Russian people's willingness to tolerate corruption, abuse, and stupidity by their leaders. They are paying. 65000 dead. Ruined economy. No freedom to speak. Americans do not appreciate that freedom as we should.

It lets me write/publish.

Russian friends are shocked. Many are here because their parents escaped Russian anti-semitism and authoritarian oppression. A Russian cultural legacy says a strongman's methods are admirable.

A legacy of a slavery history disguised as serfdom. Peasants and Princes.

Read Tolstoy. Then Anna Karenina. The main characters are princes and counts, whose leaders are incompetent idiots with wealth and power.

Peasants who die in their wars due to incompetence are nameless ciphers.

Sound familiar?

Zero-Knowledge Proofs for Beginners

Published here originally.

Introduction

I Spy—did you play as a kid? One person chose a room object, and the other had to guess it by answering yes or no questions. I Spy was entertaining, but did you know it could teach you cryptography?

Zero Knowledge Proofs let you show your pal you know what they picked without exposing how. Math replaces electronics in this secret spy mission. Zero-knowledge proofs (ZKPs) are sophisticated cryptographic tools that allow one party to prove they have particular knowledge without revealing it. This proves identification and ownership, secures financial transactions, and more. This article explains zero-knowledge proofs and provides examples to help you comprehend this powerful technology.

What is a Proof of Zero Knowledge?

Zero-knowledge proofs prove a proposition is true without revealing any other information. This lets the prover show the verifier that they know a fact without revealing it. So, a zero-knowledge proof is like a magician's trick: the prover proves they know something without revealing how or what. Complex mathematical procedures create a proof the verifier can verify.

Want to find an easy way to test it out? Try out with tis awesome example! ZK Crush

Describe it as if I'm 5

Alex and Jack found a cave with a center entrance that only opens when someone knows the secret. Alex knows how to open the cave door and wants to show Jack without telling him.

Alex and Jack name both pathways (let’s call them paths A and B).

1. In the first phase, Alex is already inside the cave and is free to select either path, in this case A or B.

2. As Alex made his decision, Jack entered the cave and asked him to exit from the B path.

3. Jack can confirm that Alex really does know the key to open the door because he came out for the B path and used it.

To conclude, Alex and Jack repeat:

1. Alex walks into the cave.

2. Alex follows a random route.

3. Jack walks into the cave.

4. Alex is asked to follow a random route by Jack.

5. Alex follows Jack's advice and heads back that way.

What is a Zero Knowledge Proof?

At a high level, the aim is to construct a secure and confidential conversation between the prover and the verifier, where the prover convinces the verifier that they have the requisite information without disclosing it. The prover and verifier exchange messages and calculate in each round of the dialogue.

The prover uses their knowledge to prove they have the information the verifier wants during these rounds. The verifier can verify the prover's truthfulness without learning more by checking the proof's mathematical statement or computation.

Zero knowledge proofs use advanced mathematical procedures and cryptography methods to secure communication. These methods ensure the evidence is authentic while preventing the prover from creating a phony proof or the verifier from extracting unnecessary information.

ZK proofs require examples to grasp. Before the examples, there are some preconditions.

Criteria for Proofs of Zero Knowledge

1. Completeness: If the proposition being proved is true, then an honest prover will persuade an honest verifier that it is true.

2. Soundness: If the proposition being proved is untrue, no dishonest prover can persuade a sincere verifier that it is true.

3. Zero-knowledge: The verifier only realizes that the proposition being proved is true. In other words, the proof only establishes the veracity of the proposition being supported and nothing more.

The zero-knowledge condition is crucial. Zero-knowledge proofs show only the secret's veracity. The verifier shouldn't know the secret's value or other details.

Example after example after example

To illustrate, take a zero-knowledge proof with several examples:

Initial Password Verification Example

You want to confirm you know a password or secret phrase without revealing it.

Use a zero-knowledge proof:

1. You and the verifier settle on a mathematical conundrum or issue, such as figuring out a big number's components.

2. The puzzle or problem is then solved using the hidden knowledge that you have learned. You may, for instance, utilize your understanding of the password to determine the components of a particular number.

3. You provide your answer to the verifier, who can assess its accuracy without knowing anything about your private data.

4. You go through this process several times with various riddles or issues to persuade the verifier that you actually are aware of the secret knowledge.

