Fairness alternatives to selling below market clearing prices (or community sentiment, or fun)
When a seller has a limited supply of an item in high (or uncertain and possibly high) demand, they frequently set a price far below what "the market will bear." As a result, the item sells out quickly, with lucky buyers being those who tried to buy first. This has happened in the Ethereum ecosystem, particularly with NFT sales and token sales/ICOs. But this phenomenon is much older; concerts and restaurants frequently make similar choices, resulting in fast sell-outs or long lines.
Why do sellers do this? Economists have long wondered. A seller should sell at the market-clearing price if the amount buyers are willing to buy exactly equals the amount the seller has to sell. If the seller is unsure of the market-clearing price, they should sell at auction and let the market decide. So, if you want to sell something below market value, don't do it. It will hurt your sales and it will hurt your customers. The competitions created by non-price-based allocation mechanisms can sometimes have negative externalities that harm third parties, as we will see.
However, the prevalence of below-market-clearing pricing suggests that sellers do it for good reason. And indeed, as decades of research into this topic has shown, there often are. So, is it possible to achieve the same goals with less unfairness, inefficiency, and harm?
Selling at below market-clearing prices has large inefficiencies and negative externalities
An item that is sold at market value or at an auction allows someone who really wants it to pay the high price or bid high in the auction. So, if a seller sells an item below market value, some people will get it and others won't. But the mechanism deciding who gets the item isn't random, and it's not always well correlated with participant desire. It's not always about being the fastest at clicking buttons. Sometimes it means waking up at 2 a.m. (but 11 p.m. or even 2 p.m. elsewhere). Sometimes it's just a "auction by other means" that's more chaotic, less efficient, and has far more negative externalities.
There are many examples of this in the Ethereum ecosystem. Let's start with the 2017 ICO craze. For example, an ICO project would set the price of the token and a hard maximum for how many tokens they are willing to sell, and the sale would start automatically at some point in time. The sale ends when the cap is reached.
So what? In practice, these sales often ended in 30 seconds or less. Everyone would start sending transactions in as soon as (or just before) the sale started, offering higher and higher fees to encourage miners to include their transaction first. Instead of the token seller receiving revenue, miners receive it, and the sale prices out all other applications on-chain.
The most expensive transaction in the BAT sale set a fee of 580,000 gwei, paying a fee of $6,600 to get included in the sale.
Many ICOs after that tried various strategies to avoid these gas price auctions; one ICO notably had a smart contract that checked the transaction's gasprice and rejected it if it exceeded 50 gwei. But that didn't solve the issue. Buyers hoping to game the system sent many transactions hoping one would get through. An auction by another name, clogging the chain even more.
ICOs have recently lost popularity, but NFTs and NFT sales have risen in popularity. But the NFT space didn't learn from 2017; they do fixed-quantity sales just like ICOs (eg. see the mint function on lines 97-108 of this contract here). So what?
That's not the worst; some NFT sales have caused gas price spikes of up to 2000 gwei.
High gas prices from users fighting to get in first by sending higher and higher transaction fees. An auction renamed, pricing out all other applications on-chain for 15 minutes.
So why do sellers sometimes sell below market price?
Selling below market value is nothing new, and many articles, papers, and podcasts have written (and sometimes bitterly complained) about the unwillingness to use auctions or set prices to market-clearing levels.
Many of the arguments are the same for both blockchain (NFTs and ICOs) and non-blockchain examples (popular restaurants and concerts). Fairness and the desire not to exclude the poor, lose fans or create tension by being perceived as greedy are major concerns. The 1986 paper by Kahneman, Knetsch, and Thaler explains how fairness and greed can influence these decisions. I recall that the desire to avoid perceptions of greed was also a major factor in discouraging the use of auction-like mechanisms in 2017.
Aside from fairness concerns, there is the argument that selling out and long lines create a sense of popularity and prestige, making the product more appealing to others. Long lines should have the same effect as high prices in a rational actor model, but this is not the case in reality. This applies to ICOs and NFTs as well as restaurants. Aside from increasing marketing value, some people find the game of grabbing a limited set of opportunities first before everyone else is quite entertaining.
But there are some blockchain-specific factors. One argument for selling ICO tokens below market value (and one that persuaded the OmiseGo team to adopt their capped sale strategy) is community dynamics. The first rule of community sentiment management is to encourage price increases. People are happy if they are "in the green." If the price drops below what the community members paid, they are unhappy and start calling you a scammer, possibly causing a social media cascade where everyone calls you a scammer.
This effect can only be avoided by pricing low enough that post-launch market prices will almost certainly be higher. But how do you do this without creating a rush for the gates that leads to an auction?
