Unlimited everything for $19 monthly!?

Even with pretty words, no one wants to read an ugly email.

• Not Gen Z

• Not Millennials

• Not Gen X

• Not Boomers

I am a minimalist.

I like Mozart. I like avos. I love Apple.

When I hear seamlessly, effortlessly, or Apple's new adverb fluidly, my toes curl.

No email marketing tool gave me that feeling.

As a marketing consultant helping high-growth brands create marketing that doesn't feel like marketing, I've worked with every email marketing platform imaginable, including that naughty monkey and the expensive platform whose sales teams don't stop calling.

Most email marketing platforms are flawed.

1. They are overpriced.

2. They use dreadful templates.

3. They employ a poor visual designer.

4. The user experience there is awful.

5. Too many useless buttons are present. (Similar to the TV remote!)

I may have finally found the perfect email marketing tool. It creates strong flows. It helps me focus on storytelling.

It’s called Flodesk.

It’s effortless. It’s seamless. It’s fluid.

Here’s why it excites me.

Unlimited everything for $19 per month

Sends unlimited. Emails unlimited. Signups unlimited.

Most email platforms penalize success.

Pay for performance?

• $87 for 10k contacts

• $605 for 100K contacts

• $1,300+ for 200K contacts

In the 1990s, this made sense, but not now. It reminds me of when ISPs capped internet usage at 5 GB per month.

Flodesk made unlimited email for a low price a reality. Affordable, attractive email marketing isn't just for big companies.

Flodesk doesn't penalize you for growing your list. Price stays the same as lists grow.

Flodesk plans cost $38 per month, but I'll give you a 30-day trial for $19.

Amazingly strong flows

Foster different people's flows.

Email marketing isn't one-size-fits-all.

Different times require different emails.

People don't open emails because they're irrelevant, in my experience. A colder audience needs a nurturing sequence.

Flodesk automates your email funnels so top-funnel prospects fall in love with your brand and values before mid- and bottom-funnel email flows nudge them to take action.

I wish I could save more custom audience fields to further customize the experience.

Dynamic editor

Easy. Effortless.

Flodesk's editor is Apple-like.

You understand how it works almost instantly.

Like many Apple products, it's intentionally limited. No distractions. You can focus on emotional email writing.

Flodesk's inability to add inline HTML to emails is my biggest issue with larger projects. I wish I could upload HTML emails.

Simple sign-up procedures

Dream up joining.

I like how easy it is to create conversion-focused landing pages. Linkly lets you easily create 5 landing pages and A/B test messaging.

I like that you can use signup forms to ask people what they're interested in so they get relevant emails instead of mindless mass emails nobody opens.

I love how easy it is to embed in-line on a website.

Wonderful designer templates

Beautiful, connecting emails.

Flodesk has calm email templates. My designer's eye felt at rest when I received plain text emails with big impacts.

As a typography nerd, I love Flodesk's handpicked designer fonts. It gives emails a designer feel that is hard to replicate on other platforms without coding and custom font licenses.

Small adjustments can have a big impact

Details matter.

Flodesk remembers your brand colors. Flodesk automatically adds your logo and social handles to emails after signup.

Flodesk uses Zapier. This lets you send emails based on a user's action.

A bad live chat can trigger a series of emails to win back a customer.

Flodesk isn't for everyone.

Flodesk is great for Apple users like me.

Sundar Pichai unveiled Simplicity Sprint at Google's latest all-hands conference.

To boost employee efficiency.

Not surprising. Few envisioned Google declaring a productivity drive.

Sunder Pichai's speech:

“There are real concerns that our productivity as a whole is not where it needs to be for the head count we have. Help me create a culture that is more mission-focused, more focused on our products, more customer focused. We should think about how we can minimize distractions and really raise the bar on both product excellence and productivity.”

The primary driver driving Google's efficiency push is:

Google's efficiency push follows 13% quarterly revenue increase. Last year in the same quarter, it was 62%.

Market newcomers may argue that the previous year's figure was fuelled by post-Covid reopening and growing consumer spending. Investors aren't convinced. A promising company like Google can't afford to drop so quickly.

Google’s quarterly revenue growth stood at 13%, against 62% in last year same quarter.

Google isn't alone. In my recent essay regarding 2025 programmers, I warned about the economic downturn's effects on FAAMG's workforce. Facebook had suspended hiring, and Microsoft had promised hefty bonuses for loyal staff.

In the same article, I predicted Google's troubles. Online advertising, especially the way Google and Facebook sell it using user data, is over.

