Will Larson's "Career Advice in 2025" predicts the evolving job landscape, emphasizing the growing importance of generalist skills alongside specialized expertise. The rise of AI will demand adaptability and a focus on uniquely human capabilities like complex problem-solving, creativity, and communication. Building a strong network, embracing lifelong learning, and demonstrating initiative through personal projects will be crucial for career advancement. Rather than chasing specific job titles, individuals should cultivate transferable skills and seek opportunities to develop a broad understanding of their industry, positioning themselves for a rapidly changing future of work.
Over 50 years in computing, the author reflects on key lessons learned. Technical brilliance isn't enough; clear communication, especially writing, is crucial for impact. Building diverse teams and valuing diverse perspectives leads to richer solutions. Mentorship is a two-way street, enriching both mentor and mentee. Finally, embracing change and continuous learning are essential for navigating the ever-evolving tech landscape, along with maintaining a sense of curiosity and playfulness in work.
HN commenters largely appreciated the author's reflections on his long career in computer science. Several highlighted the importance of his point about the cyclical nature of computer science, with older ideas and technologies often becoming relevant again. Some commenters shared their own anecdotes about witnessing this cycle firsthand, mentioning specific technologies like LISP, Smalltalk, and garbage collection. Others focused on the author's advice about the balance between specializing and maintaining broad knowledge, noting its applicability to various fields. A few also appreciated the humility and candidness of the author in acknowledging the role of luck in his success.
The blog post "The Missing Mentoring Pillar" argues that mentorship focuses too heavily on career advancement and technical skills, neglecting the crucial aspect of personal development. It proposes a third pillar of mentorship, alongside career and technical guidance, focused on helping mentees navigate the emotional and psychological challenges of their field. This includes addressing issues like imposter syndrome, handling criticism, building resilience, and managing stress. By incorporating this "personal" pillar, mentorship becomes more holistic, supporting individuals in developing not just their skills, but also their capacity to thrive in a demanding and often stressful environment. This ultimately leads to more well-rounded, resilient, and successful professionals.
HN commenters generally agree with the article's premise about the importance of explicit mentoring in open source, highlighting how difficult it can be to break into contributing. Some shared personal anecdotes of positive and negative mentoring experiences, emphasizing the impact a good mentor can have. Several suggested concrete ways to improve mentorship, such as structured programs, better documentation, and more welcoming communities. A few questioned the scalability of one-on-one mentoring and proposed alternatives like improved documentation and clearer contribution guidelines. One commenter pointed out the potential for abuse in mentor-mentee relationships, emphasizing the need for clear codes of conduct.
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https://news.ycombinator.com/item?id=43375923
HN commenters largely agreed with the author's premise that specializing in AI/ML while maintaining broad software engineering skills is a strong career strategy. Several pointed out the importance of "engineering out of" AI/ML roles as they become commoditized, emphasizing the ability to adapt. Some debated the long-term viability of "prompt engineering," with skepticism about its longevity as a specialized skill. Others highlighted adjacent areas like data engineering, MLOps, and AI safety as potentially valuable specializations. A few commenters offered alternative perspectives, suggesting that focusing on fundamental computer science principles remains crucial, and that over-specialization in a rapidly evolving field could be risky. There was also discussion around the importance of domain expertise, regardless of the technological landscape.
The Hacker News post titled "Career Advice in 2025" (linking to lethain.com/career-advice-2025/) has generated a moderate number of comments, discussing the original author's advice on navigating a career in tech, particularly in the context of the rise of AI.
Several commenters appreciated the author's emphasis on fundamental skills. One commenter highlighted the timeless value of "clear communication, empathy, systems thinking, and strong execution," agreeing that these skills remain relevant regardless of technological advancements. They also noted the importance of adaptability and the ability to learn quickly as key skills for future-proofing a career.
Another commenter concurred, pointing out that the advice offered was "solid and evergreen," and emphasizing that "being good at the fundamentals" was a key takeaway. They elaborated that even though tools and technologies change rapidly, the underlying principles of problem-solving and critical thinking remain valuable assets.
Some discussion revolved around the balance between specializing in a specific niche versus broadening one's skillset. While acknowledging the appeal of specialization, especially in AI-related fields, some commenters cautioned against over-specialization, arguing that a broader understanding of multiple domains could become even more crucial in a rapidly changing landscape. They suggested that a "T-shaped" approach, combining deep expertise in one area with a broader understanding of related fields, could be a more effective strategy.
One commenter offered a slightly different perspective, focusing on the importance of understanding and leveraging AI tools. They posited that, rather than fearing obsolescence, professionals should learn how to effectively utilize AI as a tool to augment their capabilities and increase productivity.
The topic of personal branding and networking also emerged in the comments. One commenter, identifying as a hiring manager, stressed the importance of building a strong personal brand and maintaining an active network. They suggested that demonstrating passion, enthusiasm, and a commitment to lifelong learning can make a significant difference in career advancement.
Finally, there was some discussion about the specific advice regarding Generative AI. One commenter cautioned against relying too heavily on Generative AI for coding, arguing that it can lead to a decline in fundamental coding skills. They stressed the importance of understanding the underlying principles of programming and algorithms, even when using AI-assisted tools.
In summary, the comments generally reflect a positive reception of the original author's career advice. There's a strong consensus on the enduring value of fundamental skills, adaptability, and continuous learning. The discussion also explores the nuances of specialization versus generalization, the importance of leveraging AI tools effectively, and the continued relevance of personal branding and networking in a tech-driven world.