Developer Builds AI Tool to Email Hiring Managers Directly, Bypassing Easy Apply

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A developer has launched PitchHired, an AI-powered job search platform designed to help candidates reach hiring managers directly rather than relying on standard application portals. The tool assists users in identifying hiring managers, drafting personalized outreach emails, and sending them via Gmail during business hours. Unlike many job search tools, PitchHired focuses on reducing repetitive tasks while keeping candidates in control of their outreach. The platform uses a one-time credit model instead of a recurring subscription, acknowledging the financial pressures job seekers face between roles. The tool is still in development, and the creator is actively seeking feedback from the developer community.

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How to Build a Unified ROS 2 Serial Bridge for Yahboom 520 Motor Drivers

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ProgrammingDEV Community ·

Google's DESIGN.md Solves Token Format, Not Design Intent for Early-Stage Teams

Google Labs open-sourced DESIGN.md, a standardized YAML-based format that lets AI coding agents read and write design tokens such as colors, spacing, and typography, along with a CLI for linting, diffing, and exporting to Tailwind CSS. The format works well for teams that already have a defined design direction, but critics argue it does not help solo developers or zero-to-one teams who have not yet decided on a visual identity. A DEV Community analysis points out that core decisions — like choosing an accent color or a stylistic reference — must happen before DESIGN.md can be meaningfully written. The author proposes a multi-step 'design chain' that starts with prose-only direction documents and visual mockups before any concrete values are committed to tokens. This approach ensures design choices are grounded in deliberate reference analysis rather than gut instinct, filling the gap that a token format alone cannot address.

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ProgrammingDEV Community ·

Developer Publishes SIL-3-Grade Open-Source Insulin Control Loop Simulation for T1D

Software architect Omer Giladi has published a Python-based simulation of a closed-loop insulin delivery system designed for Type 1 Diabetes management, built on what he calls a '4-Brains Cybernetic Architecture' combined with Fibonacci-derived constants. The project, released under a 2026 copyright, is classified as a mission-critical, SIL-3 medical-grade concept and is not a production medical device. Security features include HMAC-SHA256 cryptographic validation of incoming glucose sensor data, temporal drift checks to block replay attacks, and a biological accumulation guard intended to detect synthetic or spoofed data streams. Hard-coded physiological dose limits — including a maximum single correction dose and a 24-hour total dose cap — are designed to remain non-bypassable by the algorithm. The codebase is implemented using FastAPI and is publicly shared on DEV Community as a research and architectural reference.

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ProgrammingDEV Community ·

AI Agents Can Break Production Systems Without Proper Safety Controls

AI agents are capable of writing code, running tests, calling APIs, and even deploying software, but experts warn this capability introduces serious operational risk in production environments. Unlike human engineers, AI agents lack contextual judgment, accountability, and the ability to own consequences when actions go wrong. A misinterpreted instruction — such as deleting 'test data' — could lead an agent to wipe real customer records from a production database. Production engineering has decades of safety practices built around human error, including code review, access controls, and rollback mechanisms, and AI agents require the same or stricter guardrails. Practitioners recommend that agents operate through permission layers, approval gates, audit logs, and sandbox environments rather than having direct, unrestricted access to critical systems.

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