Interesting solutions
It's 2021. We have a blockchain. The blockchain is home to a powerful decentralized finance ecosystem, as well as a rapidly expanding set of non-financial tools. The blockchain also allows us to reset social norms. Where decades of economists yelling about "efficiency" failed, blockchains may be able to legitimize new uses of mechanism design. If we could use our more advanced tools to create an approach that more directly solves the problems, with fewer side effects, wouldn't that be better than fiddling with a coarse-grained one-dimensional strategy space of selling at market price versus below market price?
Begin with the goals. We'll try to cover ICOs, NFTs, and conference tickets (really a type of NFT) all at the same time.
1. Fairness: don't completely exclude low-income people from participation; give them a chance. The goal of token sales is to avoid high initial wealth concentration and have a larger and more diverse initial token holder community.
2. Don’t create races: Avoid situations where many people rush to do the same thing and only a few get in (this is the type of situation that leads to the horrible auctions-by-another-name that we saw above).
3. Don't require precise market knowledge: the mechanism should work even if the seller has no idea how much demand exists.
4. Fun: The process of participating in the sale should be fun and game-like, but not frustrating.
5. Give buyers positive expected returns: in the case of a token (or an NFT), buyers should expect price increases rather than decreases. This requires selling below market value.
Let's start with (1). From Ethereum's perspective, there is a simple solution. Use a tool designed for the job: proof of personhood protocols! Here's one quick idea:
Mechanism 1 Each participant (verified by ID) can buy up to ‘’X’’ tokens at price P, with the option to buy more at an auction.
With the per-person mechanism, buyers can get positive expected returns for the portion sold through the per-person mechanism, and the auction part does not require sellers to understand demand levels. Is it race-free? The number of participants buying through the per-person pool appears to be high. But what if the per-person pool isn't big enough to accommodate everyone?
Make the per-person allocation amount dynamic.
Mechanism 2 Each participant can deposit up to X tokens into a smart contract to declare interest. Last but not least, each buyer receives min(X, N / buyers) tokens, where N is the total sold through the per-person pool (some other amount can also be sold by auction). The buyer gets their deposit back if it exceeds the amount needed to buy their allocation.
No longer is there a race condition based on the number of buyers per person. No matter how high the demand, it's always better to join sooner rather than later.
Here's another idea if you like clever game mechanics with fancy quadratic formulas.
Mechanism 3 Each participant can buy X units at a price P X 2 up to a maximum of C tokens per buyer. C starts low and gradually increases until enough units are sold.
The quantity allocated to each buyer is theoretically optimal, though post-sale transfers will degrade this optimality over time. Mechanisms 2 and 3 appear to meet all of the above objectives. They're not perfect, but they're good starting points.
One more issue. For fixed and limited supply NFTs, the equilibrium purchased quantity per participant may be fractional (in mechanism 2, number of buyers > N, and in mechanism 3, setting C = 1 may already lead to over-subscription). With fractional sales, you can offer lottery tickets: if there are N items available, you have a chance of N/number of buyers of getting the item, otherwise you get a refund. For a conference, groups could bundle their lottery tickets to guarantee a win or a loss. The certainty of getting the item can be auctioned.
The bottom tier of "sponsorships" can be used to sell conference tickets at market rate. You may end up with a sponsor board full of people's faces, but is that okay? After all, John Lilic was on EthCC's sponsor board!
Simply put, if you want to be reliably fair to people, you need an input that explicitly measures people. Authentication protocols do this (and if desired can be combined with zero knowledge proofs to ensure privacy). So we should combine the efficiency of market and auction-based pricing with the equality of proof of personhood mechanics.
Answers to possible questions
Q: Won't people who don't care about your project buy the item and immediately resell it?
A: Not at first. Meta-games take time to appear in practice. If they do, making them untradeable for a while may help mitigate the damage. Using your face to claim that your previous account was hacked and that your identity, including everything in it, should be moved to another account works because proof-of-personhood identities are untradeable.
Q: What if I want to make my item available to a specific community?
A: Instead of ID, use proof of participation tokens linked to community events. Another option, also serving egalitarian and gamification purposes, is to encrypt items within publicly available puzzle solutions.
Q: How do we know they'll accept? Strange new mechanisms have previously been resisted.
A: Having economists write screeds about how they "should" accept a new mechanism that they find strange is difficult (or even "equity"). However, abrupt changes in context effectively reset people's expectations. So the blockchain space is the best place to try this. You could wait for the "metaverse", but it's possible that the best version will run on Ethereum anyway, so start now.
More on Web3 & Crypto
Nitin Sharma
2 years ago
Web3 Terminology You Should Know
The easiest online explanation.
Web3 is growing. Crypto companies are growing.
