ML engineer seeks venue for construction BIM benchmark
An ML engineer at a construction AI startup is preparing to publish a benchmark for construction cost estimation. The benchmark uses professional estimators to create item-level takeoffs from drawing sets, with multiple rounds of review. The engineer is asking for advice on where to submit the research.
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Community shares budget local LLM build guide for ~$3K total
A Reddit user posted a detailed guide for building a local LLM rig for about $3,000, recommending ~$2K in GPUs and ~$1K for the rest of the system. The post, written without LLM assistance, argues this offers the best price-to-performance for running models locally in mid-2026.
Developer seeks feedback on AI-assisted feature development pipeline
A developer shared a detailed 5-step assembly line for feature development using AI, where each step requires passing a checklist before proceeding. The process includes spec writing, plan review, and multiple reviewer passes for risky features. The post asks whether this approach is efficient or wastes tokens.
CTOs share playbooks for governing LLM cost and usage in production
Engineering leaders discuss strategies for managing LLM costs and usage as AI features scale from prototype to production. A key challenge is that user-facing workflows often trigger multiple LLM calls, making costs non-obvious during MVP stages.
Startup founder surveys community on paid AI agent use cases
A startup founder asked the community which AI agents they pay for, what specific problems they solve, and whether they save time or money. The post seeks genuine value insights beyond hype, targeting real-world use cases.
ML community debates submission limits to ease review burden
A researcher working across multiple fields observes that the ML community's high submission volume is degrading review quality, as seen in recent ARR cycles. They question why ML does not adopt per-author submission caps used successfully in security (CCS) and computer architecture (DAC) conferences.