Best of Career — December 2025

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Video
CodeHead·21w
Why It Sucks To Be A Fullstack Dev Now
Full stack development has evolved from a valuable versatile skill into an overwhelming expectation to master an ever-expanding technology landscape. The modern stack spans frontend frameworks, backend infrastructure, cloud deployments, and DevOps, forcing developers into shallow knowledge across all areas rather than deep expertise. This creates constant context switching, impostor syndrome, and unrealistic job expectations where companies seek multiple specialized roles under one title. Specialization with T-shaped skills is proving more effective than attempting to master everything, suggesting developers should choose depth in one area while maintaining collaborative breadth.
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Article
Developer's Journey·21w
Documenting my learning as a developer — focusing on process, not just outcomes
A developer shares their approach to documenting the learning process itself rather than just finished projects. The focus is on capturing what's being learned, tested, and how understanding evolves over time for clarity and consistency. They view documentation as a skill that improves decision-making and long-term growth, and invite others to share their own learning documentation practices.
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Article
freeCodeCamp·19w
How to Prepare for Technical Job Interviews – Based on My Experience Landing a Job
A web developer shares their 18-month job search journey, detailing how they struggled with technical interviews despite having the necessary skills. The core issue was recall under pressure, not knowledge gaps. By adopting active recall techniques using flashcards, asking recruiters what to prepare for, and shifting job search strategies to smaller communities, they eventually landed a $5,500/month position with relocation. The approach emphasizes consistent practice of fundamentals, targeted preparation, and strategic job hunting over mass applications.
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Article
Cassidy's blog·22w
Goodbye to an 11-year-old Issue
A reflection on an 11-year-old GitHub issue that was recently closed, prompting thoughts about how much has changed in the software development landscape and the author's career since 2014. The post touches on the evolution of GitHub features like Discussions and GitHub Flavored Markdown, while sharing personal milestones and career growth from early developer evangelism days to working at GitHub itself.
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Video
Google for Developers·21w
3 skills every early-career engineer needs
Early-career software engineers should focus on three fundamental skills: writing clean, maintainable code with meaningful names and simple logic; developing a quality mindset through comprehensive testing that prevents regressions and enables confident refactoring; and mastering essential tools like version control, debugging techniques, documentation practices, and communication skills. These foundational practices create long-term career success more effectively than chasing the latest frameworks.
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Article
Advanced Web Machinery·18w
Why I prefer multi-tenant systems
Multi-tenant architecture offers significant advantages even for single-customer systems. Key benefits include parallelizable integration testing through tenant isolation, production monitoring that mimics real user behavior without affecting actual clients, safe demo environments for sales and developers, and flexibility for future business evolution. The complexity overhead can be minimized using database-level features like PostgreSQL's row-level security, which centralizes tenant filtering rather than requiring it in every query.
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Article
System Design Codex·22w
Top Microservices Patterns
Four essential microservices patterns are explored: Database Per Service (each service manages its own data with well-defined APIs), Shared Database (multiple services access a common database, useful for migrations but with coordination overhead), API Composition (aggregating data from multiple services through in-memory joins), and CQRS with Event Sourcing (separating read and write operations while storing state as event sequences). Each pattern presents distinct trade-offs between isolation, performance, and implementation complexity.
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Article
ByteByteGo·22w
How Netflix Built a Distributed Write Ahead Log For Its Data Platform
Netflix built a distributed Write-Ahead Log (WAL) system to solve data reliability issues across their platform. The WAL captures every data change before applying it to databases, enabling automatic retries, cross-region replication, and multi-partition consistency. Built on top of their Data Gateway Infrastructure, it uses Kafka and Amazon SQS as pluggable backends, supports multiple use cases through namespaces, and scales independently through sharded deployments. The system provides durability guarantees while allowing teams to configure retry logic, delays, and targets without code changes.
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Article
Hacker News·20w
AWS CEO Explains 3 Reasons AI Can’t Replace Junior Devs
AWS CEO Matt Garman argues against replacing junior developers with AI, citing three key reasons: junior developers are often more proficient with AI tools than senior staff, they represent minimal cost savings as the lowest-paid employees, and eliminating them breaks the talent pipeline that companies need for future growth. He emphasizes that junior hires bring fresh perspectives, adapt quickly to new technologies, and form the foundation for developing future leaders. While acknowledging AI will change how developers work, Garman believes it will ultimately create more jobs than it eliminates in the medium to long term.