Instagram, Adidas, and Stripe adopted cryptocurrency.
Bitcoin and other cryptocurrencies made web3 famous.
Most don't know where to start. Cryptocurrency, DeFi, etc. are investments.
Since we don't understand web3, I'll help you today.
Let’s go.
1. Web3
It is the third generation of the web, and it is built on the decentralization idea which means no one can control it.
There are static webpages that we can only read on the first generation of the web (i.e. Web 1.0).
Web 2.0 websites are interactive. Twitter, Medium, and YouTube.
Each generation controlled the website owner. Simply put, the owner can block us. However, data breaches and selling user data to other companies are issues.
They can influence the audience's mind since they have control.
Assume Twitter's CEO endorses Donald Trump. Result? Twitter would have promoted Donald Trump with tweets and graphics, enhancing his chances of winning.
We need a decentralized, uncontrollable system.
And then there’s Web3.0 to consider. As Bitcoin and Ethereum values climb, so has its popularity. Web3.0 is uncontrolled web evolution. It's good and bad.
Dapps, DeFi, and DAOs are here. It'll all be explained afterwards.
2. Cryptocurrencies:
No need to elaborate.
Bitcoin, Ethereum, Cardano, and Dogecoin are cryptocurrencies. It's digital money used for payments and other uses.
Programs must interact with cryptocurrencies.
3. Blockchain:
Blockchain facilitates bitcoin transactions, investments, and earnings.
This technology governs Web3. It underpins the web3 environment.
Let us delve much deeper.
Blockchain is simple. However, the name expresses the meaning.
Blockchain is a chain of blocks.
Let's use an image if you don't understand.
The graphic above explains blockchain. Think Blockchain. The block stores related data.
Here's more.
4. Smart contracts
Programmers and developers must write programs. Smart contracts are these blockchain apps.
That’s reasonable.
Decentralized web3.0 requires immutable smart contracts or programs.
5. NFTs
Blockchain art is NFT. Non-Fungible Tokens.
Explaining Non-Fungible Token may help.
Two sorts of tokens:
These tokens are fungible, meaning they can be changed. Think of Bitcoin or cash. The token won't change if you sell one Bitcoin and acquire another.
Non-Fungible Token: Since these tokens cannot be exchanged, they are exclusive. For instance, music, painting, and so forth.
Right now, Companies and even individuals are currently developing worthless NFTs.
The concept of NFTs is much improved when properly handled.
6. Dapp
Decentralized apps are Dapps. Instagram, Twitter, and Medium apps in the same way that there is a lot of decentralized blockchain app.
Curve, Yearn Finance, OpenSea, Axie Infinity, etc. are dapps.
7. DAOs
DAOs are member-owned and governed.
Consider it a company with a core group of contributors.
8. DeFi
We all utilize centrally regulated financial services. We fund these banks.
If you have $10,000 in your bank account, the bank can invest it and retain the majority of the profits.
We only get a penny back. Some banks offer poor returns. To secure a loan, we must trust the bank, divulge our information, and fill out lots of paperwork.
DeFi was built for such issues.
Decentralized banks are uncontrolled. Staking, liquidity, yield farming, and more can earn you money.
Web3 beginners should start with these resources.
Marco Manoppo
3 years ago
Failures of DCG and Genesis
Don't sleep with your own sister.
70% of lottery winners go broke within five years. You've heard the last one. People who got rich quickly without setbacks and hard work often lose it all. My father said, "Easy money is easily lost," and a wealthy friend who owns a family office said, "The first generation makes it, the second generation spends it, and the third generation blows it."
This is evident. Corrupt politicians in developing countries live lavishly, buying their third wives' fifth Hermès bag and celebrating New Year's at The Brando Resort. A successful businessperson from humble beginnings is more conservative with money. More so if they're atom-based, not bit-based. They value money.
Crypto can "feel" easy. I have nothing against capital market investing. The global financial system is shady, but that's another topic. The problem started when those who took advantage of easy money started affecting other businesses. VCs did minimal due diligence on FTX because they needed deal flow and returns for their LPs. Lenders did minimum diligence and underwrote ludicrous loans to 3AC because they needed revenue.
Alameda (hence FTX) and 3AC made "easy money" Genesis and DCG aren't. Their businesses are more conventional, but they underestimated how "easy money" can hurt them.
Genesis has been the victim of easy money hubris and insolvency, losing $1 billion+ to 3AC and $200M to FTX. We discuss the implications for the broader crypto market.
Here are the quick takeaways:
Genesis is one of the largest and most notable crypto lenders and prime brokerage firms.
DCG and Genesis have done related party transactions, which can be done right but is a bad practice.
Genesis owes DCG $1.5 billion+.
