the final look of my portfolio

@natyiu0

This is impressive 👏

Your terminal, in your pocket.

Kiteline runs Claude Code on your own computer and puts every session on your phone. Self-hosted, open source.

kiteline.seefun.dev

github.com/sifenfisaha/kiteline

@sifendev

Heyyy guys! We're back!! Hope you all had a good weekend. Anywayyy, here's today's challenge. Let's see how it goes!

LeetCode Series — Day 5

📚 Concept: Matrices

Today's Challenge: Matrix Diagonal Sum

Given a square matrix, can you calculate the sum of its primary and secondary diagonals without counting the center element twice?
🔗 https://leetcode.com/problems/matrix-diagonal-sum/

Should I post the answer with explanation what do u say ?

Hey everyone! completed today's challenge but almost forgot to share it here. anyways here is today's part

LeetCode Series — Day 6

📚 Concept: Matrices

Today's Challenge: Transpose Matrix

Can you turn the rows of a matrix into columns and its columns into rows?

🔗 https://leetcode.com/problems/transpose-matrix/

Since most of you guys ask me about the sites I use to apply for remote jobs, here is a list of them along with their unique features.

1. LinkedIn: Country-specific jobs with easy apply options, featuring a high volume of new listings every day.
2. WellFound: A platform for finding jobs at small and medium-sized startups.
3. Talentmate: Remote jobs specific to the UAE.
4. Cord: A site dedicated to global remote jobs.
5. Jobgether: One of the largest sites for remote jobs, featuring AI and autofill capabilities.
6. Himalayas: A job site with profile matching and a wide selection of remote roles.
7. YO AI Labs: The largest network for AI training tasks.
8. Jobicy: Another platform for remote jobs.
9. Adzzat: A place to find AI training jobs.
10. SME Careers: Domain-specific AI training jobs.
11. Terac: Remote AI training opportunities.
12. ZipRecruiter: You build a profile, and they email you every job that matches it.
13. SWE List: You subscribe, and they send you internships and job listings daily.
14. Jooble: A source for US-only jobs.
15. Jobright: One of the largest job sites, also offering automatic job application features.

Here are all the sites I have discovered and use almost every day. Feel free to share other sites you know in the comments below.

@devwitheyob
#tips #JobSites

Good morning ❤️

In the age of AI, technology by itself is becoming less defensible. Code, interfaces, workflows, and even fairly sophisticated product features can now be reproduced much faster than before. If the main reason your company is difficult to compete with is simply that your software took a long time to build, that advantage is becoming weaker every year. The important shift is that implementation is being commoditized. When everyone has access to powerful models, coding agents, cheap infrastructure, and open-source components, the advantage moves away from who can build the feature and toward who can learn what should be built next.

That is what I mean when I say speed is the moat. I do not mean raw coding speed, and I do not mean shipping random features faster than everyone else. I mean the speed of the entire learning loop: how quickly you can notice a change in the market, form a hypothesis, build something, distribute it, observe how real users respond, kill what does not work, update your understanding, and make the next decision. The company that completes that loop faster gets more attempts at discovering the truth.

Imagine two companies attacking the same market with access to roughly the same technology. One company can run ten meaningful experiments in the time the other runs two. Even if most of those experiments fail, the first company has interacted with reality five times more often. It has learned more about customer behavior, willingness to pay, distribution, onboarding, retention, messaging, product priorities, and where its assumptions were wrong. Over one month the difference may look small. Over several years it compounds into a completely different understanding of the market.

This is why copying a product does not necessarily mean catching the company that built it. A competitor can often see your interface, reverse engineer your features, copy your pricing, and reproduce large parts of your product. What they cannot see as easily is everything that produced those decisions. They do not automatically have the customer conversations that caused you to remove a feature, the failed experiments that taught you which segment not to target, the data that changed your onboarding flow, or the insight that caused you to start building the next product before the current one became obvious to everyone else. They can copy the visible output, but they cannot instantly copy the learning history behind it.

The real question therefore is not whether someone can copy your product. In modern software, the answer should often be assumed to be yes. The more important question is whether copying today's product is enough to catch the company. If you are learning and evolving significantly faster than your competitors, they may reproduce where you were without understanding where you are going. They are copying a snapshot while you are operating a moving system.

