More on Leadership
Trevor Stark
3 years ago
Peter Thiels's Multi-Billion Dollar Net Worth's Unknown Philosopher
Peter Thiel studied philosophy as an undergraduate.
Peter Thiel has $7.36 billion.
Peter is a world-ranked chess player, has a legal degree, and has written profitable novels.
In 1999, he co-founded PayPal with Max Levchin, which merged with X.com.
Peter Thiel made $55 million after selling the company to eBay for $1.5 billion in 2002.
You may be wondering…
How did Peter turn $55 million into his now multi-billion dollar net worth?
One amazing investment?
Facebook.
Thiel was Facebook's first external investor. He bought 10% of the company for $500,000 in 2004.
This investment returned 159% annually, 200x in 8 years.
By 2012, Thiel sold almost all his Facebook shares, becoming a billionaire.
What was the investment thesis of Peter?
This investment appeared ridiculous. Facebook was an innovative startup.
Thiel's $500,000 contribution transformed Facebook.
Harvard students have access to Facebook's 8 features and 1 photo per profile.
How did Peter determine that this would be a wise investment, then?
Facebook is a mimetic desire machine.
Social media's popularity is odd. Why peek at strangers' images on a computer?
Peter Thiel studied under French thinker Rene Girard at Stanford.
Mimetic Desire explains social media's success.
Mimetic Desire is the idea that humans desire things simply because other people do.
If nobody wanted it, would you?
Would you desire a family, a luxury car, or expensive clothes if no one else did? Girard says no.
People we admire affect our aspirations because we're social animals. Every person has a role model.
Our nonreligious culture implies role models are increasingly other humans, not God.
The idea explains why social media influencers are so powerful.
Why would Andrew Tate or Kim Kardashian matter if people weren't mimetic?
Humanity is fundamentally motivated by social comparison.
Facebook takes advantage of this need for social comparison, and puts it on a global scale.
It aggregates photographs and updates from millions of individuals.
Facebook mobile allows 24/7 social comparison.
Thiel studied mimetic desire with Girard and realized Facebook exploits the urge for social comparison to gain money.
Social media is more significant and influential than ever, despite Facebook's decline.
Thiel and Girard show that applied philosophy (particularly in business) can be immensely profitable.
Solomon Ayanlakin
3 years ago
Metrics for product management and being a good leader
Never design a product without explicit metrics and tracking tools.
Imagine driving cross-country without a dashboard. How do you know your school zone speed? Low gas? Without a dashboard, you can't monitor your car. You can't improve what you don't measure, as Peter Drucker said. Product managers must constantly enhance their understanding of their users, how they use their product, and how to improve it for optimum value. Customers will only pay if they consistently acquire value from your product.
I’m Solomon Ayanlakin. I’m a product manager at CredPal, a financial business that offers credit cards and Buy Now Pay Later services. Before falling into product management (like most PMs lol), I self-trained as a data analyst, using Alex the Analyst's YouTube playlists and DannyMas' virtual data internship. This article aims to help product managers, owners, and CXOs understand product metrics, give a methodology for creating them, and execute product experiments to enhance them.
☝🏽Introduction
Product metrics assist companies track product performance from the user's perspective. Metrics help firms decide what to construct (feature priority), how to build it, and the outcome's success or failure. To give the best value to new and existing users, track product metrics.
Why should a product manager monitor metrics?
to assist your users in having a "aha" moment
To inform you of which features are frequently used by users and which are not
To assess the effectiveness of a product feature
To aid in enhancing client onboarding and retention
To assist you in identifying areas throughout the user journey where customers are satisfied or dissatisfied
to determine the percentage of returning users and determine the reasons for their return
📈 What Metrics Ought a Product Manager to Monitor?
What indicators should a product manager watch to monitor product health? The metrics to follow change based on the industry, business stage (early, growth, late), consumer needs, and company goals. A startup should focus more on conversion, activation, and active user engagement than revenue growth and retention. The company hasn't found product-market fit or discovered what features drive customer value.
