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ProgrammingDEV Community ·

Four Canadian Provinces Drop DST in 2026, Threatening Scheduler and Timezone Systems

Starting November 1, 2026, British Columbia, Alberta, the Northwest Territories, and Manitoba will stop observing daylight saving time, opting instead for permanent standard time offsets. The four provinces announced their decisions at different times, with Manitoba giving only six weeks' notice before the change — far short of the one year the tz database project requests for smooth propagation. The tz database, which underpins timezone handling across most operating systems and programming languages, has already incorporated three of the four regions in its latest release, with a further update pending. Software systems relying on OS-level tzdata packages, language runtimes, or embedded timezone libraries will all need timely updates to avoid scheduling errors. The disruption is not unprecedented — since 2020, 26 of 31 tz releases have altered future timestamps, with frequent last-minute changes from countries like Palestine, Morocco, Lebanon, and Mexico highlighting the ongoing fragility of global timezone management.

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ProgrammingDEV Community ·

Developer Shares Linux Essentials Learnings from Akwannya Hub Course

A developer participating in Akwannya Hub's Linux Essentials course shared a weekly recap of topics covered across core Linux concepts. The course covered system architecture fundamentals including the Linux file system hierarchy, open-source licensing models, and key networking services such as DNS, DHCP, and LDAP. Participants also explored shell environments, package management differences between Debian and Red Hat distributions, and several programming and scripting languages used in Linux ecosystems. Security best practices — including two-factor authentication, VPN usage, and root account restrictions — were also part of the curriculum. The course concluded with an overview of cloud deployment models, virtualization technologies, and container orchestration tools like Docker and Kubernetes.

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ProgrammingDEV Community ·

New C Code Scoring Tool Flags Risky Functions Using Nesting and Pointer Depth

A lightweight open-source tool called c-code-score assigns a single risk score to C functions based on three factors: nesting depth, pointer depth, and dereference chain length. The score is calculated by multiplying these three metrics, aiming to highlight functions most prone to memory bugs and null-pointer errors. When tested against real-world projects like libXt and libtiff, the score correlated with maintenance churn at rates of 0.52 and 0.38 respectively, outperforming both raw line count and cyclomatic complexity. The tool also works as a feedback loop for LLM-generated C code, allowing developers to iteratively prompt rewrites until scores improve. It is available via pip and requires no external dependencies or complex parsing infrastructure.

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ProgrammingDEV Community ·

Developer builds rule-based crypto wallet classifier to test on-chain label readability

A developer created a browser-based card game called LabelMe to explore how much of a crypto wallet's classification can be inferred from raw on-chain numbers alone. The project uses ten real Ethereum wallets, each displaying four Nansen-computed metrics — PnL, top trades, balance profile, and counterparty mix — and asks players to assign one of five labels: Smart Money, Exchange, Whale, Contract/Pool, or Regular. Answer keys are derived directly from Nansen API calls rather than the developer's own judgment, making the ground truth as objective as possible. Alongside the game, the developer wrote a minimal threshold-based rule reader — no machine learning model involved — to determine how accurately simple numeric rules can replicate Nansen's labeling. The experiment found that activity volume and token diversity were stronger signals for Smart Money classification than win rate or realized PnL.

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ProgrammingDEV Community ·

Modular Architecture Offers a Simpler Path to Scaling Large Next.js Apps

As Next.js applications grow, codebases often become difficult to maintain, with features scattered across hundreds of files and multiple teams conflicting over the same code. Common scaling solutions like Multi-Zones and microfrontends address the problem by splitting the application into separate deployable units, but introduce significant operational overhead and do not fix the underlying code organisation issue. Modular architecture, familiar from frameworks like Nuxt and NestJS, instead splits code by feature within a single app, keeping all logic for a given feature in one self-contained folder. A developer has built an open-source package called next-modular to bring this pattern natively to Next.js, allowing each feature module to plug into the app through a single configuration entry. The approach aims to improve maintainability, debuggability, and code reuse without the complexity of running and coordinating multiple independent applications.

