Short, useful summaries of coding, AI, and education news, with a practical next step for learners.
A frontend interview in 2026 is described as five stages: recruiter screen, technical screen, coding round, frontend system design, and behavioral round. The excerpt says the coding round is the most variable, and candidates should ask recruiters to confirm the format in writing. It also says AI use in interviews now depends on each company’s policy.
The excerpt explains that automation has long helped software handle routine work, and AI has made those systems smarter. It says the article will define AI automation and show how to implement it with real examples from teams already using it.
The excerpt says that simply using ChatGPT for one-off prompts is not the same as integrating AI into a company's work. AI workflow automation means building AI into repeatable processes so tasks can be handled more consistently and at scale. It is presented as a way to get more efficiency than ad hoc prompting.
Sal Khan says schools that use technology well succeed because of teachers, administrators, and other hard-to-copy conditions, not technology alone. He argues that overrating the tech can create unrealistic expectations and distract from what is needed to help more classrooms benefit. His goal is to use technology to let students learn at their own pace while freeing class time for human interaction.
Students are already using AI for schoolwork, often to summarize material, get unstuck, and brainstorm. The excerpt says Study and Learn in Microsoft 365 Copilot is built to support active learning rather than just give quick answers, and it discusses how institutions are responding to student AI use. Some schools have limited AI, but that may leave students using unmanaged tools elsewhere.
Python’s __all__ variable controls what gets imported when someone uses a wildcard import, like from module import *. It also helps define which names a module or package presents as part of its public API.
This quiz checks your understanding of wildcard imports in Python, the special __all__ variable, and how modules and packages control which names are public. It focuses on how import behavior affects what users see and access.
The Raspberry Pi Foundation hosted the 22nd Bebras International Task Workshop in Cambridge, bringing together organisers, educators, and researchers to review computational thinking tasks for upcoming national Bebras Challenges. Delegates from 61 countries discussed wording, illustrations, age suitability, accessibility, and the thinking skills involved. Out of 277 submitted tasks, 214 were accepted.
Agent skills are described as reusable tricks that teach an AI agent how to do specific tasks more reliably. The excerpt compares them to a trained dog learning expected actions, so the agent can follow a skill without being prompted from scratch each time.
A high school student in New Jersey created a free economics program for middle schoolers, using AI-built simulations based on sports. Students make decisions like managing payroll, handling salary caps, drafting players, and setting ticket prices while learning concepts such as incentives, scarcity, risk, and opportunity cost. The classes mix slide lessons, discussion, and interactive games.
A 31-year-old graphic designer began with HTML and CSS, then used those skills to make custom WordPress changes. She continued with a front-end program to expand what she could do in her existing role rather than treating coding as an all-or-nothing career switch.
This quiz explores how to work with Excel files in Python using openpyxl. It covers reading and writing cell values, using formulas, and adding styling, charts, and images.
This learning path introduces FastAPI from the basics. It covers building REST APIs, serving web pages with Jinja2 templates, and creating a complete URL shortener project in Python.
The excerpt argues that simplifying texts for students can weaken the reading experience and reduce the effortful thinking that helps them learn. It says some schools once praised an AI tool for leveling text, but the author warns that this shortcut can do the thinking for students instead of helping them access complex texts. It also notes that many states are moving away from text-leveling programs.
This article introduces Python’s built-in functions for working with math, data types, iterables, and input/output. It also explains when to use each one to write code that feels more natural in Python.
This quiz checks your knowledge of Python’s built-in functions for math, data types, iterables, and input/output. It also helps you learn when to use each function.
The excerpt says AI is becoming a business capability across many sectors, but many organisations still struggle to move beyond experiments. It argues that success depends less on technical tools and more on an AI mindset: curiosity, critical thinking, strategic use, responsible implementation, and change management.