Hey girl I will own you at each time you will be mine as long as we don't get out of scope my dear ,you will removing my rust yaani utanitoa kutu ,beb kazi ya germany codility nilipata 84 na walitaka 90,sina pesa don't reply ,I don't have a austrian visa like @MkenyaMzi ,gracias

gila banget exam hari, ga pernah se pressure ini exam, terakhir keknya ujian pernah setegang ini pas s1 kalo lagi ujian kayak codility🤢

Codility ya germany nimepata 84 na wanataka 87 saai ningekuwa uko lamu naangalia island for sale mamae

Tes codility nya susah ga kak? Seputar apa soalnya?

This is funny because some Polish AI specialists that work in American labs might also come from Russia.. Or some American labs can also be incorporated from poles or russians... I wouldn't say you're wrong but clearly we need some numbers here. For example, my landlord studied in Moscow university, and he can understand Russian but he forgot how to speak it... and we speak in English and a bit of Polish, and I'm trying to learn Polish if not sudden unemployment and fire extinguishing at Codility and my ADHD/OCD 🤣 How can we even get one? Or a better question... how do we distinguish between Russian / Polish individuals? Because some might even have two passports due to history🤷 Or am I too crazy?

The funniest thing is when you realize your brain is programmed the same way. You wouldn’t attempt solving a problem nobody trying to solve because they say it is impossible to solve. And yet I didn’t know I couldn’t solve specific software engineering problem, and I spent two month solving it and I realized that nobody tried to solve what I attempted. Nobody. Not a single person I know even aware of this problem I discovered. To me it seemed like such a simple thing to do 🤷‍♂️ And so… I’m not sure if I should write a paper after I finish working on it. I think this might lead me to a Turing award or something like that I don’t even know yet🤣 I just decided to write an algorithm what exactly I am doing as a software engineer and I figured exactly what happens and how to perfectly model this with a simple semantic graph and code. That is literally it. I can’t believe nobody ever tried to do this. Out of all software engineers and computer scientists. Somehow I’m the one building this thing that should have been built 50 years ago or earlier 🤷‍♂️🤷‍♂️🤷‍♂️ Why has nobody thought about connecting semantics to code? Verifiable semantic primes. For example you write a spec for „calculator” app and one criteria is it must be able to add two numbers. So you write a test for it, right? And so I was doing exactly that. For 13 years. Just writing tests for these specs that people gave me: verbally, Jira, Skype messages, zoom calls — so many ways to receive ambiguous requirements and make a spec out of them and then write a test for it. But then I joined Codility, and before I joined Stash. And before Edukey Education.. and no matter where I go I see same problem. Nobody has entire spec of the application they are building in their head. Because it is impossible to store specs for 500,000 lines of code in your mind. Documentation? Haha! Ask anyone have they ever seen documentation that is recent and not drifting from what the code actually does! Tests? Ha! Have you seen anyone adding semantic meaning to thousands of tests? They are just there for coverage! Nobody is worrying about losing product semantics. Engineers only care that build runs on CI and no errors are triggered and performance are good an UX. All of that important, sure. But product semantics is why are you even building an app. And to me it was so confusing why nobody ever figured out how to connect Jira to code. Yes you have ticket number in git commits. But nobody keeps track of it. We lose meaning, we lose coherence over time. And my solution? Just make spec live right inside codebase, a first class artifact like a git repo! And people trying to do it today and they call it spec driven development… Pfft 🤣 markdown is the worst possible artifact you can come up with. You cannot test markdown. You need tiny claims, criteria that make a larger spec. And then what? And then you realize that the perfect data structure for specs is a graph. But you can simulate graph with just ordinary database tables 🤷‍♂️ And that is exactly what I did. And it is amazing how simple it became to develop software now. Because I only focus on one spec at a time. And you can connect ANYTHING you can think of: metrics, logs, time spent, commits, tasks, code, tests, everything! EVERYTHING BECAUSE IT IS A GRAPH!!! And then I realized. YOU CAN DESCRIBE ENTIRE UNIVERSE WITH A GRAPH. ENTIRE. UNIVERSE. 🌌 And I just made this graph verifiable. One spec at a time we can verify anything we want. This is no longer a programming invention.. you can describe anything with it and verify with code… I’m still trying to process what the hell that I’ve created with just 5 tables… Man… That is what 2 months of uninterrupted thinking does. Anyway. The project is called usecoherence.dev And this is my best work so far. But I’m hoping to get a job because I want to continue working on it and life is expensive in Warsaw 🤷‍♂️ my runway is 2 months left… Thanks for reading.

