Why Laravel Sanctum Sessions Break in Nuxt SSR and How to Fix It

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When using Laravel Sanctum's SPA cookie authentication with a Nuxt frontend, authenticated requests succeed in the browser but return 401 errors during server-side rendering. This happens because Nuxt's SSR runs inside a Node/Nitro server process that has no cookie jar, no Origin header, and no browser context to attach session cookies automatically. The fix requires manually forwarding the incoming request's cookie and origin headers to outbound server-side API calls using Nuxt's useRequestHeaders utility. Additionally, the API base URL must differ by environment, since internal server processes often cannot reach public-facing addresses like localhost or external domains. State-changing requests also require proper CSRF handling by reading the XSRF-TOKEN cookie and echoing it in the X-XSRF-TOKEN request header.

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Six weeks of AI agent payment data reveals 5 endpoints drive 69% of revenue

A developer running NetIntel, a pay-per-call API platform settled in USDC on Base and Solana, analyzed 2,646 real on-chain payments from 194 distinct wallets across 101 endpoints over six weeks. Just five endpoints generated 69% of total revenue, with a single text-to-structured-JSON endpoint accounting for 42% — almost entirely driven by one automated wallet running a daily workflow. When the developer doubled that endpoint's price mid-month, the buyer did not pause once, suggesting embedded agent workflows are highly price-insensitive. Notably, 35 of the 101 endpoints have never received a single paid call, including technically complex network-intelligence tools the developer considered his strongest work. The data suggests AI agents prioritize paying for data transformation — converting messy text into guaranteed clean structure — over raw data access, as structured output reduces downstream token costs and error handling.

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ProgrammingDEV Community ·

AI Code Generation Is Making Security the New Crisis in DevOps

The widespread adoption of Large Language Models in software development is fundamentally reshaping the threat landscape for DevOps teams, shifting the primary concern from scaling to security. AI tools can generate hundreds of lines of code in seconds, effectively bypassing traditional manual code review processes that many organizations rely on as a last line of defense. A key technical vulnerability stems from the 'context window' limitation of LLMs, which causes AI agents to optimize code locally without understanding broader system architecture, potentially introducing race conditions, authorization bypasses, or data inconsistencies. This fragmented code generation leads to a phenomenon called semantic drift, where iterative AI-driven refactoring subtly alters the original intent of code in ways that evade standard static and dynamic testing. Experts argue that managing this exponential rise in code complexity and embedded vulnerabilities demands a complete overhaul of existing security postures rather than incremental improvements to current DevOps infrastructure.

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ProgrammingDEV Community ·

How to Build a Text Summarizer Using Hugging Face Transformers in Python

A tutorial published on DEV Community walks developers through building a functional text summarizer using Hugging Face's Transformers library and Python. The guide leverages the pipeline API, which simplifies the process by handling tokenization, model loading, and output decoding with minimal code. It recommends Facebook's BART model trained on the CNN/DailyMail dataset as the go-to choice for general-purpose summarization due to its accuracy and ease of use. Other models such as Google's Pegasus and T5-small are also mentioned as alternatives with different trade-offs in conciseness and flexibility. The tutorial is aimed at developers who want to integrate NLP summarization features quickly without deep expertise in machine learning.

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ProgrammingDEV Community ·

Python Developers Can Now Build Shopify Apps Without Node.js or React

A new tutorial published on DEV Community demonstrates how Python developers can build production-ready Shopify apps using Flask and the shopify Python package, without relying on JavaScript frameworks. Shopify's official tooling typically favors Node.js, Rails, or React, but since the platform's API is HTTP-based, any language capable of making HTTP requests and handling webhooks can integrate with it. The guide walks developers through setting up a Python 3.9+ environment, installing dependencies like Flask and shopifyapi, and configuring credentials via a Partner Dashboard app. Because Shopify does not offer an official Python SDK for app scaffolding, developers must implement OAuth authentication and webhook handling manually. The tutorial covers use cases ranging from inventory automation to storefront customization and analytics backends.

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