FAAMG and 2nd rung IT companies could be the first to fall without Post-COVID revival and uncertain global geopolitics.

Google has hardly ever discussed effectiveness:

Apparently openly.

Amazon treats its employees like robots, even in software positions. It has significant turnover and a terrible reputation as a result. Because of this, it rarely loses money due to staff productivity.

Amazon trumps Google. In reality, it treats its employees poorly.

Google was the founding father of the modern-day open culture.

Larry and Sergey Google founded the IT industry's Open Culture. Silicon Valley called Google's internal democracy and transparency near anarchy. Management rarely slammed decisions on employees. Surveys and internal polls ensured everyone knew the company's direction and had a vote.

20% project allotment (weekly free time to build own project) was Google's open-secret innovation component.

After Larry and Sergey's exit in 2019, this is Google's first profitability hurdle. Only Google insiders can answer these questions.

• Would Google's investors compel the company's management to adopt an Amazon-style culture where the developers are treated like circus performers?

• If so, would Google follow suit?

• If so, how does Google go about doing it?

Before discussing Google's likely plan, let's examine programming productivity.

What determines a programmer's productivity is simple:

How would we answer Google's questions?

As a programmer, I'm more concerned about Simplicity Sprint's aftermath than its economic catalysts.

Large organizations don't care much about quarterly and annual productivity metrics. They have 10-year product-launch plans. If something seems horrible today, it's likely due to someone's lousy judgment 5 years ago who is no longer in the blame game.

Deconstruct our main question.

• How exactly do you change the culture of the firm so that productivity increases?

• How can you accomplish that without affecting your capacity to profit? There are countless ways to increase output without decreasing profit.

• How can you accomplish this with little to no effect on employee motivation? (While not all employers care about it, in this case we are discussing the father of the open company culture.)

• How do you do it for a 10-developer IT firm that is losing money versus a 1,70,000-developer organization with a trillion-dollar valuation?

When implementing a large-scale organizational change, success must be carefully measured.

The fastest way to do something is to do it right, no matter how long it takes.

You require clearly-defined group/team/role segregation and solid pass/fail matrices to:

• You can give performers rewards.

• Ones that are average can be inspired to improve

• Underachievers may receive assistance or, in the worst-case scenario, rehabilitation

As a 20-year programmer, I associate productivity with greatness.

Doing something well, no matter how long it takes, is the fastest way to do it.

Let's discuss a programmer's productivity.

Why productivity is a strange term in programming:

Productivity is work per unit of time.

Money=time This is an economic proverb. More hours worked, more pay. Longer projects cost more.

As a buyer, you desire a quick supply. As a business owner, you want employees who perform at full capacity, creating more products to transport and boosting your profits.

All economic matrices encourage production because of our obsession with it. Productivity is the only organic way a nation may increase its GDP.

Time is money — is not just a proverb, but an economical fact.

Applying the same productivity theory to programming gets problematic. An automating computer. Its capacity depends on the software its master writes.

Today, a sophisticated program can process a billion records in a few hours. Creating one takes a competent coder and the necessary infrastructure. Learning, designing, coding, testing, and iterations take time.

Programming productivity isn't linear, unlike manufacturing and maintenance.

Average programmers produce code every day yet miss deadlines. Expert programmers go days without coding. End of sprint, they often surprise themselves by delivering fully working solutions.

Reversing the programming duties has no effect. Experts aren't needed for productivity.

These patterns remind me of an XKCD comic.

Programming productivity depends on two factors:

• The capacity of the programmer and his or her command of the principles of computer science

• His or her productive bursts, how often they occur, and how long they last as they engineer the answer

At some point, productivity measurement becomes Schrödinger’s cat.

Product companies measure productivity using use cases, classes, functions, or LOCs (lines of code). In days of data-rich source control systems, programmers' merge requests and/or commits are the most preferred yardstick. Companies assess productivity by tickets closed.

Every organization eventually has trouble measuring productivity. Finer measurements create more chaos. Every measure compares apples to oranges (or worse, apples with aircraft.) On top of the measuring overhead, the endeavor causes tremendous and unnecessary stress on teams, lowering their productivity and defeating its purpose.

Macro productivity measurements make sense. Amazon's factory-era management has done it, but at great cost.

Google can pull it off if it wants to.

What Google meant in reality when it said that employee productivity has decreased:

When Google considers its employees unproductive, it doesn't mean they don't complete enough work in the allotted period.

They can't multiply their work's influence over time.

• Programmers who produce excellent modules or products are unsure on how to use them.

• The best data scientists are unable to add the proper parameters in their models.

