This story was originally published on HackerNoon at: https://hackernoon.com/using-zmanim-wp-shortcodes-for-shabbat.
This installment in the free WordPress plugin tutorial covers Shabbat shortcodes: candle lighting, Torah portion, and holiday names.
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This story was written by: @leonadato. Learn more about this writer by checking @leonadato's about page, and for more stories, please visit hackernoon.com.

This time I'm covering the free WordPress plugin Zmanim-WP's Shabbat specific shortcodes, including candle lighting time, weekly Torah portion, and holiday names.

This story was originally published on HackerNoon at: https://hackernoon.com/hellocv-earns-a-63-proof-of-usefulness-score-by-building-ai-powered-profiles-that-network-autonomously.
hello.cv earned a 63 Proof of Usefulness score for combining AI-powered profiles, autonomous networking, and search-optimized professional identity.
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This story was written by: @ope_1p3aiql. Learn more about this writer by checking @ope_1p3aiql's about page, and for more stories, please visit hackernoon.com.

hello.cv earned a 63 Proof of Usefulness score for building an AI-first professional networking platform that gives users search-optimized personal sites, custom domains, and autonomous networking assistants.

This story was originally published on HackerNoon at: https://hackernoon.com/ellas-ai-agent-earns-a-4606-proof-of-usefulness-score-by-building-an-autonomous-e-commerce-ai-support-agent.
Ella’s AI Agent earned a 46.06 Proof of Usefulness score for automating e-commerce support, order lookups, ticket triage, and human escalation.
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This story was written by: @its.ella.codes_0jr3tfqo. Learn more about this writer by checking @its.ella.codes_0jr3tfqo's about page, and for more stories, please visit hackernoon.com.

Ella’s AI Agent earned a 46.06 Proof of Usefulness score for building a real-time e-commerce support prototype that handles order inquiries, ticket triage, sentiment analysis, and escalation to human support. Built with n8n, Groq, Supabase, Bright Data, and Gmail integrations, the project is still pre-launch. Its biggest limitation is that the strongest performance claims, including 70–80% automated resolution and sub-two-second response times, are projections rather than live-user results.