If DCG unwinds Grayscale's GBTC, $9-10 billion in BTC will hit the market.
DCG will survive Genesis.
What happened?
Let's recap the FTX shenanigan from two weeks ago. Shenanigans! Delphi's tweet sums up the craziness. Genesis has $175M in FTX.
Cred's timeline: I hate bad crisis management. Yes, admitting their balance sheet hole right away might've sparked more panic, and there's no easy way to convey your trouble, but no one ever learns.
By November 23, rumors circulated online that the problem could affect Genesis' parent company, DCG. To address this, Barry Silbert, Founder, and CEO of DCG released a statement to shareholders.
A few things are confirmed thanks to this statement.
DCG owes $1.5 billion+ to Genesis.
$500M is due in 6 months, and the rest is due in 2032 (yes, that’s not a typo).
Unless Barry raises new cash, his last-ditch efforts to repay the money will likely push the crypto market lower.
Half a year of GBTC fees is approximately $100M.
They can pay $500M with GBTC.
With profits, sell another port.
Genesis has hired a restructuring adviser, indicating it is in trouble.
Rehypothecation
Every crypto problem in the past year seems to be rehypothecation between related parties, excessive leverage, hubris, and the removal of the money printer. The Bankless guys provided a chart showing 2021 crypto yield.
In June 2022, @DataFinnovation published a great investigation about 3AC and DCG. Here's a summary.
3AC borrowed BTC from Genesis and pledged it to create Grayscale's GBTC shares.
3AC uses GBTC to borrow more money from Genesis.
This lets 3AC leverage their capital.
3AC's strategy made sense because GBTC had a premium, creating "free money."
GBTC's discount and LUNA's implosion caused problems.
3AC lost its loan money in LUNA.
Margin called on 3ACs' GBTC collateral.
DCG bought GBTC to avoid a systemic collapse and a larger discount.
Genesis lost too much money because 3AC can't pay back its loan. DCG "saved" Genesis, but the FTX collapse hurt Genesis further, forcing DCG and Genesis to seek external funding.
bruh…
Learning Experience
Co-borrowing. Unnecessary rehypothecation. Extra space. Governance disaster. Greed, hubris. Crypto has repeatedly shown it can recreate traditional financial system disasters quickly. Working in crypto is one of the best ways to learn crazy financial tricks people will do for a quick buck much faster than if you dabble in traditional finance.
Moving Forward
I think the crypto industry needs to consider its future. This is especially true for professionals. I'm not trying to scare you. In 2018 and 2020, I had doubts. No doubts now. Detailing the crypto industry's potential outcomes helped me gain certainty and confidence in its future. This includes VCs' benefits and talking points during the bull market, as well as what would happen if government regulations became hostile, etc. Even if that happens, I'm certain. This is permanent. I may write a post about that soon.
Sincerely,
M.
joyce shen
3 years ago
Framework to Evaluate Metaverse and Web3
Everywhere we turn, there's a new metaverse or Web3 debut. Microsoft recently announced a $68.7 BILLION cash purchase of Activision.
Like AI in 2013 and blockchain in 2014, NFT growth in 2021 feels like this year's metaverse and Web3 growth. We are all bombarded with information, conflicting signals, and a sensation of FOMO.
How can we evaluate the metaverse and Web3 in a noisy, new world? My framework for evaluating upcoming technologies and themes is shown below. I hope you will also find them helpful.
Understand the “pipes” in a new space.
Whatever people say, Metaverse and Web3 will have to coexist with the current Internet. Companies who host, move, and store data over the Internet have a lot of intriguing use cases in Metaverse and Web3, whether in infrastructure, data analytics, or compliance. Hence the following point.
## Understand the apps layer and their infrastructure.
Gaming, crypto exchanges, and NFT marketplaces would not exist today if not for technology that enables rapid app creation. Yes, according to Chainalysis and other research, 30–40% of Ethereum is self-hosted, with the rest hosted by large cloud providers. For Microsoft to acquire Activision makes strategic sense. It's not only about the games, but also the infrastructure that supports them.
Follow the money
Understanding how money and wealth flow in a complex and dynamic environment helps build clarity. Unless you are exceedingly wealthy, you have limited ability to significantly engage in the Web3 economy today. Few can just buy 10 ETH and spend it in one day. You must comprehend who benefits from the process, and how that 10 ETH circulates now and possibly tomorrow. Major holders and players control supply and liquidity in any market. Today, most Web3 apps are designed to increase capital inflow so existing significant holders can utilize it to create a nascent Web3 economy. When you see a new Metaverse or Web3 application, remember how money flows.
What is the use case?
What does the app do? If there is no clear use case with clear makers and consumers solving a real problem, then the euphoria soon fades, and the only stakeholders who remain enthused are those who have too much to lose.