Depending on your use case, company goals, or business stage, here are some important product metric buckets:
All measurements shouldn't be used simultaneously. It depends on your business goals and what value means for your users, then selecting what metrics to track to see if they get it.
Some KPIs are more beneficial to track, independent of industry or customer type. To prevent recording vanity metrics, product managers must clearly specify the types of metrics they should track. Here's how to segment metrics:
The North Star Metric, also known as the Focus Metric, is the indicator and aid in keeping track of the top value you provide to users.
Primary/Level 1 Metrics: These metrics should either add to the north star metric or be used to determine whether it is moving in the appropriate direction. They are metrics that support the north star metric.
These measures serve as leading indications for your north star and Level 2 metrics. You ought to have been aware of certain problems with your L2 measurements prior to the North star metric modifications.
North Star Metric
This is the key metric. A good north star metric measures customer value. It emphasizes your product's longevity. Many organizations fail to grow because they confuse north star measures with other indicators. A good focus metric should touch all company teams and be tracked forever. If a company gives its customers outstanding value, growth and success are inevitable. How do we measure this value?
A north star metric has these benefits:
Customer Obsession: It promotes a culture of customer value throughout the entire organization.
Consensus: Everyone can quickly understand where the business is at and can promptly make improvements, according to consensus.
Growth: It provides a tool to measure the company's long-term success. Do you think your company will last for a long time?
How can I pick a reliable North Star Metric?
Some fear a single metric. Ensure product leaders can objectively determine a north star metric. Your company's focus metric should meet certain conditions. Here are a few:
A good focus metric should reflect value and, as such, should be closely related to the point at which customers obtain the desired value from your product. For instance, the quick delivery to your home is a value proposition of UberEats. The value received from a delivery would be a suitable focal metric to use. While counting orders is alluring, the quantity of successfully completed positive review orders would make a superior north star statistic. This is due to the fact that a client who placed an order but received a defective or erratic delivery is not benefiting from Uber Eats. By tracking core value gain, which is the number of purchases that resulted in satisfied customers, we are able to track not only the total number of orders placed during a specific time period but also the core value proposition.
Focus metrics need to be quantifiable; they shouldn't only be feelings or states; they need to be actionable. A smart place to start is by counting how many times an activity has been completed.
A great focus metric is one that can be measured within predetermined time limits; otherwise, you are not measuring at all. The company can improve that measure more quickly by having time-bound focus metrics. Measuring and accounting for progress over set time periods is the only method to determine whether or not you are moving in the right path. You can then evaluate your metrics for today and yesterday. It's generally not a good idea to use a year as a time frame. Ideally, depending on the nature of your organization and the measure you are focusing on, you want to take into account on a daily, weekly, or monthly basis.
Everyone in the firm has the potential to affect it: A short glance at the well-known AAARRR funnel, also known as the Pirate Metrics, reveals that various teams inside the organization have an impact on the funnel. Ideally, the NSM should be impacted if changes are made to one portion of the funnel. Consider how the growth team in your firm is enhancing customer retention. This would have a good effect on the north star indicator because at this stage, a repeat client is probably being satisfied on a regular basis. Additionally, if the opposite were true and a client churned, it would have a negative effect on the focus metric.
It ought to be connected to the business's long-term success: The direction of sustainability would be indicated by a good north star metric. A company's lifeblood is product demand and revenue, so it's critical that your NSM points in the direction of sustainability. If UberEats can effectively increase the monthly total of happy client orders, it will remain in operation indefinitely.
Many product teams make the mistake of focusing on revenue. When the bottom line is emphasized, a company's goal moves from giving value to extracting money from customers. A happy consumer will stay and pay for your service. Customer lifetime value always exceeds initial daily, monthly, or weekly revenue.