• Despite having a great product backlog, managers struggle to recruit resources with the necessary skills.

• Product designers who frequently develop and A/B test newer designs are unaware of why measures are inaccurate or whether they have already reached the saturation point.

• Most ignorant: All of the aforementioned positions are aware of what to do with their deliverables, but neither their supervisors nor Google itself have given them sufficient authority.

So, Google employees aren't productive.

How to fix it?

• Business analysis: White suits introducing novel items can interact with customers from all regions. Track analytics events proactively, especially the infrequent ones.

• SOLID, DRY, TEST, and AUTOMATION: Do less + reuse. Use boilerplate code creation. If something already exists, don't implement it yourself.

• Build features-building capabilities: N features are created by average programmers in N hours. An endless number of features can be built by average programmers thanks to the fact that expert programmers can produce 1 capability in N hours.

• Work on projects that will have a positive impact: Use the same algorithm to search for images on YouTube rather than the Mars surface.

• Avoid tasks that can only be measured in terms of time linearity at all costs (if a task can be completed in N minutes, then M copies of the same task would cost M*N minutes).

In conclusion:

Software development isn't linear. Why should the makers be measured?

Notation for The Big O

I'm discussing a new way to quantify programmer productivity. (It applies to other professions, but that's another subject)

The Big O notation expresses the paradigm (the algorithmic performance concept programmers rot to ace their Google interview)

Google (or any large corporation) can do this.

1. Sort organizational roles into categories and specify their impact vs. time objectives. A CXO role's time vs. effect function, for instance, has a complexity of O(log N), meaning that if a CEO raises his or her work time by 8x, the result only increases by 3x.

2. Plot the influence of each employee over time using the X and Y axes, respectively.

3. Add a multiplier for Y-axis values to the productivity equation to make business objectives matter. (Example values: Support = 5, Utility = 7, and Innovation = 10).

4. Compare employee scores in comparable categories (developers vs. devs, CXOs vs. CXOs, etc.) and reward or help employees based on whether they are ahead of or behind the pack.

After measuring every employee's inventiveness, it's straightforward to help underachievers and praise achievers.

Example of a Big(O) Category:

If I ran Google (God forbid, its worst days are far off), here's how I'd classify it. You can categorize Google employees whichever you choose.

The Google interview truth:

O(1) < O(log n) < O(n) < O(n log n) < O(n^x) where all logarithmic bases are < n.

O(1): Customer service workers' hours have no impact on firm profitability or customer pleasure.

CXOs Most of their time is spent on travel, strategic meetings, parties, and/or meetings with minimal floor-level influence. They're good at launching new products but bad at pivoting without disaster. Their directions are being followed.

Devops, UX designers, testers Agile projects revolve around deployment. DevOps controls the levers. Their automation secures results in subsequent cycles.

UX/UI Designers must still prototype UI elements despite improved design tools.

All test cases are proportional to use cases/functional units, hence testers' work is O(N).

Architects Their effort improves code quality. Their right/wrong interference affects product quality and rollout decisions even after the design is set.

Core Developers Only core developers can write code and own requirements. When people understand and own their labor, the output improves dramatically. A single character error can spread undetected throughout the SDLC and cost millions.

Core devs introduce/eliminate 1000x bugs, refactoring attempts, and regression. Following our earlier hypothesis.

The fastest way to do something is to do it right, no matter how long it takes.

Conclusion:

Google is at the liberal extreme of the employee-handling spectrum

Microsoft faced an existential crisis after 2000. It didn't choose Amazon's data-driven people management to revitalize itself.

Instead, it entrusted developers. It welcomed emerging technologies and opened up to open source, something it previously opposed.

Google is too lax in its employee-handling practices. With that foundation, it can only follow Amazon, no matter how carefully.

Any attempt to redefine people's measurements will affect the organization emotionally.

The more Google compares apples to apples, the higher its chances for future rebirth.

Ali's $1,054,053.74 YouTube Adsense haul.

YouTuber, entrepreneur, and former doctor Ali Abdaal. He began filming productivity and financial videos in 2017. Ali Abdaal has 3 million YouTube subscribers and has crossed $1 million in AdSense revenue. Crazy, no?

Ali will share the revenue of his top 5 youtube videos, things he's learned that you can apply to your side hustle, and how many views it takes to make a livelihood off youtube.

First, "The Long Game."

All good things take time to bear fruit. Compounding improves everything. Long-term work yields better returns. Ali made his first dollar after nine months and 85 videos.

Second, "One piece of content can transform your life, but you never know which one."