"Interviewer: What's this 4-year gap? Me: That's when I went to Yale. Interviewer: Hired! Me: Thanks, I really need this yob." The joke works because Ivy League credentials still produce hiring outcomes that don't track actual skill. The data. McKinsey's annual recruiting class is roughly 8,000 globally. Of those, 38% come from 8 schools (Harvard, Yale, Princeton, MIT, Stanford, Wharton, Columbia, Chicago). Those 8 schools produce roughly 8,000 graduates per year combined. McKinsey is taking 38% of its hires from a pool that represents 0.4% of the US college-graduating population. The pattern repeats at Goldman Sachs, Morgan Stanley, Apollo, Blackstone, KKR, Carlyle, BCG, Bain, and every top consulting and finance firm. The credential filter is more important than the skill filter at the first job. The first job enables the second. The credential effect compounds for 10-20 years before "what you actually do" overrides "where you went." The criticism has merit. Yale graduates are not uniformly more capable than graduates of UMass Amherst or Indiana University. Selection bias at admissions explains some apparent quality gap (Yale takes the top 5% of applicants). Network effects explain more (Yale alumni connect Yale graduates to Yale-favored employers). The pure educational delta is small compared to the credential signal value. The defense. Credentialing reduces transaction costs in hiring. An interviewer can confidently assume a Yale graduate cleared specific cognitive and effort thresholds. The 2026 update. AI tools are starting to dismantle the credentialing economy. Skill assessments via Codility, HackerRank are increasingly used in tech hiring. The credential effect is weakening at the margins but still dominates the first 5 years of a career.

I'm currently job hunting and I can say for sure, due to the high number of applications, companies are using code tests to filter out people. I've come across multiple Hackerrank, codility and test gorilla assessments. Some are not LC style, but most are.

If I were to rewrite the calendar like Pope Gregory and Ceaser, I would divide the epochs into pre-LLM and post-LLM eras. Life before ChatGPT (and Covid) is vastly different from life today. I remember advising upcoming software engineers that, in this field, nobody cares about your soft skills. You ought to fill your resume with hard technical skills to show employers what you can really do. Nobody, I argued, cared about your communication and conflict-resolving skills as much as they wanted to know whether you can ship functional code, optimise a database, or debug a complex system. That advice was perfectly sound for the pre-LLM world. Employers needed people who could sit in a corner, translate business requirements into Python or Java, and push it to production. Raw coding ability was sufficient. I recently interviewed for a role where I was provided with an AI coding assistant that I was free to refer to during the technical assessment. Remember when, during code interviews, you were given a marker pen and were to write the perfect solution extemporaneously on a whiteboard? Back then, mastery of syntax and algorithms was your professional moat. But as Bob Dylan so prophetically sang, the times, indeed, they are a-changing. Two of my skills that I’ve spent decades acquiring, writing and coding, have since been usurped by AI, which does them faster and, in most instances, even better. I was pondering on this when I came across an article by CTO Yue Zhao where she described 3 centres of wisdom: the Head, the Heart, and the Gut. In my early career, the tech industry exclusively worshipped the Head. You went on Codility and practised data structures and algorithms daily. “A LeetCode a day keeps unemployment away”, a popular saying went. Now, AI is the smartest entity in the room. It has ingested every repository on GitHub and every documentation page ever written. The Head is no longer a differentiator. It is merely the baseline. This brings us to the Heart and the Gut, where AI still struggles to replicate. The Heart represents connection and empathy. Those soft skills I used to tell juniors to leave off their resumes are now the most critical tools we have. AI cannot sit down with a confused stakeholder, read their frustration, and figure out what product they actually need. It cannot mediate a dispute between two devs stubbornly arguing over an architectural choice. The Gut is our ethical compass and instinct. It is the intuition that tells you a certain system architecture feels brittle before a single line of code is written. AI lacks the capacity to make moral judgements. It will build exactly what you ask it to build, with little nuance. The Gut is what allows an engineer to say no, to hold the line on quality, and to foresee downstream consequences. Do we still have room for an engineer like me, who still believes there’s value in knowing how to manually configure a Kubernetes cluster, even though AI can now do the same task on the fly?

