LinkedIn’s 2026 data shows AI engineering, prompting, and model tuning are the fastest-growing skills, reshaping hiring, salaries, and interview expectations across tech.
This guide compares AI and human mock interviews across feedback quality, realism, repetition, and cost to determine which improves tech interview performance fastest.
In 2026, tech hiring is prioritizing hands-on, performance-based IT certifications over theory exams as employers demand real-world, applied skills.
A detailed comparison of Interview Query and StrataScratch covering SQL practice, mock interviews, pricing, features, and which platform better prepares you for real data science interviews.
Microsoft AI chief Mustafa Suleyman argues rapid advances in AI could automate large portions of white-collar work within two years, though labor market effects may unfold more gradually.
A Guardian investigation reveals that despite AI’s promise of efficiency, startup employees are working longer hours as expectations and competition escalate.
IBM’s plan to hire three times more entry-level workers in 2026 suggests AI may be reshaping, not eliminating, junior tech roles.
A curated guide to 40 data analytics datasets and realistic project ideas that help you build end-to-end, portfolio-ready analyses for analytics interviews.
January 2026 data science hiring shows stabilization across core roles, continued AI-driven growth in ML engineering, selective FAANG demand, and elevated tech layoffs shaping a tighter market.
A UC Berkeley field study suggests AI speeds up individual tasks but often expands scope and expectations, leaving tech workers feeling busier, not freer.
OpenAI’s move toward forward-deployed AI engineers signals a shift from selling AI models to managing AI agents like workers, with major implications for tech hiring.
Microsoft’s push toward AI-driven “vibe coding” promises faster software development, but critics argue it could erode open source and raise the bar for core engineering skills.
