Why Android Apps Keep Draining Battery Even When You're Not Using Them

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Android apps can continue consuming battery in the background through mechanisms like WorkManager jobs, foreground services, scheduled alarms, location callbacks, and push message handlers, even when no visible activity is open. The distinction matters because some background work is legitimate — navigation, podcast downloads, and messaging all have valid reasons to run — while other work runs more frequently or longer than necessary. Android's power management features, including Doze mode and App Standby, are designed to batch and defer background tasks to reduce scattered CPU wakeups. However, vendor-specific power management and device state variables mean background behavior on a developer's USB-connected phone can differ significantly from a real user's overnight experience. Developers are advised to question what work was performed and whether it justified the battery cost, rather than bypassing power restrictions through exemptions or exact alarms.

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Why AI Agents Hallucinate Their Own Actions and How to Engineer Around It

AI agents built on the ReAct (Reason + Act) architecture frequently fabricate tool outputs, file paths, and function results — not due to bad prompts but because of a structural flaw in how large language models process their own actions. Since an agent's entire memory of past steps exists only as text tokens in a context window, the model has no verified execution trace to anchor its reasoning. Research indicates hallucination rates can climb from around 5% in single-turn tool use to 20–40% in multi-turn loops exceeding ten steps, as compounding errors reinforce flawed reasoning. The root cause lies in how autoregressive models are optimized for fluency and plausibility rather than factual accuracy, causing them to reconstruct or invent tool responses when outputs are large or ambiguous. Addressing this requires architectural solutions such as sandboxing, verified audit trails, and honest agent design that decouple execution state from the model's interpretive context.

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ProgrammingDEV Community ·

Key Multi-Agent Design Lessons from AutoGen That Still Apply Today

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ProgrammingDEV Community ·

Vaadin Lets Java Developers Build Full Web UIs Without JavaScript Frameworks

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ProgrammingDEV Community ·

Solo Developer Builds 73-Line Script to Guard macOS Automation Schedules from Silent Rewrites

A solo developer discovered in late August 2026 that an unknown process had silently reduced their automated outreach DM jobs from eight daily runs to just three, costing them missed opportunities for several days before they noticed. The developer relies on macOS launchd-scheduled Python scripts to run social media outreach across Instagram, Threads, and YouTube while they sleep, with automation uptime directly tied to their income. Because macOS does not alert users when a plist configuration file is modified, the jobs appeared active in launchctl even though they were running on altered schedules. In response, the developer built a 73-line shell script called outreach-schedule-guard.sh that detects unauthorized plist changes, logs the modification timestamp, captures a snapshot of running processes for forensic review, and automatically restores the correct configuration. The tool was designed not just to fix the problem but to preserve evidence, allowing the developer to distinguish between their own scripting errors and potential outside interference.

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