Want to get into product based companies? Product-based companies hiring timeline where to apply 📅 🟢 Google • Timeline: Aug – Oct • Process: OA (Coding Test) Interviews • Where: careers.google.com 🔵 Microsoft • Timeline: July – Sept • Process: Codility / HackerRank OA • Where: careers.microsoft.com 🟡 Amazon • Timeline: Aug – Nov • Process: Online Assessment (DSA MCQs) • Where: amazon.jobs 🟣 Adobe • Timeline: Aug – Oct • Process: HackerRank OA • Where: adobe.com/careers 🟠 Atlassian • Timeline: Sept – Nov • Process: HackerRank System Design • Where: atlassian.com/company/career… 🚗 Uber • Timeline: Sept – Nov • Process: HackerRank OA Interviews • Where: uber.com/careers 🛒 Flipkart • Timeline: Aug – Oct • Process: HackerEarth OA • Where: flipkartcareers.com 💳 Razorpay • Timeline: Rolling Sept peak • Process: DSA Machine Coding • Where: razorpay.com/jobs 🍔 Swiggy / Zomato • Timeline: Rolling • Process: DSA Practical Rounds • Where: careers pages ☁️ Salesforce • Timeline: Aug – Oct • Process: HackerRank OA • Where: salesforce.com/careers 🏦 Oracle • Timeline: Rolling (Sept–Jan peak) • Process: Online Test Interviews • Where: oracle.com/careers 📊 SAP / Intuit • Timeline: Aug – Oct • Process: Coding CS fundamentals • Where: official career pages (Save this before hiring season starts 📌) Which company are you targeting this year?

Мы используем Codility, там встроенный браузерный vscode с чем-то типа intellisense, подсказывает методы и однострочники, и мы в целом норм)

Nangojea tweet ya you are angry at Safaricom you failed codility test will be assigned to you ama bado hajaona.😂😂😂😂😂

Wewe ni hater ju ukifail codility test ya safaricom ndugu, that app is very efficient , you are an engineer with no product to show 😅😅😅😅😅

Did those devs really need to pass codility to ship garbage...

You are justing on safaricom because you failed Safaricom codility test, you are an engineer with no product to show for it, stop hating in safaricom our unicorn

This is actually huge! Hacker Rank is one of the leading interview test platforms like Coder Pad, Code Signal, Codility, etc.. As a swe you will be spammed with these tests before ever speaking to a human. The problem is they have strict anti-ai policies that force you to write code by hand. which is just absurd in this day and age. This signals a HUGE shift in the develper space and hope to see more companies move in this direction

Tuko na Codility test😂

day 47 building invisible AI for interviews & tests/exams in public ☑️ worked on new undetectability features (never seen) ☑️ test/exam platforms like honorlock, codility, mercer, have been added to the list of tested 🎉 shoutout to 7 new users Try Velin AI @ velinai.live listened to your feedback, and I’m making keyboard commands custom to you, and adding mouse gestures for getting answers undetected. been locked in setting up reddit and yt, have to move launching here to next week.🙏 pass any live interview, test or exams with zero effort.

Kuna time codility itakuja na kichinku 😂😂😂😂 Waiyaki way watch the space muone

Hao interns walikuwa codility test juzi wakatumia AI kwani wameanza kazi