US Toilet Paper Prices Rise as Canada Trade War Triggers Tariff Pressure

·1 views

The United States is experiencing a significant increase in toilet paper prices linked to ongoing trade tensions with Canada. Tariffs imposed as part of the broader US-Canada trade dispute are driving up costs for paper products. Canada is a major supplier of the wood pulp and paper goods that underpin US toilet paper production, making American consumers vulnerable to such trade measures. The price surge reflects wider economic consequences of the prolonged trade conflict between the two neighboring countries.

Read the full story at Hacker News

This is an AI-generated summary. ShortSingh links to the original source for the complete article.

Discussion (0)

Developer Builds NutriApp to Connect Patients with Nutritionists and Health Professionals

A developer has built NutriApp, a study project and health platform designed to connect patients with nutritionists, doctors, and personal trainers, with each user type seeing only the data their role permits. The app is built using React 19, TypeScript, TanStack Start, Tailwind v4, and a Supabase-backed Postgres database with Row Level Security enabled. A key challenge was implementing role-based access control across three core tables, which required custom SECURITY DEFINER functions to prevent policy recursion loops. The platform also automates health profile creation by calculating BMI in real time and generating an initial plan based on the patient's selected goal, reducing manual work for professionals. The developer noted that modeling access roles early in the project and keeping role verification on the backend were among the most important lessons learned.

0 comments Read more at DEV Community

ProgrammingDEV Community ·

Why AI Memory Architecture Is the Next Big Challenge in Logistics

The logistics industry is generating vast amounts of data — from GPS signals and carrier performance to customs records and exception histories — but the core challenge is no longer data access. The emerging question is whether AI systems can retrieve the right information, at the right moment, for the right shipment, while discarding what is irrelevant. Experts are shifting focus from what AI models 'know' to what they can remember, reason about, and act upon over time, particularly as AI agents take on complex operational tasks. Recent enterprise research describes AI memory not as simple chat history, but as a full lifecycle involving ingestion, retrieval, consolidation, and deletion. A raw data lake or vector database alone does not constitute AI memory — true utility comes when a system can dynamically determine which past information is relevant to a current decision.

0 comments Read more at DEV Community

ProgrammingDEV Community ·

How Golden Images Eliminate Manual Server Setup Steps at Scale

A developer shared how repeated manual server setup steps became a bottleneck when managing a fleet of machines that needed to scale on demand. To solve this, they built a tool that connects to a pre-configured machine, packages only the setup-derived configuration files, and uploads a versioned snapshot to storage. Every new server then automatically downloads and applies that snapshot during boot, removing the need for any human intervention. An early mistake involved capturing too much data, including application binaries, which caused new servers to silently revert to older software versions. Narrowing the capture to only the relevant config subfolders resolved the regression and made the golden image complement rather than conflict with the installation process.

0 comments Read more at DEV Community

ProgrammingDEV Community ·

Developer Documents API Learning and Project Planning in Python Full Stack Journey

A developer has shared progress from days 7 and 8 of their Python Full Stack Development learning journey. During this period, they began taking notes on project ideas while simultaneously studying API concepts. The learner explored Software Requirements Specifications (SRS), system architecture, and key features relevant to their upcoming project. Alongside project planning, they also started learning FastAPI, a modern Python web framework for building APIs.

0 comments Read more at DEV Community