Matthias Endler·42wHow To Review Code
A comprehensive guide to effective code reviewing based on two decades of experience. Emphasizes focusing on big picture design over syntax, the critical importance of good naming, being decisive when rejecting changes, and treating reviews as iterative communication processes. Key principles include running code locally when possible, asking clarifying questions, avoiding nitpicking on formatting, and continuously learning from the review process.
The Serious CTO·40wFrom Burned-Out Junior Dev to CTO in 2 Years – The No-BS Guide They Don’t Teach You
A seasoned tech leader shares unconventional advice for rapidly advancing from junior developer to CTO, emphasizing systems thinking over coding skills, business communication, and visible impact over technical perfection. The guide challenges common career advice by focusing on leadership and decision-making rather than pure technical expertise.
Simple Thread·41wUnnecessary Anxiety in Software Development
Software development often creates unnecessary anxiety through risky practices like deploying without proper safeguards. Using a metaphor of walking across a plank between buildings, the author explains how anxiety is self-reinforcing and leads to avoidance behaviors. Organizations can reduce developer stress by implementing better testing, staging environments, documentation, and blameless cultures. Individuals can combat anxiety by approaching feared tasks, building competence, and accepting discomfort as part of growth. The key is lowering both the likelihood of failure and its consequences.
The Developing Dev·38wStripe CTO on What Grew His Career, Hiring Without Leetcode, Coding as a Leader (Career Story)
Former Stripe CTO David Singleton shares insights from his journey from junior engineer to VP at Google and CTO at Stripe. He discusses the transition from IC to management, the importance of engineering leaders staying technical through practices like 'engineer-acation', hiring without leetcode interviews, and building effective engineering organizations. Key topics include managing managers, scaling teams, communication strategies for leaders, and making career decisions based on personal fulfillment rather than just advancement.
Manager.dev·41wThe best time to be an Engineering Manager is now
Engineering managers are positioned for success in an AI-driven future because their core value lies beyond coding. While AI agents may handle mid-level programming tasks, EMs excel in three critical areas: understanding business requirements and bridging technical-business gaps, defining clear technical solutions and requirements, and managing complex interpersonal relationships. These skills become more valuable as companies still need humans to guide AI agents, handle incidents, and navigate organizational dynamics. The key advice is for EMs to maintain current coding skills alongside their management expertise.
DEV·38wFrom Mid-Level to Senior: Why I Built a Product Thinking Simulator
A mid-level engineer shares their realization that advancing to senior roles requires more than technical skills—it demands product thinking. They built a Product Thinking Simulator, an interactive tool with story-driven scenarios that help engineers practice making strategic decisions about shipping vs. quality, technical debt, and user experience trade-offs.
The Pragmatic Engineer·40wNew trend: extreme hours at AI startups
AI startups are increasingly adopting extreme work cultures requiring 80+ hour weeks, similar to China's "996" pattern. Companies like Cognition, Lovable, and xAI justify these demanding schedules as necessary to achieve AGI quickly before competitors. The promise of generational wealth through equity motivates employees to accept these conditions, as seen with Windsurf's acquisition by Google. However, long hours don't guarantee success, and this trend may persist due to intense competition and FOMO in the AI industry.
Stack Overflow Blog·40wDocuments: The architect’s programming language
Software architects differ from senior developers by knowing how to deploy ideas to systems made of people, not just code to systems made of machines. The key skill is effective technical writing using documentation tools like Confluence or Notion. Good documents use bullet points for clarity, headers for organization, and chronological rather than topical structure. Essential document types include architecture overviews, dev designs, project proposals, developer forecasts, technology menus, problem statements, and postmortems. Each serves to orchestrate ideas across teams and stakeholders, enabling architects to drive consensus and decision-making at scale.
Tech Lead Digest·40wThe Politics of Software
Office politics are inevitable in any workplace because they emerge from human relationships and resource competition. The author argues that people who complain about politics often contribute to it themselves. Politics increase with seniority due to harder-to-measure outcomes, limited senior positions, and people-focused challenges. Organizations can reduce politics through explicit metrics, abundant resources, and leadership behaviors that discourage political maneuvering. Examples from Facebook, Microsoft, and Valve illustrate how company structure affects political dynamics.
FREEK.DEV·39wAn engineer's perspective on hiring
The current hiring process for software engineers is fundamentally broken, wasting valuable time for both candidates and companies while failing to effectively distinguish between genuinely skilled developers and those relying on AI assistance. The traditional interview methods need significant reform to address these modern challenges and create a more efficient, accurate evaluation system.