Time is a major competition that is often overlooked.
We're only busier, but each day is still 24 hours. Using new apps may mean that time is lost doing other things. The user must be eager to learn. Metaverse and Web3 vs. our time? I don't think we know the answer yet (at least for working adults whose cost of time is higher).
I don't think we know the answer yet (at least for working adults whose cost of time is higher).
People and organizations need security and transparency.
For new technologies or apps to be widely used, they must be safe, transparent, and trustworthy. What does secure Metaverse and Web3 mean? This is an intriguing subject for both the business and public sectors. Cloud adoption grew in part due to improved security and data protection regulations.
The following frameworks can help analyze and understand new technologies and emerging technological topics, unless you are a significant investment fund with the financial ability to gamble on numerous initiatives and essentially form your own “index fund”.
I write on VC, startups, and leadership.
More on https://www.linkedin.com/in/joycejshen/ and https://joyceshen.substack.com/
This writing is my own opinion and does not represent investment advice.
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Looi Qin En
3 years ago
I polled 52 product managers to find out what qualities make a great Product Manager
Great technology opens up an universe of possibilities.
Need a friend? WhatsApp, Telegram, Slack, etc.
Traveling? AirBnB, Expedia, Google Flights, etc.
Money transfer? Use digital banking, e-wallet, or crypto applications
Products inspire us. How do we become great?
I asked product managers in my network:
What does it take to be a great product manager?
52 product managers from 40+ prominent IT businesses in Southeast Asia responded passionately. Many of the PMs I've worked with have built fantastic products, from unicorns (Lazada, Tokopedia, Ovo) to incumbents (Google, PayPal, Experian, WarnerMedia) to growing (etaily, Nium, Shipper).
TL;DR:
Soft talents are more important than hard skills. Technical expertise was hardly ever stressed by product managers, and empathy was mentioned more than ten times. Janani from Xendit expertly recorded the moment. A superb PM must comprehend that their empathy for the feelings of their users must surpass all logic and data.
Constant attention to the needs of the user. Many people concur that the closer a PM gets to their customer/user, the more likely it is that the conclusion will be better. There were almost 30 references to customers and users. Focusing on customers has the advantage because it is hard to overshoot, as Rajesh from Lazada puts it best.
Setting priorities is invaluable. Prioritization is essential because there are so many problems that a PM must deal with every day. My favorite quotation on this is from Rakuten user Yee Jie. Viki, A competent product manager extinguishes fires. A good product manager lets things burn and then prioritizes.
This summary isn't enough to capture what excellent PMs claim it requires. Read below!
What qualities make a successful product manager?
Themed quotes are alphabetized by author.
Embrace your user/customer
Aeriel Dela Paz, Rainmaking Venture Architect, ex-GCash Product Head
Great PMs know what customers need even when they don’t say it directly. It’s about reading between the lines and going through the numbers to address that need.
Anders Nordahl, OrkestraSCS's Product Manager
Understanding the vision of your customer is as important as to get the customer to buy your vision
Angel Mendoza, MetaverseGo's Product Head
Most people think that to be a great product manager, you must have technical know-how. It’s textbook and I do think it is helpful to some extent, but for me the secret sauce is EMPATHY — the ability to see and feel things from someone else’s perspective. You can’t create a solution without deeply understanding the problem.
Senior Product Manager, Tokopedia
Focus on delivering value and helping people (consumer as well as colleague) and everything else will follow
Darren Lau, Deloitte Digital's Head of Customer Experience
Start with the users, and work backwards. Don’t have a solution looking for a problem
Darryl Tan, Grab Product Manager
I would say that a great product manager is able to identify the crucial problems to solve through strong user empathy and synthesis of insights
Diego Perdana, Kitalulus Senior Product Manager
I think to be a great product manager you need to be obsessed with customer problems and most important is solve the right problem with the right solution
Senior Product Manager, AirAsia
Lot of common sense + Customer Obsession. The most important role of a Product manager is to bring clarity of a solution. Your product is good if it solves customer problems. Your product is great if it solves an eco-system problem and disrupts the business in a positive way.
Edward Xie, Mastercard Managing Consultant, ex-Shopee Product Manager
Perfect your product, but be prepared to compromise for right users
AVP Product, Shipper
For me, a great product manager need to be rational enough to find the business opportunities while obsessing the customers.
Janani Gopalakrishnan is a senior product manager of a stealth firm.
While as a good PM it’s important to be data-driven, to be a great PM one needs to understand that their empathy for their users’ emotions must exceed all logic and data. Great PMs also make these product discussions thrive within the team by intently listening to all the members thoughts and influence the team’s skin in the game positively.
