How to Diagnose and Fix High Load Average on a Linux Server

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A high load average on a Linux server can be misleading, as it reflects processes waiting for either CPU or I/O without distinguishing between the two. Dividing the load average by the number of CPU cores helps gauge severity, with a ratio above 1.0 signaling concern and above 2.0 indicating a serious problem. Tools like top, iostat, and iotop help pinpoint whether the bottleneck is CPU usage or disk I/O saturation. Once the culprit process is identified, fixes vary by cause — such as rescheduling backup jobs, investigating slow database queries, or checking for runaway log writes. Utilities like pidstat, lsof, and strace provide deeper per-process insight to resolve the issue without unnecessary service restarts.

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Why a Developer Deleted Clean AI-Generated Code to Build Something Truly Original

A software developer writing on DEV Community argues that AI's advantage over any individual is limited precisely to the boundaries of that person's own ignorance — no further. While acknowledging AI's superior recall of syntax, algorithms, and documented solutions, the developer contends that it can only remix what already exists and cannot originate a vision for something entirely new. The author deleted a cleaner, AI-style function and replaced it with a slower, idiosyncratic one because that imperfect version contained a behaviour no standard solution would produce — one central to the product's purpose. The piece frames AI's knowledge gaps not as a threat but as a personal to-do list, arguing that every subject learned deeply removes one more area where the tool holds an edge. Ultimately, the developer concludes that authorship and taste are inseparable from the product itself, and outsourcing key decisions — even to a better output — hollows out the work's identity.

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ProgrammingDEV Community ·

CF7 to Google Sheets Drops Submissions Due to Shared API Quota Across All Users

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ProgrammingDEV Community ·

Developer Builds PDF Chat API in One Day Using FastAPI, Gemini, and Qdrant

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ProgrammingDEV Community ·

AI Agents Can't Be Sued: Why Liability Trails Back to Human Operators

When an AI agent autonomously negotiates and signs a contract, it cannot be held legally liable because software has no legal personhood. Legal systems universally agree that liability travels back along the chain of delegation until it reaches a human or entity that can be sued or fined. The challenge becomes more complex in multi-hop deployments where a principal authorizes an agent, which in turn delegates to sub-agents and third-party tools. Determining liability requires identifying, at each step, who held authority, who had sufficient information, and who could have intervened to prevent a bad outcome. Operators must maintain verifiable, timestamped authorization trails — not just policy statements — to demonstrate that governance controls were actually enforced at the moment an agent acted.

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