Linear·41wQuality Wednesdays: How we trained our team to see what doesn’t work
Linear's engineering team developed Quality Wednesdays, a weekly practice where engineers identify and fix small UI/UX imperfections during team meetings. Starting from a 2023 offsite exercise that revealed how different team members notice different quality issues, this ritual has resulted in over 1,000 small improvements. The practice emphasizes making quality a habit through consistent, time-boxed fixes (30 minutes to 1 hour) that collectively enhance the product experience and train developers to catch issues before they ship.
Tech Lead Digest·42wLeading your engineers towards an AI-assisted future
A comprehensive strategy for engineering leaders to guide their teams through AI adoption in software development. The approach centers on three phases: experimentation, adoption, and impact measurement, using aligned autonomy principles. Key elements include establishing clear metrics for tracking progress, providing organizational support through training and communities of practice, and addressing engineer concerns about AI's impact on their roles. The strategy emphasizes finding a middle path between AI enthusiasm and skepticism, ensuring teams understand both capabilities and limitations of AI coding tools.
Ars Technica·38wZuckerberg’s AI hires disrupt Meta with swift exits and threats to leave
Meta faces internal disruption as newly hired AI executives, including OpenAI's ChatGPT co-creator Shengjia Zhao, threaten to quit shortly after joining. Zuckerberg is conducting Meta's biggest leadership reorganization in 20 years, bringing in high-profile AI talent like former Scale AI CEO Alexandr Wang and former GitHub chief Nat Friedman. However, several new AI hires have already left after brief tenures, highlighting the challenges of integrating external talent into Meta's culture while competing in the AI race.
Tech Lead Digest·39wManaging engineers more experienced than you
New engineering managers often struggle when managing highly experienced engineers, making three common mistakes: trying to compete technically with their team members, giving them complete autonomy without any guidance, and avoiding feedback out of fear. The solution involves accepting your role as a complement to their technical skills, providing structured support through periodic check-ins and clear expectations, and consistently offering feedback focused on broader impact and growth opportunities. Success comes from partnering with experienced engineers rather than competing with them.
Stay SaaSy·39wYou Know What To Do
Experienced professionals with business context usually know the right decision to make but avoid taking action due to discomfort with confrontation. Common difficult decisions include firing executives, conducting layoffs, cutting products, or shutting down businesses. The key is to lean into discomfort, gather feedback from people close to the problem, and avoid over-relying on data analysis that delays obvious decisions. Leaders owe their teams decisive action rather than paralysis from fear of making wrong choices.
swizec.com·39wYes it's like spinning plates
Software engineering in fast-growing companies resembles spinning plates, where engineers constantly move from one urgent issue to another. The key is prioritizing problems, building solutions that survive the next few months rather than perfect systems, and finding balance between shallow quick fixes and deep solutions that could slow business progress. Success comes from having a rough vision of the future while solving today's problems first, allowing small fixes to compound toward better software over time.
Code Like A Girl·41wAI Won’t Take Your Job. Bad Leadership Will.
AI integration in the workplace is already happening, not a future concern. By 2030, 40% of current skills will be outdated, but the real threat isn't AI replacing jobs—it's poor leadership failing to adapt. Organizations focusing only on AI tools miss the point; success requires developing human skills like critical thinking, ethical reasoning, and leading through uncertainty. Design roles will evolve from pixel-pushing to problem framing and value creation. The next five years will see AI becoming a collaborative teammate, with outcomes depending on whether leaders build cultures that grow talent or simply chase efficiency metrics.
Chief Suffering Officer·39wOver communication
A discussion about whether over-communication can harm software projects. The author argues that projects fail more often from wrong assumptions than excessive communication, while acknowledging concerns that too much communication might create noise that obscures important signals for engineers.
Justin Searls·39wAI is exposing order-takers
AI tools are revealing a fundamental divide in the workforce between those who can creatively leverage new capabilities and those who lack the imagination to utilize powerful tools effectively. The issue isn't resistance to AI adoption, but rather the inability of some professionals to envision meaningful applications for these transformative technologies.
The Register·41wThe plan for Linux after Linus? A work in progress
Linux kernel development faces an uncertain future regarding leadership succession after Linus Torvalds. While Torvalds believes natural succession will occur through community trust and existing maintainers, the project lacks formal succession planning. Key challenges include overworked maintainers doing unpaid work, commercial pressures from companies like Red Hat, resistance to innovation like Rust adoption, and increasing bug reports from AI tools. The kernel's remarkable stability and global impact make succession planning critical, as hope alone isn't sufficient strategy for such a foundational technology.