Director, Product Management, Indeed
Great product managers put their users first. They discover problems that matter most to their users and inspire their team to find creative solutions.
Grab's Senior Product Manager Lakshay Kalra
Product management is all about finding and solving most important user problems
Quipper's Mega Puji Saraswati
First of all, always remember the value of “user first” to solve what user really needs (the main problem) for guidance to arrange the task priority and develop new ideas. Second, ownership. Treat the product as your “2nd baby”, and the team as your “2nd family”. Third, maintain a good communication, both horizontally and vertically. But on top of those, always remember to have a work — life balance, and know exactly the priority in life :)
Senior Product Manager, Prosa.AI Miswanto Miswanto
A great Product Manager is someone who can be the link between customer needs with the readiness and flexibility of the team. So that it can provide, build, and produce a product that is useful and helps the community to carry out their daily activities. And He/She can improve product quality ongoing basis or continuous to help provide solutions for users or our customer.
Lead Product Manager, Tokopedia, Oriza Wahyu Utami
Be a great listener, be curious and be determined. every great product manager have the ability to listen the pain points and understand the problems, they are always curious on the users feedback, and they also very determined to look for the solutions that benefited users and the business.
99 Group CPO Rajesh Sangati
The advantage of focusing on customers: it’s impossible to overshoot
Ray Jang, founder of Scenius, formerly of ByteDance
The difference between good and great product managers is that great product managers are willing to go the unsexy and unglamorous extra mile by rolling up their sleeves and ironing out all minutiae details of the product such that when the user uses the product, they can’t help but say “This was made for me.”
BCG Digital Ventures' Sid Narayanan
Great product managers ensure that what gets built and shipped is at the intersection of what creates value for the customer and for the business that’s building the product…often times, especially in today’s highly liquid funding environment, the unit economics, aka ensuring that what gets shipped creates value for the business and is sustainable, gets overlooked
Stephanie Brownlee, BCG Digital Ventures Product Manager
There is software in the world that does more harm than good to people and society. Great Product Managers build products that solve problems not create problems
Experiment constantly
Delivery Hero's Abhishek Muralidharan
Embracing your failure is the key to become a great Product Manager
DeliveryHero's Anuraag Burman
Product Managers should be thick skinned to deal with criticism and the stomach to take risk and face failures.
DataSpark Product Head Apurva Lawale
Great product managers enjoy the creative process with their team to deliver intuitive user experiences to benefit users.
Dexter Zhuang, Xendit Product Manager
The key to creating winning products is building what customers want as quickly as you can — testing and learning along the way.
PayPal's Jay Ko
To me, great product managers always remain relentlessly curious. They are empathetic leaders and problem solvers that glean customer insights into building impactful products
Home Credit Philippines' Jedd Flores
Great Product Managers are the best dreamers; they think of what can be possible for the customers, for the company and the positive impact that it will have in the industry that they’re part of
Set priorities first, foremost, foremost.
HBO Go Product Manager Akshay Ishwar
Good product managers strive to balance the signal to noise ratio, Great product managers know when to turn the dials for each up exactly
Zuellig Pharma's Guojie Su
Have the courage to say no. Managing egos and request is never easy and rejecting them makes it harder but necessary to deliver the best value for the customers.
Ninja Van's John Prawira
(1) PMs should be able to ruthlessly prioritize. In order to be effective, PMs should anchor their product development process with their north stars (success metrics) and always communicate with a purpose. (2) User-first when validating assumptions. PMs should validate assumptions early and often to manage risk when leading initiatives with a focus on generating the highest impact to solving a particular user pain-point. We can’t expect a product/feature launch to be perfect (there might be bugs or we might not achieve our success metric — which is where iteration comes in), but we should try our best to optimize on user-experience earlier on.
Nium Product Manager Keika Sugiyama
I’d say a great PM holds the ability to balance ruthlessness and empathy at the same time. It’s easier said than done for sure!
ShopBack product manager Li Cai
Great product managers are like great Directors of movies. They do not create great products/movies by themselves. They deliver it by Defining, Prioritising, Energising the team to deliver what customers love.
Quincus' Michael Lim
A great product manager, keeps a pulse on the company’s big picture, identifies key problems, and discerns its rightful prioritization, is able to switch between the macro perspective to micro specifics, and communicates concisely with humility that influences naturally for execution
Mathieu François-Barseghian, SVP, Citi Ventures
“You ship your org chart”. This is Conway’s Law short version (1967!): the fundamental socio-technical driver behind innovation successes (Netflix) and failures (your typical bank). The hype behind micro-services is just another reflection of Conway’s Law
Mastercard's Regional Product Manager Nikhil Moorthy
A great PM should always look to build products which are scalable & viable , always keep the end consumer journey in mind. Keeping things simple & having a MVP based approach helps roll out products faster. One has to test & learn & then accordingly enhance / adapt, these are key to success
Rendy Andi, Tokopedia Product Manager
Articulate a clear vision and the path to get there, Create a process that delivers the best results and Be serious about customers.