AI makes this dynamic even more important because it lowers the cost of experimentation. If building an experiment used to take a month and now takes two days, the value of being able to choose, launch, and evaluate the right experiments becomes much greater. The bottleneck moves from engineering capacity to organizational intelligence. Judgment, product taste, customer proximity, prioritization, and decision speed become more important precisely because the underlying implementation becomes easier.

This also explains why small companies can sometimes outperform much larger incumbents. Large companies may have more engineers, more capital, more distribution, stronger brands, and deeper relationships. Those are real advantages. But scale often introduces coordination costs. A change that a founder-led team can make in a day may require meetings, planning cycles, cross-functional alignment, legal review, budget approval, and organizational consensus inside a large company. None of those processes are irrational; many exist for good reasons. But they create latency between seeing something and acting on it.

A startup's advantage is therefore not simply that it is smaller. It is that it can compress the distance between information and action. A user complains in the morning, the team understands the underlying problem by noon, a new version ships that evening, and the next day the team is already measuring whether the change worked. If that cycle happens continuously, the startup can accumulate hundreds of small learning advantages before a slower competitor completes a few major planning cycles.

However, speed should not be confused with permanent defensibility. Speed itself can eventually be copied. Competitors can hire better teams, reorganize, use the same AI tools, or create faster internal units. The deeper value of speed is what it allows you to build before that happens. Speed buys time, and inside that time you can accumulate the harder forms of defensibility: proprietary data, customer trust, brand, workflow integration, distribution, switching costs, ecosystem relationships, network effects, and operational knowledge.

This distinction matters because those advantages usually do not appear automatically at the beginning of a company. A startup rarely launches on day one with massive switching costs or a dominant network effect. Those things are earned through repeated interaction with the market. Speed increases the number of chances you have to earn them before someone else does.

It is also important to separate distribution from network effects. Having access to customers, investors, buyers, sellers, or influential people is valuable, but access alone is not necessarily a moat. A true network effect exists when each additional participant makes the product more valuable to the other participants, making the network increasingly difficult to replace. A competitor with better relationships may be able to reach your customers, but that does not automatically mean they can recreate a product whose value depends on the existing network itself.

At the same time, there are situations where speed is not enough. If an incumbent already has extremely strong network effects, regulatory protection, massive economies of scale, exclusive distribution, or very high switching costs, simply moving faster may not overcome those advantages. That does not weaken the argument. It clarifies it. Speed is most powerful as the mechanism that allows an emerging company to discover an opening, exploit it quickly, and build durable advantages before the market closes around it.

So the strongest version of “speed is the moat” is not that every other moat is fake. It is that in an environment where the cost of building software is collapsing, speed of learning becomes the foundational advantage from which many of the other moats are created.

Your code can be copied. Your interface can be copied. Your feature list can be copied. Your pricing can be copied. Your AI stack can be copied.

What is much harder to copy is a company that has spent years learning faster than everyone else and has converted that learning into customers, data, trust, distribution, workflow ownership, and network effects.

That is the real argument.

Speed does not make you impossible to copy.

Speed makes copying you insufficient.

"I can do all things through Christ who strengthens me."

— Philippians 4:13

Have a blessed day, peeps! ❤️

LeetCode Series — Day 7

📚 Concept: Matrices

Today's Challenge: Toeplitz Matrix

Given a matrix, can you determine whether every diagonal from top-left to bottom-right contains the same elements?

🔗 https://leetcode.com/problems/toeplitz-matrix/

I woke up for class and when I was about to leave the class canceled😎, what a day fr 🙃

Anyhow have a good day fam

To the next class 💃

LeetCode Series — Day 8

📚 Concept: Matrices

Today's Challenge: Count Negative Numbers in a Sorted Matrix

Given a matrix sorted in non-increasing order across its rows and columns, can you count how many negative numbers it contains?

🔗 https://leetcode.com/problems/count-negatives-in-a-sorted-matrix/

Good night peeps ✨️

LeetCode Series — Day 9

📚 Concept: Arrays

Today's Challenge: Find the Distance Value Between Two Arrays

Given two integer arrays and an integer d, can you count the elements in the first array whose absolute difference from every element in the second array is greater than d?

🔗 https://leetcode.com/problems/find-the-distance-value-between-two-arrays/

Have a great weekend everyone 🙌