Missing DMARC record was silently blocking registration emails on Gmail and Outlook

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Registration confirmation emails from the domain wpmm.jp were failing to reach users on Gmail and Outlook, landing in spam or going missing entirely. Investigation revealed the domain had SPF and DKIM configured but lacked a DMARC record, which major providers like Gmail factor into mail delivery decisions. A DMARC TXT record with a permissive 'p=none' policy was added to DNS, enabling aggregate reporting without risking legitimate mail being blocked. Alongside this, the sending code was updated to properly handle failed send attempts and include required headers such as Message-ID and Date, which are known spam signals when absent. Following the fix, Google began delivering aggregate DMARC reports confirming legitimate mail passes DKIM alignment, giving the team active visibility into email deliverability.

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How to Build an Offline AI Health Analyst on a MacBook Using Llama-3 and MLX

A new tutorial demonstrates how Mac users can analyze their Apple Health data entirely offline using Meta's Llama-3 language model and Apple's MLX framework, eliminating the need to upload sensitive health information to the cloud. The setup runs a 4-bit quantized Llama-3-8B model locally on Apple Silicon chips, taking advantage of the Unified Memory Architecture for fast on-device inference. Users first export their health data from the Apple Health app, then parse metrics such as heart rate and step count from the XML file using Python and Pandas. The processed data is fed into the local model, which generates actionable health insights without any data leaving the device. The approach requires a Mac with an M1, M2, or M3 chip and a few open-source Python libraries to get started.

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ProgrammingDEV Community ·

Claude Code 2.1.229 adds SSE keepalive pings to fix gateway stream timeouts

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ProgrammingDEV Community ·

Kanban Was Born in Japan, Yet Japanese Offices Still Swear by Excel

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ProgrammingDEV Community ·

How to Handle Speech-to-Text API Timeouts for Large Audio Uploads in EdTech

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