Senior Product Manager, DANA Indonesia
Own the problem, not the solution — Great PMs are outstanding problem preventers. Great PMs are discerning about which problems to prevent, which problems to solve, and which problems not to solve
Tat Leong Seah, LionsBot International Senior UX Engineer, ex-ViSenze Product Manager
Prioritize outcomes for your users, not outputs of your system” or more succinctly “be agile in delivering value; not features”
Senior Product Manager, Rakuten Viki
A good product manager puts out fires. A great product manager lets fires burn and prioritize from there
acquire fundamental soft skills
Oracle NetSuite's Astrid April Dominguez
Personally, i believe that it takes grit, empathy, and optimistic mindset to become a great PM
Ovo Lead Product Manager Boy Al Idrus
Contrary to popular beliefs, being a great product manager doesn’t have anything to do with technicals, it sure plays a part but most important weapons are: understanding pain points of users, project management, sympathy in leadership and business critical skills; these 4 aspects would definitely help you to become a great product manager.
PwC Product Manager Eric Koh
Product managers need to be courageous to be successful. Courage is required to dive deep, solving big problems at its root and also to think far and dream big to achieve bold visions for your product
Ninja Van's Product Director
In my opinion the two most important ingredients to become a successful product manager is: 1. Strong critical thinking 2. Strong passion for the work. As product managers, we typically need to solve very complex problems where the answers are often very ambiguous. The work is tough and at times can be really frustrating. The 2 ingredients I mentioned earlier will be critical towards helping you to slowly discover the solution that may become a game changer.
PayPal's Lead Product Manager
A great PM has an eye of a designer, the brain of an engineer and the tongue of a diplomat
Product Manager Irene Chan
A great Product Manager is able to think like a CEO of the company. Visionary with Agile Execution in mind
Isabella Yamin, Rakuten Viki Product Manager
There is no one model of being a great product person but what I’ve observed from people I’ve had the privilege working with is an overflowing passion for the user problem, sprinkled with a knack for data and negotiation
Google product manager Jachin Cheng
Great product managers start with abundant intellectual curiosity and grow into a classic T-shape. Horizontally: generalists who range widely, communicate fluidly and collaborate easily cross-functionally, connect unexpected dots, and have the pulse both internally and externally across users, stakeholders, and ecosystem players. Vertically: deep product craftsmanship comes from connecting relentless user obsession with storytelling, business strategy with detailed features and execution, inspiring leadership with risk mitigation, and applying the most relevant tools to solving the right problems.
Jene Lim, Experian's Product Manager
3 Cs and 3 Rs. Critical thinking , Customer empathy, Creativity. Resourcefulness, Resilience, Results orientation.
Nirenj George, Envision Digital's Security Product Manager
A great product manager is someone who can lead, collaborate and influence different stakeholders around the product vision, and should be able to execute the product strategy based on customer insights, as well as take ownership of the product roadmap to create a greater impact on customers.
Grab's Lead Product Manager
Product Management is a multi-dimensional role that looks very different across each product team so each product manager has different challenges to deal with but what I have found common among great product managers is ability to create leverage through their efforts to drive outsized impacts for their products. This leverage is built using data with intuition, building consensus with stakeholders, empowering their teams and focussed efforts on needle moving work.
NCS Product Manager Umar Masagos
To be a great product manager, one must master both the science and art of Product Management. On one hand, you need have a strong understanding of the tools, metrics and data you need to drive your product. On the other hand, you need an in-depth understanding of your organization, your target market and target users, which is often the more challenging aspect to master.
M1 product manager Wei Jiao Keong
A great product manager is multi-faceted. First, you need to have the ability to see the bigger picture, yet have a keen eye for detail. Secondly, you are empathetic and is able to deliver products with exceptional user experience while being analytical enough to achieve business outcomes. Lastly, you are highly resourceful and independent yet comfortable working cross-functionally.
Yudha Utomo, ex-Senior Product Manager, Tokopedia
A great Product Manager is essentially an effective note-taker. In order to achieve the product goals, It is PM’s job to ensure objective has been clearly conveyed, efforts are assessed, and tasks are properly tracked and managed. PM can do this by having top-notch documentation skills.
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.
Frank Andrade
3 years ago
I discovered a bug that allowed me to use ChatGPT to successfully web scrape. Here's how it operates.