Had he abandoned YouTube at 84 videos without making any money, he wouldn't have filmed the 85th video that altered everything.

Third Lesson: Your Industry Choice Can Multiply.

The industry or niche you target as a business owner or side hustler can have a major impact on how much money you make.

Here are the top 5 videos.

1) 9.8m views: $191,258.16 for 9 passive income ideas

Ali made 2 points.

We should consider YouTube videos digital assets. They're investments, which make us money. His investments are yielding passive income.

Investing extra time and effort in your films can pay off.

2) How to Invest for Beginners — 5.2m Views: $87,200.08.

This video did poorly in the first several weeks after it was published; it was his tenth poorest performer. Don't worry about things you can't control. This applies to life, not just YouTube videos.

He stated we constantly have anxieties, fears, and concerns about things outside our control, but if we can find that line, life is easier and more pleasurable.

3) How to Build a Website in 2022— 866.3k views: $42,132.72.

The RPM was $48.86 per thousand views, making it his highest-earning video. Squarespace, Wix, and other website builders are trying to put ads on it and competing against one other, so ad rates go up.

Because it was beyond his niche, Ali almost didn't make the video. He made the video because he wanted to help at least one person.

4) How I take notes on my iPad in medical school — 5.9m views: $24,479.80

85th video. It's the video that affected Ali's YouTube channel and his life the most. The video's success wasn't certain.

5) How I Type Fast 156 Words Per Minute — 8.2M views: $25,143.17

Ali didn't know this video would perform well; he made it because he can type fast and has been practicing for 10 years. So he made a video with his best advice.

How many views to different wealth levels?

It depends on geography, niche, and other monetization sources. To keep things simple, he would solely utilize AdSense.

How many views to generate money?

To generate money on Youtube, you need 1,000 subscribers and 4,000 hours of view time. How much work do you need to make pocket money?

Ali's first 1,000 subscribers took 52 videos and 6 months. The typical channel with 1,000 subscribers contains 152 videos, according to Tubebuddy. It's time-consuming.

After monetizing, you'll need 15,000 views/month to make $5-$10/day.

How many views to go part-time?

Say you make $35,000/year at your day job. If you work 5 days/week, you make $7,000/year each day. If you want to drop down from 5 days to 4 days/week, you need to make an extra $7,000/year from YouTube, or $600/month.

What's the quit-your-job budget?

Silicon Valley Girl is in a highly successful niche targeting tech-focused folks in the west. When her channel had 500k views/month, she made roughly $3,000/month or $47,000/year, enough to quit your work.

Marina has another 1.5m subscriber channel in Russia, which has a lower rpm because fewer corporations advertise there than in the west. 2.3 million views/month is $4,000/month or $50,000/year, enough to quit your employment.

Marina is an intriguing example because she has three YouTube channels with the same skills, but one is 16x more profitable due to the niche she chose.

In Ali's case, he made 100+ videos when his channel was producing enough money to quit his job, roughly $4,000/month.

How many views make you rich?

Depending on how you define rich. Ali felt prosperous with over $100,000/year and 3–5m views/month.

Conclusion

YouTubers and artists don't treat their work like a company, which is a mistake. Businesses have been attempting to figure this out for decades, if not centuries.

We can learn from the business world how to monetize YouTube, Instagram, and Tiktok and make them into sustainable enterprises where we can hire people and delegate tasks.

Bonus

Watch Ali's video explaining all this:

This post is a summary. Read the full article here

Amazon's Rings of Power is the most costly TV series ever made. This is merely a down payment towards Amazon's grand goal.

Here's a video:

Amazon bought J.R.R. Tolkien's fantasy novels for $250 million in 2017. This agreement allows Amazon to create a Tolkien series for Prime Video.

The business spent years developing and constructing a Lord of the Rings prequel. Rings of Power premiered on September 2, 2022.

It drew 25 million global viewers in 24 hours. Prime Video's biggest debut.

An Exorbitant Budget

The most expensive. First season cost $750 million to $1 billion, making it the most costly TV show ever.

Jeff Bezos has spent years looking for the next Game of Thrones, a critically and commercially successful original series. Rings of Power could help.

Why would Amazon bet $1 billion on one series?

It's Not Just About the Streaming War

It's simple to assume Amazon just wants to win. Since 2018, the corporation has been fighting Hulu, Netflix, HBO, Apple, Disney, and NBC. Each wants your money, talent, and attention. Amazon's investment goes beyond rivalry.

