Niharikaa Kaur Sodhi
5 days ago
The Only Paid Resources I Turn to as a Solopreneur
4 Pricey Tools That Are Valuable
I pay based on ROI (return on investment).
If a $20/month tool or $500 online course doubles my return, I'm in.
Investing helps me build wealth.
I initially refused to pay.
My course content needed updating a few months ago. My Google Docs text looked cleaner and more professional in Canva.
I've used it to:
product cover pages
Product page infographics
See my Google Sheets vs. Canva product page graph.
Google Sheets vs Canva
Yesterday, I used it to make a LinkedIn video thumbnail. It took less than 5 minutes and improved my video.
In 30 hours, the video had 39,000 views.
It builds my brand as I sleep. What else?
Because I'm traveling this weekend, I planned tweets for 10 days. It took me 80 minutes.
So while I travel or am absent, my content mill keeps producing.
Also I like:
I can reach hundreds of people thanks to auto-DMs. I utilize it to advertise freebies; for instance, leave an emoji remark to receive my checklist. And they automatically receive a message in their DM.
Scheduled Retweets: By appearing in a different time zone, they give my tweet a second chance.
It helps me save time and expand my following, so that's my favorite part.
It’s also super neat:
My course involves weekly and monthly calls for alumni.
Google Meet isn't great for group calls. The interface isn't great.
Zoom Pro is expensive, and the monthly payments suck, but it's necessary.
It gives my students a smooth experience.
Previously, we'd do 40-minute meetings and then reconvene.
Zoom's free edition limits group calls to 40 minutes.
This wouldn't be a good online course if I paid hundreds of dollars.
So I felt obligated to help.
My laptop has an ad blocker.
I bought an iPad recently.
When you're self-employed and work from home, the line between the two blurs. My bed is only 5 steps away!
When I read or watched videos on my laptop, I'd slide into work mode. Only option was to view on phone, which is awkward.
YouTube premium handles it. No more advertisements and I can listen on the move.
3 Expensive Tools That Aren't Valuable
Marketing strategies are sometimes aimed to make you feel you need 38474 cool features when you don’t.
Certain tools are useless.
I found it useless.
Depending on your needs. As a writer and creator, I get no return.
They could for other jobs.
It tracks LinkedIn stats, like:
trend chart for impressions
Engagement, views, and comment stats for posts
and much more.
Middle-tier creator costs $12/month.
I got a 25% off coupon but canceled my free trial before writing this. It's not worth the discount.
LinkedIn provides free analytics. See:
Not thorough and won't show top posts.
I don't need to see my top posts because I love experimenting with writing.
Slack was my classroom. Slack provided me a premium trial during the prior cohort.
I skipped it.
Sure, voice notes are better than a big paragraph. I didn't require pro features.
Marketing methods sometimes make you think you need 38474 amazing features. Don’t fall for it.
This may be worth it if you get many calls.
I avoid calls. During my 9-5, I had too many pointless calls.
I don't need:
ability to schedule calls for 15, 30, or 60 minutes: I just distribute each link separately.
I have a Gumroad consultation page with a payment option.
follow-up emails: I hardly ever make calls, so
I just use one calendar, therefore I link to various calendars.
I'll admit, the integrations are cool. Not for me.
If you're a coach or consultant, the features may be helpful. Or book meetings.
Investing is spending to make money.
Use my technique — put money in tools that help you make money. This separates it from being an investment instead of an expense.
Try free versions of these tools before buying them since everyone else is.
7 days ago
Why Google Staff Doesn't Work
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:
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).
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.
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.
Plot the influence of each employee over time using the X and Y axes, respectively.
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).
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.
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.
8 days ago
How Elon Musk Picks Things Up Quicker Than Anyone Else
Adopt Elon Musk's learning strategy to succeed.
Medium writers rank first and second when you Google “Elon Musk's learning approach”.
My article idea seems unoriginal. Lol
Musk is brilliant.
No doubt here.
His name connotes success and intelligence.
He knows rocket science, engineering, AI, and solar power.
Musk is a Unicorn, but his skills aren't special.
How does he manage it?
Elon Musk has two learning rules that anyone may use.
You can apply these rules and become anyone you want.
You can become a rocket scientist or a surgeon. If you want, of course.
The learning process is key.
Make sure you are creating a Tree of Knowledge according to Rule #1.
Musk told Reddit how he learns:
“It is important to view knowledge as sort of a semantic tree — make sure you understand the fundamental principles, i.e. the trunk and big branches, before you get into the leaves/details or there is nothing for them to hang onto.”
Musk understands the essential ideas and mental models of each of his business sectors.
He starts with the tree's trunk, making sure he learns the basics before going on to branches and leaves.
We often act otherwise. We memorize small details without understanding how they relate to the whole. Our minds are stuffed with useless data.
Cramming isn't learning.
Start with the basics to learn faster. Before diving into minutiae, grasp the big picture.
Rule #2: You can't connect what you can't remember.
Elon Musk transformed industries this way. As his expertise grew, he connected branches and leaves from different trees.
Musk read two books a day as a child. He didn't specialize like most people. He gained from his multidisciplinary education. It helped him stand out and develop billion-dollar firms.
He gained skills in several domains and began connecting them. World-class performances resulted.
Most of us never learn the basics and only collect knowledge. We never really comprehend information, thus it's hard to apply it.
Learn the basics initially to maximize your chances of success. Then start learning.