Great North Star Metrics Examples
🥇 Basic/L1 Metrics:
The NSM is broad and focuses on providing value for users, while the primary metric is product/feature focused and utilized to drive the focus metric or signal its health. The primary statistic is team-specific, whereas the north star metric is company-wide. For UberEats' NSM, the marketing team may measure the amount of quality food vendors who sign up using email marketing. With quality vendors, more orders will be satisfied. Shorter feedback loops and unambiguous team assignments make L1 metrics more actionable and significant in the immediate term.
🥈 Supporting L2 metrics:
These are supporting metrics to the L1 and focus metrics. Location, demographics, or features are examples of L1 metrics. UberEats' supporting metrics might be the number of sales emails sent to food vendors, the number of opens, and the click-through rate. Secondary metrics are low-level and evident, and they relate into primary and north star measurements. UberEats needs a high email open rate to attract high-quality food vendors. L2 is a leading sign for L1.
Where can I find product metrics?
How can I measure in-app usage and activity now that I know what metrics to track? Enter product analytics. Product analytics tools evaluate and improve product management parameters that indicate a product's health from a user's perspective.
Various analytics tools on the market supply product insight. From page views and user flows through A/B testing, in-app walkthroughs, and surveys. Depending on your use case and necessity, you may combine tools to see how users engage with your product. Gainsight, MixPanel, Amplitude, Google Analytics, FullStory, Heap, and Pendo are product tools.
This article isn't sponsored and doesn't market product analytics tools. When choosing an analytics tool, consider the following:
Tools for tracking your Focus, L1, and L2 measurements
Pricing
Adaptations to include external data sources and other products
Usability and the interface
Scalability
Security
An investment in the appropriate tool pays off. To choose the correct metrics to track, you must first understand your business need and what value means to your users. Metrics and analytics are crucial for any tech product's growth. It shows how your business is doing and how to best serve users.
Nir Zicherman
3 years ago
The Great Organizational Conundrum
Only two of the following three options can be achieved: consistency, availability, and partition tolerance
Someone told me that growing from 30 to 60 is the biggest adjustment for a team or business.
I remember thinking, That's random. Each company is unique. I've seen teams of all types confront the same issues during development periods. With new enterprises starting every year, we should be better at navigating growing difficulties.
As a team grows, its processes and systems break down, requiring reorganization or declining results. Why always? Why isn't there a perfect scaling model? Why hasn't that been found?
The Three Things Productive Organizations Must Have
Any company should be efficient and productive. Three items are needed:
First, it must verify that no two team members have conflicting information about the roadmap, strategy, or any input that could affect execution. Teamwork is required.
Second, it must ensure that everyone can receive the information they need from everyone else quickly, especially as teams become more specialized (an inevitability in a developing organization). It requires everyone's accessibility.
Third, it must ensure that the organization can operate efficiently even if a piece is unavailable. It's partition-tolerant.
From my experience with the many teams I've been on, invested in, or advised, achieving all three is nearly impossible. Why a perfect organization model cannot exist is clear after analysis.
The CAP Theorem: What is it?
Eric Brewer of Berkeley discovered the CAP Theorem, which argues that a distributed data storage should have three benefits. One can only have two at once.
The three benefits are consistency, availability, and partition tolerance, which implies that even if part of the system is offline, the remainder continues to work.
This notion is usually applied to computer science, but I've realized it's also true for human organizations. In a post-COVID world, many organizations are hiring non-co-located staff as they grow. CAP Theorem is more important than ever. Growing teams sometimes think they can develop ways to bypass this law, dooming themselves to a less-than-optimal team dynamic. They should adopt CAP to maximize productivity.
Path 1: Consistency and availability equal no tolerance for partitions
Let's imagine you want your team to always be in sync (i.e., for someone to be the source of truth for the latest information) and to be able to share information with each other. Only division into domains will do.
Numerous developing organizations do this, especially after the early stage (say, 30 people) when everyone may wear many hats and be aware of all the moving elements. After a certain point, it's tougher to keep generalists aligned than to divide them into specialized tasks.