You solved the mathematical puzzles or problems, proving to the verifier that you know the hidden information. The proof is zero-knowledge since the verifier only sees puzzle solutions, not the secret information.

In this scenario, the mathematical challenge or problem represents the secret, and solving it proves you know it. The evidence does not expose the secret, and the verifier just learns that you know it.

My simple example meets the zero-knowledge proof conditions:

1. Completeness: If you actually know the hidden information, you will be able to solve the mathematical puzzles or problems, hence the proof is conclusive.

2. Soundness: The proof is sound because the verifier can use a publicly known algorithm to confirm that your answer to the mathematical conundrum or difficulty is accurate.

3. Zero-knowledge: The proof is zero-knowledge because all the verifier learns is that you are aware of the confidential information. Beyond the fact that you are aware of it, the verifier does not learn anything about the secret information itself, such as the password or the factors of the number. As a result, the proof does not provide any new insights into the secret.

Explanation #2: Toss a coin.

One coin is biased to come up heads more often than tails, while the other is fair (i.e., comes up heads and tails with equal probability). You know which coin is which, but you want to show a friend you can tell them apart without telling them.

Use a zero-knowledge proof:

1. One of the two coins is chosen at random, and you secretly flip it more than once.

2. You show your pal the following series of coin flips without revealing which coin you actually flipped.

3. Next, as one of the two coins is flipped in front of you, your friend asks you to tell which one it is.

4. Then, without revealing which coin is which, you can use your understanding of the secret order of coin flips to determine which coin your friend flipped.

5. To persuade your friend that you can actually differentiate between the coins, you repeat this process multiple times using various secret coin-flipping sequences.

In this example, the series of coin flips represents the knowledge of biased and fair coins. You can prove you know which coin is which without revealing which is biased or fair by employing a different secret sequence of coin flips for each round.

The evidence is zero-knowledge since your friend does not learn anything about which coin is biased and which is fair other than that you can tell them differently. The proof does not indicate which coin you flipped or how many times you flipped it.

The coin-flipping example meets zero-knowledge proof requirements:

1. Completeness: If you actually know which coin is biased and which is fair, you should be able to distinguish between them based on the order of coin flips, and your friend should be persuaded that you can.

2. Soundness: Your friend may confirm that you are correctly recognizing the coins by flipping one of them in front of you and validating your answer, thus the proof is sound in that regard. Because of this, your acquaintance can be sure that you are not just speculating or picking a coin at random.

3. Zero-knowledge: The argument is that your friend has no idea which coin is biased and which is fair beyond your ability to distinguish between them. Your friend is not made aware of the coin you used to make your decision or the order in which you flipped the coins. Consequently, except from letting you know which coin is biased and which is fair, the proof does not give any additional information about the coins themselves.

Figure out the prime number in Example #3.

You want to prove to a friend that you know their product n=pq without revealing p and q. Zero-knowledge proof?

Use a variant of the RSA algorithm. Method:

1. You determine a new number s = r2 mod n by computing a random number r.

2. You email your friend s and a declaration that you are aware of the values of p and q necessary for n to equal pq.

3. A random number (either 0 or 1) is selected by your friend and sent to you.

4. You send your friend r as evidence that you are aware of the values of p and q if e=0. You calculate and communicate your friend's s/r if e=1.

5. Without knowing the values of p and q, your friend can confirm that you know p and q (in the case where e=0) or that s/r is a legitimate square root of s mod n (in the situation where e=1).

This is a zero-knowledge proof since your friend learns nothing about p and q other than their product is n and your ability to verify it without exposing any other information. You can prove that you know p and q by sending r or by computing s/r and sending that instead (if e=1), and your friend can verify that you know p and q or that s/r is a valid square root of s mod n without learning anything else about their values. This meets the conditions of completeness, soundness, and zero-knowledge.

Zero-knowledge proofs satisfy the following:

1. Completeness: The prover can demonstrate this to the verifier by computing q = n/p and sending both p and q to the verifier. The prover also knows a prime number p and a factorization of n as p*q.

2. Soundness: Since it is impossible to identify any pair of numbers that correctly factorize n without being aware of its prime factors, the prover is unable to demonstrate knowledge of any p and q that do not do so.

3. Zero knowledge: The prover only admits that they are aware of a prime number p and its associated factor q, which is already known to the verifier. This is the extent of their knowledge of the prime factors of n. As a result, the prover does not provide any new details regarding n's prime factors.