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ProgrammingHacker News ·

Study argues LLMs use cold-reading tricks similar to psychic cons

A new analysis published on softwarecrisis.dev draws parallels between how chat-based large language models respond and the deceptive techniques used by psychics and mentalists. The piece argues that LLMs, like cold readers, generate responses that feel personally accurate by using vague, statistically likely statements. This creates an illusion of deep understanding or knowledge when the system is largely pattern-matching and inferring from context. The author suggests users may be misled into overestimating AI capabilities due to these psychic-style conversational dynamics. The article sparked discussion on Hacker News, signaling growing interest in critically examining how LLM outputs are perceived and trusted.

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ProgrammingHacker News ·

Researchers Propose a Set of Grand Unsolved Problems for Biology

A new initiative has outlined a collection of fundamental unsolved problems in biology, drawing inspiration from the famous Millennium Prize Problems in mathematics. The project, hosted at millenniumproblems.bio, aims to define the field's most pressing and deep scientific challenges. The effort has sparked discussion in the scientific and tech communities, including on Hacker News. By framing biology's open questions in a structured way, the initiative hopes to guide future research priorities. The project reflects a growing interest in bringing greater clarity and ambition to biological sciences.

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ProgrammingDEV Community ·

How to Retrofit Spring Security Into a Legacy Internal App When VPN Access Ends

A software developer has published a detailed guide on adding Spring Security to an existing Java Spring Boot application that previously relied solely on VPN-based network access for protection. The article addresses a common real-world scenario where internal business tools — such as accounting systems and admin panels — must handle authentication and authorization as remote and external access needs grow. Using a demonstration financial accounting system built on Java 21 and Spring Boot 3.5, the author walks through retrofitting security onto a live, publicly accessible app with a fabricated but structurally realistic dataset. The guide deliberately recreates actual bugs encountered during a parallel work project, allowing readers to trace each flaw from cause to fix using published code on GitHub. It is aimed at beginner and mid-level developers who have basic Spring Security experience but have not yet tackled row-level or role-based data authorization.

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ProgrammingDEV Community ·

How to Set Up an Isolated Cybersecurity Home Lab Using Kali Linux and Ubuntu

Security researcher Elijah Abolaji has published a step-by-step guide for building a self-contained cybersecurity home lab on a personal computer. The lab uses two virtual machines — Kali Linux as the attacker and Ubuntu Server as a deliberately vulnerable target — connected on an isolated network with no access to the internet or home Wi-Fi. The setup allows users to practice real penetration testing techniques, including scanning, exploitation, and defense, without risking harm to live systems. The guide recommends a minimum of a 4-core processor, 16GB RAM, and SSD storage, and uses VirtualBox as the virtualization platform. Abolaji stresses that all tools demonstrated are dual-use and that running them against systems without explicit authorization is illegal in most jurisdictions.

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ProgrammingDEV Community ·

Why 'Supported' Linux Doesn't Always Mean 'Secure': The ELS Vulnerability Gap

Enterprise Linux servers under Extended or Maintenance Support are often flagged with dozens of vulnerabilities by scanners, sparking disputes between security and application teams. The core issue is that 'vendor support' does not guarantee uniform security updates across all packages, releases, or architectures. Many enterprise Linux vendors, including Red Hat and Canonical, backport security fixes into older package versions, meaning an outdated-looking version number does not automatically confirm a system is vulnerable. Vulnerability scanners that compare installed versions against upstream releases can therefore produce misleading results in these environments. Organizations running aging systems face compounding challenges — high application dependency, low change tolerance, and shrinking patch coverage — making risk-based vulnerability assessment essential rather than relying solely on scanner output.