In a specialized, segmented team, leaders optimize consistency and availability (i.e. every function is up-to-speed on the latest strategy, no one is out of sync, and everyone is able to unblock and inform everyone else).
Partition tolerance suffers. If any component of the organization breaks down (someone goes on vacation, quits, underperforms, or Gmail or Slack goes down), productivity stops. There's no way to give the team stability, availability, and smooth operation during a hiccup.
Path 2: Partition Tolerance and Availability = No Consistency
Some businesses avoid relying too heavily on any one person or sub-team by maximizing availability and partition tolerance (the organization continues to function as a whole even if particular components fail). Only redundancy can do that. Instead of specializing each member, the team spreads expertise so people can work in parallel. I switched from Path 1 to Path 2 because I realized too much reliance on one person is risky.
What happens after redundancy? Unreliable. The more people may run independently and in parallel, the less anyone can be the truth. Lack of alignment or updated information can lead to people executing slightly different strategies. So, resources are squandered on the wrong work.
Path 3: Partition and Consistency "Tolerance" equates to "absence"
The third, least-used path stresses partition tolerance and consistency (meaning answers are always correct and up-to-date). In this organizational style, it's most critical to maintain the system operating and keep everyone aligned. No one is allowed to read anything without an assurance that it's up-to-date (i.e. there’s no availability).
Always short-lived. In my experience, a business that prioritizes quality and scalability over speedy information transmission can get bogged down in heavy processes that hinder production. Large-scale, this is unsustainable.
Accepting CAP
When two puzzle pieces fit, the third won't. I've watched developing teams try to tackle these difficulties, only to find, as their ancestors did, that they can never be entirely solved. Idealized solutions fail in reality, causing lost effort, confusion, and lower production.
As teams develop and change, they should embrace CAP, acknowledge there is a limit to productivity in a scaling business, and choose the best two-out-of-three path.
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Monroe Mayfield
2 years ago
CES 2023: A Third Look At Upcoming Trends
Las Vegas hosted CES 2023. This third and last look at CES 2023 previews upcoming consumer electronics trends that will be crucial for market share.
Definitely start with ICT. Qualcomm CEO Cristiano Amon spoke to CNBC from Las Vegas on China's crackdown and the company's automated driving systems for electric vehicles (EV). The business showed a concept car and its latest Snapdragon processor designs, which offer expanded digital interactions through SalesForce-partnered CRM platforms.
Electrification is reviving Michigan's automobile industry. Michigan Local News reports that $14 billion in EV and battery manufacturing investments will benefit the state. The report also revealed that the Strategic Outreach and Attraction Reserve (SOAR) fund had generated roughly $1 billion for the state's automotive sector.
Ars Technica is great for technology, society, and the future. After CES 2023, Jonathan M. Gitlin published How many electric car chargers are enough? Read about EV charging network issues and infrastructure spending. Politics aside, rapid technological advances enable EV charging network expansion in American cities and abroad.
Finally, the UNEP's The Future of Electric Vehicles and Material Resources: A Foresight Brief. Understanding how lithium-ion batteries will affect EV sales is crucial. Climate change affects EVs in various ways, but electrification and mining trends stand out because more EVs demand more energy-intensive metals and rare earths. Areas & Producers has been publishing my electrification and mining trends articles. Follow me if you wish to write for the publication.
The Weekend Brief (TWB) will routinely cover tech, industrials, and global commodities in global markets, including stock markets. Read more about the future of key areas and critical producers of the global economy in Areas & Producers.
Ashraful Islam
4 years ago
Clean API Call With React Hooks
| Photo by Juanjo Jaramillo on Unsplash |
Calling APIs is the most common thing to do in any modern web application. When it comes to talking with an API then most of the time we need to do a lot of repetitive things like getting data from an API call, handling the success or error case, and so on.
When calling tens of hundreds of API calls we always have to do those tedious tasks. We can handle those things efficiently by putting a higher level of abstraction over those barebone API calls, whereas in some small applications, sometimes we don’t even care.