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Article
Tech World With Milan·20w
10 software essays that changed how I think
A curated collection of 10 influential software engineering essays spanning 1989-2022, covering technology selection (Choose Boring Technology), type safety (Parse Don't Validate), refactoring strategy (never rewrite from scratch), monolith vs microservices architecture, team process health (Joel Test), API design principles, simplicity over perfection (Worse is Better), complexity management, quality-speed tradeoffs, and career positioning. Each essay is accompanied by personal lessons learned and practical applications, emphasizing pragmatism, simplicity, and business value over technical perfectionism.
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Article
Engineer’s Codex·20w
Everyone is a Staff Engineer Now
AI coding agents like Claude Code are shifting engineering work from implementation to higher-level activities like architecture, planning, and code review. Skills traditionally associated with staff engineers—maintaining context across systems, managing asynchronous workflows, steering AI agents effectively, and reviewing code—are becoming baseline requirements earlier in careers. Junior engineers now operate at senior-level abstraction while seniors architect at staff-level scale. Success depends less on prompting AI and more on managing personal context, maintaining focus during agent runtime, and developing new workflows that treat AI as a junior engineer to delegate to.
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Video
Let's Get Rusty·20w
I’m a Rust developer, here’s what I’d do if I had to start over
Three key strategies for learning Rust more effectively: focus on domain-specific knowledge rather than trying to master every feature, maintain consistent progress through community support and mentorship instead of repeatedly restarting, and learn with the goal of becoming job-market ready to ensure practical skill development. The approach emphasizes learning only the 20% of Rust needed for your specific use case, whether backend services, embedded systems, or blockchain development.
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Video
Anthony Sistilli·20w
ai is making you a bad programmer.
AI coding assistants may diminish critical thinking and programming skills through overreliance, as studies show reduced problem-solving abilities compared to manual coding. The impact depends on your goals: purists who view coding as a craft should minimize AI use to maintain deep expertise, while those focused on business outcomes can leverage AI as operators. Senior engineers have the advantage of choosing either path, though many resist AI due to ego or outdated perceptions. The key tension is between skill atrophy from AI dependence versus increased productivity for delivering business value.
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Video
CodeHead·20w
How To ESCAPE Imposter Syndrome
Imposter syndrome in software engineering stems from the gap between external recognition and internal self-doubt, often intensifying with career progression. Combat it by grounding yourself in evidence rather than feelings, comparing yourself only to your past self rather than others online, and reframing doubt as a signal of growth. Build your identity around continuous learning rather than status or titles, recognizing that discomfort often indicates you're stepping into new challenges where you're supposed to be.
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Video
The Serious CTO·20w
7 Signs You’re a Stuck Developer (And How Senior Engineers Break Free)
Seven behavioral patterns distinguish developers who advance from those who stagnate: taking initiative without permission, working around obstacles instead of complaining, documenting achievements systematically, admitting knowledge gaps confidently, measuring progress against past self rather than peers, curating relationships that support growth, and taking ownership instead of blaming external factors. Each pattern is actionable through specific weekly practices like maintaining a brag document, proposing solutions proactively, and auditing time spent with colleagues.
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Article
The Palindrome·22w
The Story of the Mathematics of Machine Learning Book
A mathematician shares his four-year journey of accidentally writing a 700-page machine learning textbook while building an audience through Twitter threads and Substack. Starting as a creative outlet after a failed startup, he validated the idea through early access sales, navigated platform algorithm changes, and eventually partnered with Packt Publishing. The story covers content creation strategies, the challenges of self-publishing versus traditional publishing, and how constraints like Twitter's character limit shaped his teaching style and visual approach to explaining complex mathematical concepts.
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Article
Towards Data Science·21w
6 Technical Skills That Make You a Senior Data Scientist
Senior data scientists distinguish themselves through a structured six-stage workflow for building data products: mapping the business ecosystem, defining product constraints as operators, designing systems end-to-end before coding, starting with simple models and adding complexity only when justified, rigorously evaluating outputs through manual review and appropriate metrics, and tailoring communication to different audiences (product managers, engineers, other data scientists). The emphasis is on understanding context, making design-level trade-offs, and delivering production-ready solutions rather than just technical coding ability.
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Article
Foojay.io·22w
Building Systems That Know Why They Exist ~ When Data, Logic, and Intent Finally Align
Requirements-as-Code (RaC) is an engineering discipline that treats requirements and business rules as executable data models rather than static documentation. By storing requirements as structured, versioned data in systems like MongoDB, software can maintain a living connection to its original intent throughout its lifecycle. This approach enables systems to interpret documented purpose at runtime, validate behavior against intent, and maintain semantic alignment between what software does and what it was meant to do. When combined with AI for natural language compilation, RaC creates systems that don't just execute code but understand why they exist.