Learn across fields and connect them.
This method enabled Elon Musk to enter and revolutionize a century-old industry.
15 days ago
Effective Technical Book Reading Techniques
Technical books aren't like novels. We need a new approach to technical texts. I've spent years looking for a decent reading method. I tried numerous ways before finding one that worked. This post explains how I read technical books efficiently.
What Do I Mean When I Say Effective?
Effectiveness depends on the book. Effective implies I know where to find answers after reading a reference book. Effective implies I learned the book's knowledge after reading it.
I use reference books as tools in my toolkit. I won't carry all my tools; I'll merely need them. Non-reference books teach me techniques. I never have to make an effort to use them since I always have them.
Reference books I like:
Refactoring: Improving the Design of Existing Code
You can also check My Top Takeaways from Refactoring here.
Non-reference books I like:
Technical books might be overwhelming to read in one sitting. Especially when you have no idea what is coming next as you read. When you don't know how deep the rabbit hole goes, you feel lost as you read. This is my years-long method for overcoming this difficulty.
Whether you follow the step-by-step guide or not, remember these:
Understand the terminology. Make sure you get the meaning of any terms you come across more than once. The likelihood that a term will be significant increases as you encounter it more frequently.
Know when to stop. I've always believed that in order to truly comprehend something, I must delve as deeply as possible into it. That, however, is not usually very effective. There are moments when you have to draw the line and start putting theory into practice (if applicable).
Look over your notes. When reading technical books or documents, taking notes is a crucial habit to develop. Additionally, you must regularly examine your notes if you want to get the most out of them. This will assist you in internalizing the lessons you acquired from the book. And you'll see that the urge to review reduces with time.
Let's talk about how I read a technical book step by step.
0. Read the Foreword/Preface
These sections are crucial in technical books. They answer Who should read it, What each chapter discusses, and sometimes How to Read? This is helpful before reading the book. Who could know the ideal way to read the book better than the author, right?
I scan the chapter. Fast scanning is needed.
I review the headings.
I scan the pictures quickly.
I assess the chapter's length to determine whether I might divide it into more manageable sections.
Skimming is faster than reading but slower than scanning.
I focus more on the captions and subtitles for the photographs.
I read each paragraph's opening and closing sentences.
I examined the code samples.
I attempt to grasp each section's basic points without getting bogged down in the specifics.
Throughout the entire reading period, I make an effort to make mental notes of what may require additional attention and what may not. Because I don't want to spend time taking physical notes, kindly notice that I am using the term "mental" here. It is much simpler to recall. You may think that this is more significant than typing or writing “Pay attention to X.”
I move on quickly. This is something I considered crucial because, when trying to skim, it is simple to start reading the entire thing.
3. Complete reading
Previous steps pay off.
I finished reading the chapter.
I concentrate on the passages that I mentally underlined when skimming.
I put the book away and make my own notes. It is typically more difficult than it seems for me. But it's important to speak in your own words. You must choose the right words to adequately summarize what you have read. How do those words make you feel? Additionally, you must be able to summarize your notes while you are taking them. Sometimes as I'm writing my notes, I realize I have no words to convey what I'm thinking or, even worse, I start to doubt what I'm writing down. This is a good indication that I haven't internalized that idea thoroughly enough.
I jot my inquiries down. Normally, I read on while compiling my questions in the hopes that I will learn the answers as I read. I'll explore those issues more if I wasn't able to find the answers to my inquiries while reading the book.
Best part: If you take lovely notes like I do, you can publish them as a blog post with a few tweaks.
This is my learning journey. I wanted to show you. This post may help someone with a similar learning style. You can alter the principles above for any technical material.
18 days ago
Do You Have Focus Issues? Use These 5 Simple Habits
Many can't concentrate. The first 20% of the day isn't optimized.
Elon Musk, Tony Robbins, and Bill Gates share something:
A repeatable morning ritual saves time.
Time for hobbies.
I'll discuss 5 easy morning routines you can use.
1. Stop pressing snooze
Waking up starts the day. You disrupt your routine by hitting snooze.
One sleep becomes three. Your morning routine gets derailed.
Hide your phone. This disables snooze and wakes you up.
Once awake, staying awake is 10x easier. Simple trick, big results.
2. Drink water
Chronic dehydration is common. Mostly urban, air-conditioned workers/residents.
2% cerebral dehydration causes short-term memory loss.
Dehydration shrinks brain cells.
Drink 3-4 liters of water daily to avoid this.
3. Improve your focus
How to focus better?
Improve your mood
Enhance your memory
increase mental clarity
Reduce blood pressure and stress
Headspace helps with the habit.
Here's a meditation guide.
Shut your eyes.
Concentrate on your breathing
Breathe in through your nose
Breathe out your mouth.
5 in, 5 out.
Repeat for 1 to 20 minutes.
Here's a beginner's video:
focus and memory
15-60 minutes of fun:
Stretching and yoga
This helps you now and later.
5. Keep a journal
You have countless thoughts daily. Many quietly steal your focus.
Here’s how to clear these:
Write for 5-10 minutes.
You'll gain 2x more mental clarity.
5 morning practices for 5x more productivity:
Say no to snoozing
Improve your focus
One step starts a thousand-mile journey. Try these easy yet effective behaviors if you have trouble concentrating or have too many thoughts.
Start with one of these behaviors, then add the others. Its astonishing results are instant.