The problem comes when we start adding new features on top of the existing features without handling the API calls in an efficient and reusable manner. In that case for all of those API calls related repetitions, we end up with a lot of repetitive code across the whole application.
In React, we have different approaches for calling an API. Nowadays mostly we use React hooks. With React hooks, it’s possible to handle API calls in a very clean and consistent way throughout the application in spite of whatever the application size is. So let’s see how we can make a clean and reusable API calling layer using React hooks for a simple web application.
I’m using a code sandbox for this blog which you can get here.
import "./styles.css";
import React, { useEffect, useState } from "react";
import axios from "axios";
export default function App() {
const [posts, setPosts] = useState(null);
const [error, setError] = useState("");
const [loading, setLoading] = useState(false);
useEffect(() => {
handlePosts();
}, []);
const handlePosts = async () => {
setLoading(true);
try {
const result = await axios.get(
"https://jsonplaceholder.typicode.com/posts"
);
setPosts(result.data);
} catch (err) {
setError(err.message || "Unexpected Error!");
} finally {
setLoading(false);
}
};
return (
<div className="App">
<div>
<h1>Posts</h1>
{loading && <p>Posts are loading!</p>}
{error && <p>{error}</p>}
<ul>
{posts?.map((post) => (
<li key={post.id}>{post.title}</li>
))}
</ul>
</div>
</div>
);
}
I know the example above isn’t the best code but at least it’s working and it’s valid code. I will try to improve that later. For now, we can just focus on the bare minimum things for calling an API.
Here, you can try to get posts data from JsonPlaceholer. Those are the most common steps we follow for calling an API like requesting data, handling loading, success, and error cases.
If we try to call another API from the same component then how that would gonna look? Let’s see.
500: Internal Server Error
Now it’s going insane! For calling two simple APIs we’ve done a lot of duplication. On a top-level view, the component is doing nothing but just making two GET requests and handling the success and error cases. For each request, it’s maintaining three states which will periodically increase later if we’ve more calls.
Let’s refactor to make the code more reusable with fewer repetitions.
Step 1: Create a Hook for the Redundant API Request Codes
Most of the repetitions we have done so far are about requesting data, handing the async things, handling errors, success, and loading states. How about encapsulating those things inside a hook?
The only unique things we are doing inside handleComments and handlePosts are calling different endpoints. The rest of the things are pretty much the same. So we can create a hook that will handle the redundant works for us and from outside we’ll let it know which API to call.
500: Internal Server Error
Here, this request function is identical to what we were doing on the handlePosts and handleComments. The only difference is, it’s calling an async function apiFunc which we will provide as a parameter with this hook. This apiFunc is the only independent thing among any of the API calls we need.
With hooks in action, let’s change our old codes in App component, like this:
500: Internal Server Error
How about the current code? Isn’t it beautiful without any repetitions and duplicate API call handling things?
Let’s continue our journey from the current code. We can make App component more elegant. Now it knows a lot of details about the underlying library for the API call. It shouldn’t know that. So, here’s the next step…
Step 2: One Component Should Take Just One Responsibility
Our App component knows too much about the API calling mechanism. Its responsibility should just request the data. How the data will be requested under the hood, it shouldn’t care about that.
