Mykhailo Faraponov

Job listings should stop using non-sense requirements like: ❌ 5 years in C# ❌ 7 years in React ❌ 10 years in enterprise software development They are not only poor metrics but also scare away developers. Judging a developer by the number of years is like judging a book by the number of pages. I know many young developers who are already better than many seniors with 10 years of experience but repeated the same year 10 times. Value developers for the depth of their journey, not the length of it.

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Pizza won't motivate your developers. Beers won't motivate your developers. Ping-pong won't motivate your developers. Your developers don't need motivation. They are already motivated to work in tech. You just need to stop demotivating them. Throwing pizza and beers at problems doesn't fix it. Instead, - ditch micromanagement - remove everything that slows them down - focus on dev experience The goal is to have an environment that doesn't demotivate them.

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I can’t stress this enough: To become a Senior engineer you don’t need to complicate things. What you need is to focus your efforts on being pragmatic, business-oriented, and solution-oriented. I’ve seen too many talented mid-level devs shooting themselves in the foot by: 👉🏻Adding unnecessary abstraction layers “for future flexibility” 🤦‍♂️ 👉🏻Implementing design patterns that solve problems that don’t exist 👉🏻Building “elegant” solutions that take 3x longer to ship. Meanwhile, senior devs are out there asking the right questions: 👉🏻”Whats the simplest solution that works?” 👉🏻”What are we actually optimizing for?” 👉🏻”Will this help the business or just my ego?” Your promotion isn’t blocked by lack of complexity, actually it’s blocked by too much of it. Save your creative energy for problems that actually need complex solutions.

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🤵 Tech Lead: "We will start using DDD in our project!" 🤔 Me: "Cool! Is it Domain-Driven Design?" 🤵 Tech Lead: "Yes!" 😃 Me: "Nice! What will we do then?" 🤵 Tech Lead: "First, we will extract interfaces from all our DAOs and call them ‘Repositories’. Then, we will create big objects using ‘Factories’ instead of services..." That was a real conversation between my tech lead and me back in 2009. We tried to introduce DDD into a project. It didn’t go well. The codebase became even more complicated. And we concluded that DDD was a waste of time and didn’t work. Years later, I see many developers falling into the same trap - thinking DDD is just about repositories, factories, and aggregates. ❌ DDD is NOT about your code. Just because you have tactical patterns doesn’t mean you’re doing DDD. ✅ DDD is about understanding and structuring complexity: 🔹 Finding the right language to communicate with business. 🔹 Breaking down a complex domain into meaningful parts. 🔹 Understanding relationships between those parts. 🔹 Prioritizing: What’s core? What’s supporting? What can we buy? 🔹 Clarifying who owns and implements each part. 🔹 And only THEN, applying tactical patterns in code. Did anyone else start with “coding” DDD before understanding the strategic part? 😃

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When adding caching to your application, your strategy determines how reads and writes happen. Of course, different approaches have various trade-offs. Pekka Enberg, Founder and CTO of Turso, looks at six latency vs. complexity strategies and the pros/cons of each via The New Stack > https://lnkd.in/ePPgR9Q6 #ScyllaDB

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Nia by Nozomio is an MCP that gives coding agents 10x more developer context. It indexes external repos and docs, so any coding agent always has the right context. At 17, Arlan Rakhmetzhanov was kicked out of math classes for taking sales calls, so he dropped out of high school and raised a pre-seed round within days. He cold-emailed his way into research at Stanford and worked closely with a Caltech professor on an interactive tool for finding defects or suspicious patterns in source code. Now, this founder from Kazakhstan is back with Nozomio and its first product, Nia, born from his frustration with all coding agents. Developers love coding agents but still rely on them to retrieve the right and up-to-date information, whether it's open source SDKs or Stripe docs. Context, not code generation, slows everything down. Nia solves that problem. It indexes external repos and entire docs, then passes the most relevant information to any agent through an MCP server. In our own tests, Cursor’s accuracy increased by 27%. Plug it into any IDE and let the agent “just know” what you know, so you can ship code instead of searching for context. Congrats on the launch, Arlan! 🚀 https://lnkd.in/g--deCzE