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ProgrammingDEV Community ·

Default SSH cipher capped SFTP speeds at 1.2 MB/s until a one-line config fix

Developers at Termphin discovered that every SFTP file transfer was locked at exactly 1.2 MB/s regardless of server, network, or file size. Investigation revealed the culprit was AES-GCM, the default cipher in the dartssh2 library, which relies on hardware acceleration unavailable in pure Dart environments. Without CPU-level AES and carry-less multiplication instructions, GCM's authentication component (GHASH) ran entirely in software, bottlenecking throughput. Benchmarks showed chacha20-poly1305 achieving 51 MB/s versus AES-256-GCM's 1.2 MB/s — a roughly 43x difference. The fix was to override the library's default cipher order, placing chacha20-poly1305 first and demoting AES-GCM to a last-resort fallback.

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ProgrammingDEV Community ·

Firefox Smart Window Pairs With Mistral AI, Prioritizing Privacy Over Automation

Mozilla and Mistral announced on September 16, 2026, that Firefox Smart Window, Mozilla's in-browser AI assistant, is now powered by Mistral's models for users in the US, Canada, and France. Unlike agent-mode rivals such as ChatGPT Atlas and Perplexity's Comet, Smart Window does not fill forms, click links, or act autonomously on a user's behalf. Its features are limited to answering questions with cited sources, grouping browser tabs, and surfacing visual previews of previously visited pages. Mozilla has committed that conversations are not stored on its servers by default, Mistral applies zero data retention for the integration, and no personal data will be sold or used to train models. The feature is opt-in, with users controlling which tabs and history the assistant can access, and it can be disabled entirely through Firefox's AI Controls.

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ProgrammingDEV Community ·

Google's TPU Shortage Is a Resource Authority Problem, Not Just a Supply Gap

Alphabet CFO Anat Ashkenazi has acknowledged that Google is operating in a supply-constrained environment, with TPU shortages traced to a limited number of high-bandwidth memory manufacturers rather than internal mismanagement. DeepMind CEO Demis Hassabis confirmed the bottleneck is industry-wide and rooted in physical component availability. With demand from internal teams, Cloud customers, and frontier AI research all competing for finite compute, Google was forced to establish an explicit allocation hierarchy. CEO Sundar Pichai publicly stated that frontier AGI work takes priority, with Cloud, Search, and YouTube sharing the remainder. The situation highlights that when every demand signal is legitimate but supply still falls short, the critical question becomes who holds the authority to decide where compute goes.

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ProgrammingDEV Community ·

APC Spec Rule: Unknown .apc/ Files Must Not Be Treated as Agent Instructions

The APC folder structure specification requires that consumers ignore any .apc/ paths not formally defined by APC or an approved extension, preventing unrecognised files from being silently treated as agent instructions. This rule matters because different tools handle unknown files differently — one may ignore them while another feeds every Markdown file in the directory to its agent, causing inconsistent behaviour across the same codebase. A file's location inside .apc/ alone does not grant it semantic authority; a consumer must be able to identify what a path means before acting on it. Teams wanting to make instructions universally applicable should place them in AGENTS.md, or use defined paths such as .apc/rules/ or .apc/skills/ for scoped rules and callable procedures. Sensitive data like credentials or runtime caches should never be stored in .apc/, as the unknown-path ignore rule is a parsing convention, not a privacy safeguard.

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ProgrammingDEV Community ·

AI Coding Models in 2026: A Budget-by-Budget Breakdown for Developers

A detailed comparison of AI coding models in 2026 groups them into three tiers — premium, workhorse, and budget — based on task complexity, usage frequency, and accuracy requirements. Premium models like Claude Opus 4.8 and GPT-5.6 Sol cost around $0.18–$0.23 per session, suited for complex refactoring and autonomous agent workflows. Mid-tier options such as Grok 4.5 and Claude Sonnet 4.6 offer strong performance at roughly $0.04–$0.05 per session, making them practical for daily development work. Budget models led by DeepSeek V4 Chat cost as little as $0.001 per session, delivering competitive code quality at up to 170 times lower cost than top-tier alternatives. GitHub Copilot offers a separate flat-rate path, ranging from $10 to $99 per month depending on team size and enterprise needs.