We will extract the API client-related codes from the App component. Also, we will group all the API request-related codes based on the API resource. Now, this is our API client:
import axios from "axios";
const apiClient = axios.create({
// Later read this URL from an environment variable
baseURL: "https://jsonplaceholder.typicode.com"
});
export default apiClient;
All API calls for comments resource will be in the following file:
import client from "./client";
const getComments = () => client.get("/comments");
export default {
getComments
};
All API calls for posts resource are placed in the following file:
import client from "./client";
const getPosts = () => client.get("/posts");
export default {
getPosts
};
Finally, the App component looks like the following:
import "./styles.css";
import React, { useEffect } from "react";
import commentsApi from "./api/comments";
import postsApi from "./api/posts";
import useApi from "./hooks/useApi";
export default function App() {
const getPostsApi = useApi(postsApi.getPosts);
const getCommentsApi = useApi(commentsApi.getComments);
useEffect(() => {
getPostsApi.request();
getCommentsApi.request();
}, []);
return (
<div className="App">
{/* Post List */}
<div>
<h1>Posts</h1>
{getPostsApi.loading && <p>Posts are loading!</p>}
{getPostsApi.error && <p>{getPostsApi.error}</p>}
<ul>
{getPostsApi.data?.map((post) => (
<li key={post.id}>{post.title}</li>
))}
</ul>
</div>
{/* Comment List */}
<div>
<h1>Comments</h1>
{getCommentsApi.loading && <p>Comments are loading!</p>}
{getCommentsApi.error && <p>{getCommentsApi.error}</p>}
<ul>
{getCommentsApi.data?.map((comment) => (
<li key={comment.id}>{comment.name}</li>
))}
</ul>
</div>
</div>
);
}
Now it doesn’t know anything about how the APIs get called. Tomorrow if we want to change the API calling library from axios to fetch or anything else, our App component code will not get affected. We can just change the codes form client.js This is the beauty of abstraction.
Apart from the abstraction of API calls, Appcomponent isn’t right the place to show the list of the posts and comments. It’s a high-level component. It shouldn’t handle such low-level data interpolation things.
So we should move this data display-related things to another low-level component. Here I placed those directly in the App component just for the demonstration purpose and not to distract with component composition-related things.
Final Thoughts
The React library gives the flexibility for using any kind of third-party library based on the application’s needs. As it doesn’t have any predefined architecture so different teams/developers adopted different approaches to developing applications with React. There’s nothing good or bad. We choose the development practice based on our needs/choices. One thing that is there beyond any choices is writing clean and maintainable codes.
CyberPunkMetalHead
3 years ago
195 countries want Terra Luna founder Do Kwon
Interpol has issued a red alert on Terraform Labs' CEO, South Korean prosecutors said.
After the May crash of Terra Luna revealed tax evasion issues, South Korean officials filed an arrest warrant for Do Kwon, but he is missing.
Do Kwon is now a fugitive in 195 countries after Seoul prosecutors placed him to Interpol's red list. Do Kwon hasn't commented since then. The red list allows any country's local authorities to apprehend Do Kwon.
Do Dwon and Terraform Labs were believed to have moved to Singapore days before the $40 billion wipeout, but Singapore authorities said he fled the country on September 17. Do Kwon tweeted that he wasn't on the run and cited privacy concerns.
Do Kwon was not on the red list at the time and said he wasn't "running," only to reply to his own tweet saying he hasn't jogged in a while and needed to trim calories.
Whether or not it makes sense to read too much into this, the reality is that Do Kwon is now on Interpol red list, despite the firmly asserts on twitter that he does absolutely nothing to hide.
UPDATE:
South Korean authorities are investigating alleged withdrawals of over $60 million U.S. and seeking to freeze these assets. Korean authorities believe a new wallet exchanged over 3000 BTC through OKX and Kucoin.
Do Kwon and the Luna Foundation Guard (of whom Do Kwon is a key member of) have declined all charges and dubbed this disinformation.
Singapore's Luna Foundation Guard (LFG) manages the Terra Ecosystem.
The Legal Situation
Multiple governments are searching for Do Kwon and five other Terraform Labs employees for financial markets legislation crimes.
South Korean authorities arrested a man suspected of tax fraud and Ponzi scheme.
The U.S. SEC is also examining Terraform Labs on how UST was advertised as a stablecoin. No legal precedent exists, so it's unclear what's illegal.
The future of Terraform Labs, Terra, and Terra 2 is unknown, and despite what Twitter shills say about LUNC, the company remains in limbo awaiting a decision that will determine its fate. This project isn't a wise investment.