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EKS (Kubernetes) or ECS 🤔 Here's the problem: Many engineers are slightly confused to make a choice. It's not their fault. It's not an easy choice 💯 Especially when the requirements are not very clear. Which is usually the case with the customer anyways 😁 But generally speaking. If you see high scaling, portability demands and complex compliance requirements, then EKS is a good choice 😃 For teams new to K8s, its a tough choice. ECS on the other hand can also handle scale. Its easy to manage. Aligns very well with smaller teams, teams with less devops experience. But portability and fulfilling compliance requirements can be challenging. You are free to make your choice, but you are not free from the consequences of your choice. So ask right questions, it will help you make the right choice 🤠 Thats it for today. Hope this is useful. A repost helps ♻️ P.S. What are you using right now? And are you happy with your choice?

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📣 JetBrains is trying to better understand how developers work in .NET development and what tooling they prefer to be more productive. Influence the evolution of the .NET tooling on the market by filling out the JetBrains survey: https://hubs.li/Q03sTXZg0 https://hubs.li/Q03sTWzy0

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💡 Software Development Interview Questions That Even Smart People Fail! 🚀 Technical skills alone don’t guarantee success in SD interviews. Many brilliant developers struggle—not because they lack knowledge, but due to overthinking, unclear problem-solving approaches, or missing edge cases. 🔹 Common Pitfalls: ✅ Rushing to code without fully understanding the problem ✅ Ignoring edge cases and optimizations ✅ Struggling with time pressure & communication ✅ Overcomplicating simple solutions Interviews are about clarity, logic, and structured thinking, not just raw intelligence. The smartest candidates are the ones who stay calm, communicate well, and break down problems effectively. To know more, do check out here👇 Ever faced a tricky interview question that caught you off guard? Let’s discuss in the comments! ⬇️ Do follow Tutort Academy for more such content. Save now, learn anytime!📍 #SoftwareDevelopment #Interviews #Coding #tutortacademy

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I often talk to #CTOs, and a common topic is #technicaldebt. They say it slows down everything, makes development risky, and developers are not happy. In the same talk, the word "#refactoring" comes up. Developers want a big refactoring to fix the code. Business wants more features. This always creates a conflict. But this is a false dilemma. The problem is that many people misunderstand what refactoring is. They think it's a huge project, where you rewrite code for weeks to make it clean. But if you read the book "Refactoring", this is not the definition. Real refactoring is making small, continuous changes to improve the code design without changing what the code does. If it takes weeks, it is not refactoring. It is a rewrite. The correct way is constant refactoring. When you work on a feature, you see something to improve? Refactor it. When you finish a feature, you see a way to make the design cleaner? Refactor it. This is the key: Constant refactoring keeps code clean and flexible. It prevents the need for a big, painful rewrite. My advice for #CTOs: * Push your developers to refactor all the time. It is part of the job, not a special project. * Protect your team from business pressure to ship low-quality code. Good quality now means more speed later. #TechnicalDebt #Refactoring #SoftwareDevelopment #CTO #Agile #CleanCode #EngineeringLeadership

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This developer outsourced his entire job to China. Paid contractors a fraction of his salary. Spent workdays watching cat videos. Until a routine security audit exposed everything: "Bob" was a software developer at a critical infrastructure company. Strong performance reviews. His manager called him "the best developer in the building." Security noticed VPN logins from China while Bob sat at his desk. The investigation revealed he'd mailed his security token to a Chinese firm. They logged in as him daily, writing all his code for $50,000/year. Bob's actual workday: Reddit, lunch, eBay, cat videos, home. He was paying the firm one-fifth of his six-figure salary. Even had similar arrangements with other companies. No data theft. Just policy violations that destroyed his career overnight. But here's what most miss about this story: Bob understood leverage better than 99% of founders. His execution was criminal, but the principle reveals how to scale properly. The difference between Bob's approach and sustainable delegation: 1. Delegate outcomes, not entire roles Bob handed over his identity with zero oversight. Smart founders delegate specific deliverables: "Build this feature with these 5 metrics by Friday. Weekly reviews are on Tuesday." One client reduced their operational hours from 60 to 15 per week using this framework. 2. Use the 10-80-10 model Bob went 0-100-0. Did nothing, the contractor did everything, no review. Better: Spend 10% defining the project, contractors execute 80%, you review the final 10%. Maintains quality while reclaiming 70% of your time. 3. Build transparent systems Bob hid everything. Real leverage requires visibility. Every outsourced task needs clear SOPs, progress tracking, and quality metrics. The irony? Had Bob been transparent, he might've pioneered remote work. Instead, he became a cautionary tale. Want to build leverage without losing control? Send me "AUDIT" and I'll share our delegation framework that has helped founders reclaim over 1,000 hours.