Types of Proofs of Zero Knowledge

Each zero-knowledge proof has pros and cons. Most zero-knowledge proofs are:

1. Interactive Zero Knowledge Proofs: The prover and the verifier work together to establish the proof in this sort of zero-knowledge proof. The verifier disputes the prover's assertions after receiving a sequence of messages from the prover. When the evidence has been established, the prover will employ these new problems to generate additional responses.

2. Non-Interactive Zero Knowledge Proofs: For this kind of zero-knowledge proof, the prover and verifier just need to exchange a single message. Without further interaction between the two parties, the proof is established.

3. A statistical zero-knowledge proof is one in which the conclusion is reached with a high degree of probability but not with certainty. This indicates that there is a remote possibility that the proof is false, but that this possibility is so remote as to be unimportant.

4. Succinct Non-Interactive Argument of Knowledge (SNARKs): SNARKs are an extremely effective and scalable form of zero-knowledge proof. They are utilized in many different applications, such as machine learning, blockchain technology, and more. Similar to other zero-knowledge proof techniques, SNARKs enable one party—the prover—to demonstrate to another—the verifier—that they are aware of a specific piece of information without disclosing any more information about that information.

5. The main characteristic of SNARKs is their succinctness, which refers to the fact that the size of the proof is substantially smaller than the amount of the original data being proved. Because to its high efficiency and scalability, SNARKs can be used in a wide range of applications, such as machine learning, blockchain technology, and more.

Uses for Zero Knowledge Proofs

ZKP applications include:

1. Verifying Identity ZKPs can be used to verify your identity without disclosing any personal information. This has uses in access control, digital signatures, and online authentication.

2. Proof of Ownership ZKPs can be used to demonstrate ownership of a certain asset without divulging any details about the asset itself. This has uses for protecting intellectual property, managing supply chains, and owning digital assets.

3. Financial Exchanges Without disclosing any details about the transaction itself, ZKPs can be used to validate financial transactions. Cryptocurrency, internet payments, and other digital financial transactions can all use this.

4. By enabling parties to make calculations on the data without disclosing the data itself, Data Privacy ZKPs can be used to preserve the privacy of sensitive data. Applications for this can be found in the financial, healthcare, and other sectors that handle sensitive data.

5. By enabling voters to confirm that their vote was counted without disclosing how they voted, elections ZKPs can be used to ensure the integrity of elections. This is applicable to electronic voting, including internet voting.

6. Cryptography Modern cryptography's ZKPs are a potent instrument that enable secure communication and authentication. This can be used for encrypted messaging and other purposes in the business sector as well as for military and intelligence operations.

Proofs of Zero Knowledge and Compliance

Kubernetes and regulatory compliance use ZKPs in many ways. Examples:

1. Security for Kubernetes ZKPs offer a mechanism to authenticate nodes without disclosing any sensitive information, enhancing the security of Kubernetes clusters. ZKPs, for instance, can be used to verify, without disclosing the specifics of the program, that the nodes in a Kubernetes cluster are running permitted software.

2. Compliance Inspection Without disclosing any sensitive information, ZKPs can be used to demonstrate compliance with rules like the GDPR, HIPAA, and PCI DSS. ZKPs, for instance, can be used to demonstrate that data has been encrypted and stored securely without divulging the specifics of the mechanism employed for either encryption or storage.

3. Access Management Without disclosing any private data, ZKPs can be used to offer safe access control to Kubernetes resources. ZKPs can be used, for instance, to demonstrate that a user has the necessary permissions to access a particular Kubernetes resource without disclosing the details of those permissions.

4. Safe Data Exchange Without disclosing any sensitive information, ZKPs can be used to securely transmit data between Kubernetes clusters or between several businesses. ZKPs, for instance, can be used to demonstrate the sharing of a specific piece of data between two parties without disclosing the details of the data itself.

5. Kubernetes deployments audited Without disclosing the specifics of the deployment or the data being processed, ZKPs can be used to demonstrate that Kubernetes deployments are working as planned. This can be helpful for auditing purposes and for ensuring that Kubernetes deployments are operating as planned.

ZKPs preserve data and maintain regulatory compliance by letting parties prove things without revealing sensitive information. ZKPs will be used more in Kubernetes as it grows.