Subscriptions Are the Bait

Audible, Amazon Music, and Prime Video are subscription services, although the company's fundamental business is retail. Amazon's online stores contribute over 50% of company revenue. Subscription services contribute 6.8%. The company's master plan depends on these subscriptions.

Streaming videos on Prime increases membership renewals. Free trial participants are more likely to join. Members buy twice as much as non-members.

Amazon Studios doesn't generate original programming to earn from Prime Video subscriptions. It aims to retain and attract clients.

Amazon can track what you watch and buy. Its algorithm recommends items and services. Mckinsey says you'll use more Amazon products, shop at Amazon stores, and watch Amazon entertainment.

In 2015, the firm launched the first season of The Man in the High Castle, a dystopian alternate history TV series depicting a world ruled by Nazi Germany and Japan after World War II.

This $72 million production earned two Emmys. It garnered 1.15 million new Prime users globally.

When asked about his Hollywood investment, Bezos said, "A Golden Globe helps us sell more shoes."

Selling more footwear

Amazon secured a deal with DirecTV to air Thursday Night Football in restaurants and bars. First streaming service to have exclusive NFL games.

This isn't just about Thursday night football, says media analyst Ritchie Greenfield. This sells t-shirts. This may be a ticket. Amazon does more than stream games.

The Rings of Power isn't merely a production showcase, either. This sells Tolkien's fantasy novels such Lord of the Rings, The Hobbit, and The Silmarillion.

This tiny commitment keeps you in Amazon's ecosystem.

Are MVPs outdated and have no place in modern product culture?

Frank Robinson coined "MVP" in 2001. In the same year as the Agile Manifesto, the first Scrum experiment began. MVPs are old.

The concept was created to solve the waterfall problem at the time.

The market was still sour from the .com bubble. The tech industry needed a new approach. Product and Agile gained popularity because they weren't waterfall.

More than 20 years later, waterfall is dead as dead can be, but we are still talking about MVPs. Does that make sense?

What is an MVP?

Minimum viable product. You probably know that, so I'll be brief:

[…] The MVP fits your company and customer. It's big enough to cause adoption, satisfaction, and sales, but not bloated and risky. It's the product with the highest ROI/risk. […] — Frank Robinson, SyncDev

MVP is a complete product. It's not a prototype. It's your product's first iteration, which you'll improve. It must drive sales and be user-friendly.

At the MVP stage, you should know your product's core value, audience, and price. We are way deep into early adoption territory.

What about all the things that come before?

Modern product discovery

Eric Ries popularized the term with The Lean Startup in 2011. (Ries would work with the concept since 2008, but wide adoption came after the book was released).

Ries' definition of MVP was similar to Robinson's: "Test the market" before releasing anything. Ries never mentioned money, unlike Jobs. His MVP's goal was learning.

“Remove any feature, process, or effort that doesn't directly contribute to learning” — Eric Ries, The Lean Startup

Product has since become more about "what" to build than building it. What started as a learning tool is now a discovery discipline: fake doors, prototyping, lean inception, value proposition canvas, continuous interview, opportunity tree... These are cheap, effective learning tools.

Over time, companies realized that "maximum ROI divided by risk" started with discovery, not the MVP. MVPs are still considered discovery tools. What is the problem with that?

Time to Market vs Product Market Fit

Waterfall's Time to Market is its biggest flaw. Since projects are sliced horizontally rather than vertically, when there is nothing else to be done, it’s not because the product is ready, it’s because no one cares to buy it anymore.

MVPs were originally conceived as a way to cut corners and speed Time to Market by delivering more customer requests after they paid.

Original product development was waterfall-like.

Time to Market defines an optimal, specific window in which value should be delivered. It's impossible to predict how long or how often this window will be open.

Product Market Fit makes this window a "state." You don’t achieve Product Market Fit, you have it… and you may lose it.

Take, for example, Snapchat. They had a great time to market, but lost product-market fit later. They regained product-market fit in 2018 and have grown since.

An MVP couldn't handle this. What should Snapchat do? Launch Snapchat 2 and see what the market was expecting differently from the last time? MVPs are a snapshot in time that may be wrong in two weeks.

MVPs are mini-projects. Instead of spending a lot of time and money on waterfall, you spend less but are still unsure of the results.

MVPs aren't always wrong. When releasing your first product version, consider an MVP.

Minimum viable product became less of a thing on its own and more interchangeable with Alpha Release or V.1 release over time.

Modern discovery technics are more assertive and predictable than the MVP, but clarity comes only when you reach the market.

MVPs aren't the starting point, but they're the best way to validate your product concept.