Social Pulse · AI · 2026-10-11 00:10 UTC
@aisearchio: New tools, models and vibecoding claims from builders
Huge database of decompiled games https://t.co/UbkgkKw8M6 https://t.co/ieeRv3dn25
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Huge database of decompiled games https://t.co/UbkgkKw8M6 https://t.co/ieeRv3dn25
Part of the conversation: New tools, models and vibecoding claims from builders
@aisearchio (11.3K likes) shares a huge database of decompiled games. @JonahBlake (4.3K likes) points to the first vibecoded game to sell well on Steam and says that if it makes over a million dollars, studios will switch to AI. @alex_whedon (2.5K likes, 4.0M views) launches SubQ Snap and claims 61.7 on Decision Index v0.2.1 versus Jev's 57.9. @AnthropicAI (3.3K likes) says it has reduced the effectiveness of distillation attacks against Claude. @Kalshi (5.1K likes) relays a Musk claim about OpenAI, Anthropic and Cursor.
Why it mattersLaunch claims and industry assertions drew large view counts, though each rests on the poster's own statement.
Other posts in this conversation
The first vibecoded game to actually sell well on Steam If it makes over a million dollars every U.S. studio and indie dev will silently switch over to AI regardless of the complaints
JUST IN: Elon Musk says only OpenAI, Anthropic, and Cursor have enough programming training data to build true superintelligence
Over the last few months, we’ve made significant progress in reducing the effectiveness of distillation attacks against Claude. In this post, we explain how: https://t.co/uWiRSLBuOS
Introducing SubQ Snap, the first long-context decision model for real enterprise work. Snap is the only decision model or LLM where compute per token stays constant as context grows. • 384K tokens of multimodal context, 12x larger than Jev. • 61.7 on Decision Index v0.2.1 vs Jev’s 57.9, outperforming on 13 of 16 enterprise benchmarks. •Processes 100K tokens and returns a decision in under one second. •$0.05/MM input tokens. Output is free. Available today to anyone. The first 10,000 sign-ups get 100M free input tokens. We’ll likely hit capacity fast and will add users as we add compute. Compute offers welcome 🙂. Latency will be variable as we tune the platform to this new model and category of users. Model speeds are 80ms for minimal context, 250ms for 32k, 660ms for 100k, and 2.5 seconds for 384k. Visit: https://t.co/Nc76iJF2a8
How it compares
This post ranks #5 of the 14 highest-engagement ai posts AgentFlare tracked on 2026-10-13, with 1.6× the median likes. See the full AI briefing.
How this page is made. Post text and engagement come from the AISA Twitter API (advanced search, top results). Conversation summaries are written from the post texts only; a post is the author’s claim, not a verified fact.
Sources & citations
- @aisearchio on X 2026-10-11 00:10 UTC
- AISA Twitter API