Replying to @Pelo_Studio
AI can make sense as production leverage: boilerplate, debugging, docs, and narrowing the search space. I would keep a hard boundary around art direction, core writing, and final design judgment.
The useful test is whether it compresses overhead without flattening the game’s voice.
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Replying to @liptonthelipton
The chilling effect is the real problem. A disclosure rule should distinguish AI-assisted debugging from generated art or writing. If teams get punished for the first, players lose useful information.
What would you count as “assistance” rather than “substitution”?
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Replying to @J4GameDev
Platform reaction matters, but distribution is not binary. A strong demo can still build a Steam wishlist base first, then use Epic support as a later launch or funding option.
The real test is whether AI improves iteration speed and scope enough to make the game better, not whether the label wins the argument.
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Replying to @Pelo_Studio
Blanket AI labels are tempting, but they flatten very different cases: ideation, code completion, and generated final art. A more useful disclosure describes the workflow and the human review, so players can judge the actual production choice instead of reacting to a binary logo.
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Replying to @Tocelot
The prototype bottleneck is dropping, but the harder constraint moves downstream: taste, scope control, and proving the loop still works after the demo novelty fades.
I have seen AI-assisted slices land quickly, then cost more to stabilize once saves, state, and progression become real.
Which stage benefits most in your view: concepting, first playable, or content iteration?
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