Messi Bre

So I have decided to write the blogs in different kinds I didn't want to just say, "do this, don't do this." I wanted to take you through the whole process and let you take the lesson on your own. so here is my first hackathon experience - hope it helps :) Link @MessiBre

You learn a thing or two every day

Btw I forgot abt this one So personally I love md files and having them opened in tg makes it betterrrrrr. But changing texts/pdf... to .md ughhh - well chatgpt gets its limit after just one and claude - it got more usefull jobs to do 😁 so I just thought well lemmi vibe code it as a bot and here @mdifer_bot After some inactivity its getting idle , also AI feature might be slowww 😩 Btw where do u deploy ur bots?🤔 @mdifer_bot @Messibre

🚀 Upcoming Hackathons 1. Accessibility Hackathon 2026  Build tools that make learning and work more accessible for people with disabilities, refugees, and returnees. Choose from three tracks, with an optional Career Gateway challenge.  📅 November 14–15 | 📍 ALX Tech Hub, Lideta  🏆 Win 100,000 ETB  Register: LINK  2. Dev3Pack Hackathon 2026  Build AI and blockchain apps on Solana. Join online or at the Addis Ababa Build Station.  📅 November 27–29  🏆 $10,000+ top prize, local prizes, Seeker Phones, and student perks  Register: LINK 3. NASA Space Apps Challenge Addis Ababa 2026  Join developers, designers, and innovators for 48 hours of creative problem-solving.  📅 November 14–15 | 📍 Sheger Institute of Technology (SIT) LINK @CTBEsoftwareengineers

Huhh 🤔 https://www.lennysnewsletter.com/p/state-of-the-tech-job-market-late @Messibre

does everyone like .md files or is it only me?👀

🥰❤️ @techmemesonly 🤌

Join us for Avalanche Connect: Bishoftu Meetup designed to onboard local builders, creators,Crypto guys and students into the ecosystem. ​🔥 35 Seats 📚How to learn in Avalanche Academy 🎁 Swag bounties for top attendees 🤝 Powered by Fanos & Avalanche Team1 ​📍 Bishoftu | 🗓️ Nov 15, 2026 (ህዳር 6, 2019) ​Ready to scale your Web3 journey? Grab your seat before it fills up! 👇 እዚ event ላይ መገኘት ምትፈልጉ/interest ካላቹ ከታች ባለው ሊንክ register አድርጉ መጠየቅ ምትፈልጉት ነገር ካለ Dm አድርጉኝ (@BEAST_ZEMASS) Specific ቦታው አሳውቃለሁ Everyone is welcome to join us! 🤝 🔗 https://luma.com/q2yjn6x6

I feel like am watching z game in person 😂 Thanksss for z live stream @birhan_nega

ተፈፀመ 🥹

#ማኅሌተ_ጽጌ አምስተኛ ሳምንት #ተፈጸመ

Tech should work for everyone. Calling developers, designers & innovators! Join the Accessibility Hackathon 2026 and build tools that make learning and work accessible for people with disabilities, refugees & returnees in Ethiopia. Choose your track: •⁠ ⁠Accessible Onboarding Kit •⁠ ⁠Accessible Learning Media Kit •⁠ ⁠Multilingual Learning Assistant ➕ Add to any track: Accessible Career Gateway Win 100K ETB! 🗓 November 14th & 15th, 2026 (ቅዳሜ እና እሁድ፣ ህዳር 5 እና 6፣ 2019) 🕗 8፡30 AM – 5:30 PM | (ከጠዋቱ 2፡30 - 11፡30) 📍 ALX Tech Hub, Lideta Save your spot here: https://digitalbridge.et/ Join the community: t.me/AccessibilityHackathon2026 #ALXEthiopia #LifeAtALX #ALXAfrica #DoHardThings #accessibilityhackathon #techforall

"Find an interesting software product that already exists. Research its purpose, understand its core features, investigate its publicly documented architecture where available, and identify the engineering problems involved. Then build a smaller version yourself." 👌👌 article

where z f**k have I been when ppl were using my project 😭😭 I didn't even market it. I was just refactoring it this week just to see if it can help in the next dev3pack hackathon. Damnn forgetting projects once we found another new one glad I decided to stop working on projects am gonna market all my built projects from now on @Messibre

some non hackathons questions are also coming Sent if you got any and I will answer them all at once.

Does winning 6 hackathons(2 international) out of 10 participations make me eligible to share some wisdom? 😅😂 Some were asking me and I am thinking either to write some blogs or host one live session. If u got any questions to me abt hackathons - drop them here. I will try to address them once I decided how. https://sma.et/b/Z-xfzVh1gT3d @Messibre

i have been busy lately but now i have got some time i was working on Worksim our team project for Stark Hackathon here is a sneak peak😁 i need to cook on this one

So crazy how far we have come motivating each other fr I remember he commented on my @fullstackCampp channel for z first time , and since then we have been supporting each other and its been more than a year. @Messibre

Solana For Students is coming to 🇪🇹 on Nov 20 Join our student program to: 🎯 Discover upcoming opportunities 🛠️ Contribute to @solana & land your first job 💻 Learn how to build your skills & portfolio 🤝 Meet local experts Register here 👇 luma.com/8c9ik16p @dev3packethio

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.