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One week until my Node.js workshop in London, and I need to share a production lesson that cost an enterprise team three weeks of wasted effort: "Performance optimization without proper measurement is just expensive guesswork." An enterprise team contacted me after spending three weeks "optimizing" their Node.js API that was experiencing response time degradation. Their approach seemed logical: ✅ Rewrote database queries for better efficiency ✅ Added Redis caching layers ✅ Refactored async/await patterns ✅ Upgraded to latest Node.js version The result? Performance improved by 2%. When we ran proper profiling tools, the issue became immediately clear: a single JSON.stringify operation on massive user objects was consuming 85% of CPU time per request. One line of code was the bottleneck. Everything else they optimized was essentially noise. Without measurement, they spent weeks optimizing the wrong things while the actual problem remained untouched. This is why my workshop always starts with diagnostic tools before optimization techniques: 🔥 Node.js built-in profiler for identifying CPU bottlenecks and hot code paths 📈 Clinic.js suite for comprehensive performance analysis and visualization 🎯 OpenTelemetry distributed tracing for request flow analysis across services ⚡ Custom application metrics for domain-specific performance patterns Knowing the tools isn't enough. The key is knowing which diagnostic approach fits which performance problem: CPU-bound issues require flame graphs to identify hot functions. Memory leaks need heap snapshots and allocation tracking. Async bottlenecks require distributed tracing to understand request flow. I/O problems need different analysis than computational problems. Using the wrong diagnostic tool wastes time and leads to incorrect optimization decisions. We'll use this measurement-first approach to work through real production scenarios in London. There will be no theoretical examples and no premature optimization based on assumptions. We'll diagnose actual performance problems using the appropriate tools, then implement targeted optimizations that deliver measurable improvements. This is how senior developers approach performance: data-driven decisions, not educated guesses. 📅 Monday, September 29th | London ⏰ Final week to register Register:

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Ever struggled with the "black box" nature of AWS SQS during local development? 🤔 You can't inspect messages without affecting the queue, delayed messages stay hidden, and you're left guessing if your retry logic works. 🙃 That's why we built the SQS Developer Endpoint in LocalStack! With this, you can: 🔎 Peek into queues without side effects 👁️ See delayed and in-flight messages instantly 🚫 Avoid visibility timeouts and queue manipulation 🔄 Debug retry flows and transient failures effortlessly Check out this tutorial by Harsh Mishra, who walks you through building a complete SQS workflow with producer/consumer Lambdas and shows exactly how to use this endpoint to trace message lifecycles end-to-end. 🔗 https://lnkd.in/gv-8sMNW #LocalStack #AWS #SQS #CloudDevelopment #Debugging #ServerlessDevelopment #DeveloperExperience

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"I was juggling multiple test frameworks, environment conflicts, and the dreaded 'it works on my machine' fiasco." 😱 In today's development world, Vladimir Mikhalev explains that containerization and reliable end-to-end testing have become "practically mandatory if you want to keep up with lightning-fast release cycles." Vladimir shares how he perfected his E2E testing setup for consistency, scalability, and security: ✅ Upgrade to Node 22.x (or newer) ✅ Optimize your Dockerfile ✅ Parallelize using Docker Compose scaling or the Cypress Dashboard ✅ Harden your containers ✅ Implement a Healthcheck Read our #CypressAmbassador's full piece: https://lnkd.in/eZVS5qmW

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