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ProgrammingDEV Community ·

Why AI Agents Need Defined 'Lanes' to Function as Real Employees

Most AI tools behave like reactive assistants — responding to prompts and waiting — rather than autonomous employees capable of owning ongoing work. A developer essay argues that turning an AI agent into a true worker requires more than better prompts or additional tools. The missing element is a 'lane': a structured combination of persistent memory, trusted context, scheduled triggers, permitted actions, and clear escalation rules. Without these guardrails, an AI agent can complete isolated tasks but lacks the continuity and accountability needed for genuine ownership. The piece outlines five properties of a well-defined lane — clear outcome, recurring cadence, known inputs, allowed actions, and hard stops — and argues that bounded autonomy is what separates a capable AI employee from an impressive demo.

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ProgrammingDEV Community ·

Cache and Hash AI Prompts Locally to Cut Latency and Prevent Secret Leaks

A software development guide recommends hashing AI coding prompts and associated file sets locally before sending them to any remote model server. The approach stores prompt drafts in a local cache directory tied to the current git commit, only making a network request when no valid cached result exists. A lightweight Python script scans prompts for secret patterns — such as private keys or API tokens — and blocks the network hop entirely if any are detected. The method prioritizes three checks before using a remote server: acceptable latency, absence of secrets, and online availability. The article was published as part of outreach for MonkeyCode, which offers free remote model access, though the technique is presented as server-agnostic.

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ProgrammingDEV Community ·

LangGraph, CrewAI, and AutoGen: How the Top Multi-Agent AI Frameworks Compare in 2026

By 2026, multi-agent AI orchestration has become mainstream, with over 70% of new AI projects using such frameworks and the agentic AI market valued at $7.38 billion, according to Zylos Research. LangGraph, built by the LangChain team, leads in performance with the lowest latency and token usage, offering fine-grained control through a graph-based workflow model, and is already used in production by companies like Klarna, Uber, and LinkedIn. CrewAI takes a more accessible, role-based approach that allows developers to build working multi-agent systems in under 20 lines of Python, though it sacrifices fine-grained control and is often used for prototyping before teams migrate to more robust frameworks. Microsoft's AutoGen, restructured as AG2 from version 0.4 onward, uses a conversation-driven model suited for iterative tasks like code review and research, but comes at the cost of high token consumption. Each framework serves distinct use cases: LangGraph for production-grade control, CrewAI for rapid development, and AutoGen for dialogue-heavy, iterative workflows.

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ProgrammingDEV Community ·

85-Minute Workshop Teaches Developers to Detect Silent AI Host Drift Early

A structured 85-minute workshop guides developers in building a five-probe floor card to detect silent capability loss in shared AI inference hosts. The method freezes a small set of inputs, a deterministic scorer, and a stored baseline so that results from different runs can be meaningfully compared. Participants leave with a portable JSON probe pack, a local scoring script, and a pass-or-fail ledger that can be re-run after any host or prompt change. The workshop is deliberately narrow in scope, focusing on a single task and JSON contract rather than broad model benchmarking or production quality rankings. It is designed for teams that lack a formal versioned evaluation platform and need a lightweight, repeatable way to catch regressions before they go unnoticed.

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ProgrammingDEV Community ·

DeepSeek Releases DSH: An Open Agent Framework Built Entirely from Plugins

DeepSeek AI has released DeepSeek Harness (dsh), an open-source agent framework where every component — including session storage, sandboxing, context compression, and the model itself — is implemented as a swappable plugin. The system is built on the Cordis runtime and uses a layered patch architecture, allowing users to assemble agent behavior from bundles rather than monolithic code. Different runtime profiles (web, headless, SDK, ACP) let the same tool serve local interfaces, CI pipelines, or code editors without changing flags. DSH supports multiple sub-agent orchestration patterns, including background agents, context-inheriting agents, JavaScript-driven workflows, and looped task runners with persistent working directories. All tool calls, file changes, and state transitions are written to a structured log, giving teams full visibility into agent behavior and making the framework auditable by design.

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