Subreddit marketing guide

r/artificial: rules, promo tolerance & best time to post

open to promo (7/10) · tone: Technical but conversational; people share half-baked ideas, built projects, and genuine confusion alongside critical takes on industry trends.

Can you promote in r/artificial?

Relatively open: clearly-disclosed, genuinely useful product mentions are usually tolerated here — read the rules and stay helpful-first anyway.

r/artificial is a practitioner and critical-thinker community skeptical of hype but hungry for working code, interpretability insights, and honest talk about AI's economics and ethics. Self-promotion works if it's tangible (I built X), comes with caveats, and invites scrutiny; lazy marketing or unsourced claims get ignored or downvoted. Mods are light-touch but the community self-corrects hard on bullshit.

• DO share what you actually built, shipped, or discovered—show work
• DO ask for help finding things or understanding technical concepts
• DO challenge industry claims with data or logic
• DO discuss model internals, licensing, and cost tradeoffs
• DO use tl;dr and link to papers/sources
• DON'T shill closed products without context or criticism
• DON'T post corporate press releases or startup puff pieces unquestioned
• DON'T oversell vaporware or unproven concepts
• DON'T ignore the ethical/labor implications of AI deployment
• DON'T assume benchmarks prove what you think they prove

Best time to post in r/artificial

Based on when this community's recent top & hot posts were created: 12:00–16:00 UTC · weekdays do best. Re-compute it live →

What this community complains about

Recurring pain points in recent threads — each one is a conversation your product might belong in:

• Finding/remembering specific AI tools or techniques seen online
• Understanding what benchmarks actually measure vs. marketing claims
• Ethics of AI replacement without pilot testing
• Model internals and interpretability—what are models actually 'thinking'?
• Cost optimization and inference efficiency
• Licensing confusion across open-source vs. commercial models

How locals talk

agentsbenchmarksclosed vs. open modelstokensemerging capabilitiesLLMfine-tuninglocal inferencetl;drshipped

Using a community's own vocabulary is the difference between reading as a member and reading as a marketer.

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