[D] Self-Promotion Thread

2026-03-02 · Source: Machine Learning · Field: Business & Management — Entrepreneurship & Start-ups, Marketing, Branding & Advertising, Project & Product Management · Depth: Fundamental Awareness, quick

Summary

A new "Self-Promotion Thread" has been introduced as an experimental initiative to centralize community-generated content, including personal projects, startups, product placements, collaboration needs, and blogs. Participants are required to disclose payment and pricing details for any products or services mentioned. The thread explicitly prohibits link shorteners, link aggregator websites, and auto-subscribe links, with a warning that abuse of trust will result in bans. This initiative aims to prevent self-promotional content from cluttering main discussion threads, encouraging users to post their work here instead of creating new posts for questions. The thread will remain active until a subsequent one is launched.

Key takeaway

For community members looking to share their projects or services, you should utilize the new self-promotion thread to gain visibility without violating community guidelines. Ensure you explicitly state all payment and pricing requirements for any offerings to comply with the thread's rules, thereby fostering transparency and avoiding potential bans.

Key insights

A new self-promotion thread centralizes community projects and services, requiring pricing transparency.

Principles

• Transparency in pricing is mandatory.
• Maintain community trust to avoid bans.

Method

Post personal projects, startups, or blogs in the designated thread, including payment/pricing details, while avoiding prohibited link types.

In practice

• Post your project in the self-promotion thread.
• Include clear pricing for any services.

Topics

• Self-Promotion
• Community Engagement
• Technical Education
• Professional Development

Best for: Entrepreneur, Software Engineer, Marketing Professional

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Editorial summary, takeaway, and curation by AIssential. Original article published by Machine Learning.