The author argues that AI has increased, rather than erased, the value junior engineers can provide by expanding the complexity they can manage. In one example, an intern led delivery of a long-requested product feature that had not cleared prioritization thresholds: the intern gathered requirements from a product manager, wrote and aligned a design document, adapted to technical and product trade-offs, and built the feature with AI and team support. AI generated much of the code, while the intern owned the decisions. The author contends that engineering work extends beyond implementing specifications or prompting AI tools. Engineers at different levels solve customer problems while managing different amounts of technical complexity, including requirements, customer context, and trade-offs that may depend on information beyond a codebase. The author says junior engineers therefore add organizational capacity, while AI can reduce parts of early-career training previously spent learning languages, tools, patterns, and codebase details. Human-provided organizational context remains necessary, according to the author. The author also argues that engineers who began their careers using AI may be well positioned as they gain experience, and that organizations need to keep developing future technical judgment by hiring and training early-career engineers.

The fast.ai co-founder who helped launch the organization with Jeremy Howard in 2016 has joined Answer.AI to work on AI in education, despite widespread concerns about AI-generated content, overhyped corporate claims, resource use, and the erosion of human skills. The writer left AI in 2023 after burnout and completed an MS in Microbiology-Immunology before returning as public opposition to AI intensified. Answer.AI, which grew out of fast.ai, is developing SolveIt, a tool designed to keep people in control of AI-assisted problem-solving. Users can directly edit the system’s responses and decide their next steps. SolveIt takes its name from George Pólya’s 1945 book, How to Solve It, which divides problem-solving into understanding a problem, devising a plan, carrying it out, and reviewing the result. Its design rejects chatbots that immediately produce finished answers, on the grounds that doing the intervening work helps people understand and evaluate solutions. The writer says AI has contributed to AI-generated student work, low-quality open-source pull requests, degraded online writing, and education products focused on gameable metrics. They argue that OpenAI, Anthropic, Google, and xAI do not define AI’s only possible future, and call for tools that preserve human judgment, creativity, autonomy, collaboration, and awareness of resource constraints.

A professor at Alcorn State University used a hidden white font in an assignment prompt to instruct AI to generate irrelevant responses. This method successfully identified 32 students who attempted to cheat on their midterm exam.

A new AI tutor demonstrated an effect size of 0.71-1.30 standard deviations in improving student performance in a Dartmouth course. The study indicates significant potential for AI-driven educational tools in enhancing learning outcomes.

Roberto Serrano, a professor at Brown University, claims to have overwhelming evidence of widespread cheating using AI among his students. He emphasizes the need for a thorough discussion on the implications of AI technology for academic integrity in higher education.

Norway is implementing a near ban on generative AI tools for elementary school students and restricting their use for older students to mitigate negative impacts on learning. This decision follows a broader initiative to improve education, which includes a smartphone ban in schools and increased teacher authority.

California's public universities invested $16.9 million in AI amid a financial crisis, leading to significant internal turmoil. San Jose State University's president communicated with newly admitted students via an unusual video message.

In July 2025, AI models successfully solved five out of six problems at the International Mathematical Olympiad, surprising mathematicians with their rapid advancement. Despite these impressive results, the impact of AI on research mathematics remains uncertain.

Pope Leo XIV advised priests of the Diocese of Rome to rely on their intellect rather than artificial intelligence when writing homilies. During a private meeting, he emphasized the importance of prayer, study, and fraternity in ministry.

Alpha School, an AI-powered private institution costing up to $65,000 annually, generates faulty lesson plans that can be detrimental to students. The school scrapes data from various online courses without permission to train its AI, according to former employees and internal documents.