This method scrapes websites with ChatGPT (demo with Amazon and Twitter)
In a recent article, I demonstrated how to scrape websites using ChatGPT prompts like scrape website X using Python.
But that doesn’t always work.
After scraping dozens of websites with ChatGPT, I realized that simple prompts rarely work for web scraping.
Using ChatGPT and basic HTML, we can scrape any website.
First things first, use ChatGPT's advanced version (Playground)
ChatGPT Playground's enhanced version is needed to scrape websites quickly. It generates code faster and has less constraints.
Here’s how it looks.
The classic ChatGPT display just allows you to type a prompt. Playground is more customizable and generates code faster than the basic version.
No more delays or restrictions.
In this tutorial, we'll write prompts underneath Playground.
How to Use ChatGPT to Scrape Any Website
To show you how to utilize ChatGPT to scrape any website, we'll use subslikescript, which lists movies.
Later in this post, I'll show you how to scrape Amazon and Twitter, but let's start easy.
If we try a basic prompt like “scrape the movie titles on this website: https://subslikescript.com/movies” it won’t scrape anything. Here’s when we need some HTML knowledge to build the right prompt for ChatGPT.Let's scrape the above movie titles. First, check the webpage. Right-click any element and choose Inspect.
Then see below.
We identify the element to scrape (those in the red box). The data elements are ul, a, and scripts-list.
Here's the prompt for movie titles.
Scrape this website: https://subslikescript.com/movies with Python and Beautiful Soup. Locate the element with tag “ul” and class “scripts-list”. Scrape all the “a” elements inside. Get the text attribute and print it.
Code generated:
import requests
from bs4 import BeautifulSoup
page = requests.get('https://subslikescript.com/movies/')
soup = BeautifulSoup(page.content, 'html.parser')
scripts_list = soup.find(class_="scripts-list")
all_a_elements = scripts_list.find_all('a')
for element in all_a_elements:
print(element.get_text())It extracts movie titles successfully.
Let's scrape Amazon and Twitter.
ChatGPT's Amazon scraping
Consider scraping Amazon for self-help books. First, copy the Amazon link for self-help books.
Here’s the link I got. Location-dependent connection. Use my link to replicate my results.
Now we'll check book titles. Here's our element.
If we want to extract the book titles, we need to use the tag name span, class attribute name and a-size-base-plus a-color-base a-text-normalattribute value.
This time I'll use Selenium. I'll add Selenium-specific commands like wait 5 seconds and generate an XPath.
Scrape this website https://www.amazon.com/s?k=self+help+books&sprefix=self+help+%2Caps%2C158&ref=nb_sb_ss_ts-doa-p_2_10 with Python and Selenium.
Wait 5 seconds and locate all the elements with the following xpath: “span” tag, “class” attribute name, and “a-size-base-plus a-color-base a-text-normal” attribute value. Get the text attribute and print them.
Code generated: (I only had to manually add the path where my chromedriver is located).
from selenium import webdriver
from selenium.webdriver.common.by import By
from time import sleep
#initialize webdriver
driver = webdriver.Chrome('<add path of your chromedriver>')
#navigate to the website
driver.get("https://www.amazon.com/s?k=self+help+books&sprefix=self+help+%2Caps%2C158&ref=nb_sb_ss_ts-doa-p_2_10")
#wait 5 seconds to let the page load
sleep(5)
#locate all the elements with the following xpath
elements = driver.find_elements(By.XPATH, '//span[@class="a-size-base-plus a-color-base a-text-normal"]')
#get the text attribute of each element and print it
for element in elements:
print(element.text)
#close the webdriver
driver.close()It pulls Amazon book titles.
Utilizing ChatGPT to scrape Twitter
Say you wish to scrape ChatGPT tweets. Search Twitter for ChatGPT and copy the URL.
Here’s the link I got. We must check every tweet. Here's our element.
To extract a tweet, use the div tag and lang attribute.
Again, Selenium.
Scrape this website: https://twitter.com/search?q=chatgpt&src=typed_query using Python, Selenium and chromedriver.
Maximize the window, wait 15 seconds and locate all the elements that have the following XPath: “div” tag, attribute name “lang”. Print the text inside these elements.
Code generated: (again, I had to add the path where my chromedriver is located)
from selenium import webdriver
import time
driver = webdriver.Chrome("/Users/frankandrade/Downloads/chromedriver")
driver.maximize_window()
driver.get("https://twitter.com/search?q=chatgpt&src=typed_query")
time.sleep(15)
elements = driver.find_elements_by_xpath("//div[@lang]")
for element in elements:
print(element.text)
driver.quit()You'll get the first 2 or 3 tweets from a search. To scrape additional tweets, click X times.
Congratulations! You scraped websites without coding by using ChatGPT.