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Article
Kogan.com·22w
Patterns & Best Practices in Event-Driven Systems — Kogan.com Dev Blog
Event-driven architecture enables decoupled, scalable systems through five core patterns: event notification (lightweight signals), event-carried state transfer (self-contained payloads), event sourcing (immutable change logs), choreography (decentralized workflows), and orchestration (centralized coordination). Essential practices include implementing idempotency to handle duplicate events, using durable message streams for replay capability, versioning events explicitly, managing schemas through registries, naming events after business domain concepts, and tracking requests with correlation IDs for distributed debugging and observability.
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Video
Coding with Sphere·20w
Stop coding so much
Coding can become all-consuming, crowding out other hobbies and interests. While passion is valuable, over-specialization early in your career limits creativity and project ideas. Maintaining diverse hobbies outside programming provides fresh perspectives, inspires meaningful projects, and expands your comfort zone. Balance enhances rather than diminishes your coding abilities, giving you real-world problems to solve instead of optimizing tools endlessly. Stepping into uncomfortable new areas translates to better adaptability as a developer.
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Video
bigboxSWE·18w
THE WORST YEAR IN PROGRAMMING HISTORY
2025 has been challenging for software engineers with a severe job market downturn worse than the pandemic era, where even top university graduates struggle to find entry-level positions. Despite widespread AI adoption, software quality hasn't improved—instead seeing record outages and code quality issues. The industry faces rising costs for development tools, forced AI integration into products that don't need it, and a shift away from fundamental improvements in favor of buzzword-driven features. While some positive developments exist (Rust in Linux, TypeScript updates), the overall direction feels exhausting, though the fundamentals of being good at programming and staying adaptable remain constant.
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Article
Tech Lead Digest·21w
Proof of Concept
Succession planning is critical for organizational continuity and long-term impact. Leadership transitions should be prepared years in advance through long shadowing periods where successors gain exposure to key responsibilities. Successful handoffs like Apple's Tim Cook, Microsoft's Satya Nadella, and Nike's Mark Parker share common traits: successors already performed pieces of the job, developed their own style, and were visible to the organization long before the transition. Effective succession requires delegating real responsibility, removing single points of failure, ensuring industry knowledge, and treating it as an adaptive, ongoing process rather than a one-time event.
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Video
ThePrimeTime·21w
"Software Engineering is Done"
A commentary on the recurring pattern of people declaring software engineering obsolete with each new AI model release. The author expresses frustration with the repetitive doom-and-gloom predictions that have accompanied launches of ChatGPT, Claude, Gemini, and other AI tools, noting how each release triggers the same "software engineering is done" reactions despite the field continuing to exist.
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Article
Coins Bench·22w
Why Web3 Résumés Are Useless — And What Founders Actually Look At Instead
Traditional résumés fail in Web3 hiring because they showcase experience and credentials rather than critical thinking, risk assessment, and debugging skills. Founders prioritize GitHub activity, test quality, PR communication, and reasoning ability over formatted documents. The article argues that candidates should focus on demonstrating their thought processes through code, tests, and architectural decisions rather than polishing résumés. It recommends founders evaluate candidates through GitHub repositories, revert tests, scenario-based questions, and proof of risk-aware thinking.
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Video
TechWorld with Nana·19w
From Non IT to Lead DevOps Engineer | The Exact Roadmap
A civil engineer from Nigeria transitioned to a Lead DevOps Engineer role in the UK within 9 months through structured learning, strategic career planning, and hands-on practice. Starting with zero IT experience while working retail night shifts and facing visa pressure, he chose DevOps for its high salary threshold enabling visa sponsorship. After scattered learning attempts, he enrolled in a structured DevOps bootcamp, passed the CKA certification, and built comprehensive projects demonstrating integrated tool knowledge. His deep conceptual understanding of CI/CD optimization, Docker layer caching, and Kubernetes fundamentals helped him excel in technical interviews. He negotiated between two offers, choosing the role with modern tech stack (Kubernetes, Terraform, Ansible) over legacy tools, resulting in 25% higher salary. On the job, he immediately added value by building production Kubernetes clusters from scratch and implementing security scanning pipelines, earning a 10% raise within his first year.
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