The career stories enterprise IT pros actually read.
Volume 342, Issue 4 · 7 articles from 2 issues
Job hunting success requires a personal philosophy focused on demonstrating capability rather than gaming systems.
Nick Corcodilos argues that effective job hunting centers on understanding and performing the actual work, not navigating automated systems or following industry conventions.
He critiques personnel jockeys who automate hiring processes and advocates adopting headhunter strategies: target specific companies, build your reputation beforehand, and treat interviews as collaborative problem-solving rather than interrogations.
The core principle is positioning yourself as the solution to a manager's specific business problem.
AI will transform enterprise architecture roles rather than eliminate them, shifting focus to governance.
Enterprise architecture faces disruption as AI automates artifact production like diagrams, standards, and documentation.
However, architects will become increasingly valuable as curators of enterprise knowledge, stewards of governance, and designers of control mechanisms for autonomous systems.
The profession will evolve from document creation toward establishing trusted context, managing decision rights, and ensuring organizational accountability in AI-driven environments. Architects who thrive will spend less time maintaining documentation and more time addressing policy, risk, and strategic trade-offs.
As AI automates code writing, software development transforms into product engineering focused on customer needs.
The author argues that AI agents will soon automate most technical aspects of software development, including coding, reviewing, maintaining, and operations, leaving product definition as the core remaining job.
The market is already hiring forward deployed engineers and similar roles at senior pay ($240K+) to understand customer problems and specify solutions.
However, the profession lacks training pipelines for these skills, creating a ten-year transition period where demand vastly outpaces supply of people who can extract requirements, define quality, and exercise taste in software design.
Forrester and experts argue AI will transform, not eliminate, the enterprise architect role by shifting it toward governance.
Forrester analysts argue AI will not eliminate enterprise architecture but will fundamentally transform the profession, according to this Holt Hackney piece.
AI can now automate artifact production such as diagrams, documentation, and standards, work that previously took weeks, so enterprise architects are shifting toward governance, judgment, and managing context instead.
The role evolves into establishing guardrails and decision rights for autonomous AI agents. Experts agree that as AI agents increasingly make technology and business decisions in real time, periodic reviews become obsolete, requiring architects to build machine-consumable architecture knowledge and continuous governance layers that guide AI decisions within defined boundaries.
A guide to spotting your career strengths and applying them daily to accelerate professional growth.
The article explains that career strengths combine natural ability with consistent results, and suggests three ways to spot them: notice what comes easily, observe what colleagues ask for help with, and recall moments your work created measurable value.
It cites Gallup research finding professionals who use their strengths daily are six times more likely to feel engaged at work.
The piece stresses that a strength rarely used at work will not help a career grow, however talented someone is at it, and recommends building visibility by consistently applying strengths to projects with tangible outcomes.
CS students need core programming, AI literacy, cloud, and cybersecurity skills to build a resilient tech career.
Computer science students need foundational programming expertise in languages like Python, TypeScript, and Java, combined with strong data structures and algorithms knowledge.
Modern tech roles increasingly demand AI literacy, with 84% of respondents reportedly using or planning to use AI tools in development, though critical evaluation of AI output remains essential. Practical competencies in software development, cloud platforms (AWS, Azure, GCP), databases, and cybersecurity have become industry standard requirements.
The article, by Pardeep Sharma, notes that successful careers combine core CS fundamentals with specialized depth in AI, software engineering, DevOps, or data engineering, and that employers value both technical depth and adaptability to emerging technologies.
AI is reshaping data centre jobs, automating routine tasks while creating new automation and AI-infrastructure roles.
The data centre sector is growing about 14% annually through 2030, with 86% of operators expanding capacity mainly for AI workloads, intensifying competition for talent.
Rather than eliminating jobs, AI is redistributing work: maintenance teams move from reactive repairs to proactive, predictive monitoring, and security staff now interpret AI-flagged threats instead of manually hunting them.
New roles such as automation engineers and AI infrastructure specialists are emerging, along with hybrid positions blending operations and sustainability expertise.
The article concludes that professionals who combine traditional data centre skills with AI literacy will be best positioned to thrive.