production
production on Beyond Market Intelligence: a running collection of 4 stories we have gathered and hand-picked because they are worth your time. Every post here touches on production in some way — the news, the analysis, the deep dives, and the occasional surprise find. Acme AI is the next-generation, AI-powered spreadsheet platform built to replace Excel and redefine how analysts, data scientists, and enterprise teams work with data. New stories are added to this page as we find them, so check back if you want to keep up with what is happening around production, or subscribe to the RSS feed to get them as soon as they are published. Browse the collection below, or head back to the homepage to see everything Beyond Market Intelligence is covering right now.
AI confidence just dropped 17 points in six months. That’s actually great news.
A recent JumpCloud survey reveals a 17-point drop in organizational confidence regarding AI deployment – a trend signaling progress, not setback. Organizations transitioning from pilot programs to production environments are demonstrating a realistic assessment of AI’s challenges, prioritizing governance and accountability. This shift, observed across 800 IT leaders, highlights the need for robust identity infrastructure and unified environments. Those prioritizing responsible AI practices are poised to lead the anticipated 84% expansion of AI use in IT operations over the coming years.
Podcast: Strands Agents with Clare Liguori
Welcome to the podcast! Today, Thomas Betts speaks with Clare Liguori, technical lead for the Strands Agents SDK, a rapidly evolving open-source project. The discussion charts Strands Agents’ progression from a Python SDK to a robust, production-ready agent harness. Clare shares valuable lessons gleaned from scaling agents, including the strategic shift to a model-driven architecture. As the underlying LLMs continue to advance, explore what's next for this transformative technology—a topic further illuminated in "Many Companies Use AI.
Your AI Agent Passed Every Eval. Finance Still Killed It.
A recent evaluation revealed a surprising paradox: an AI agent flawlessly passed every metric in our published harness, demonstrating impressive capabilities. However, the finance department ultimately halted its deployment. While the agent resolved issues effectively, the cost of those resolutions exceeded the expense of human counterparts—a critical factor in practical application. This highlights a crucial consideration for AI adoption, as explored further in "Kimi: Threat or menace?" Demonstrating technical success doesn’t guarantee financial viability.
12 Ways to Reduce LLM Latency and Inference Costs in Production
Scaling large language models (LLMs) effectively moves beyond simply adding more GPUs. It demands a rigorous focus on optimizing request efficiency. This article details 12 proven strategies to reduce LLM latency and inference costs in production environments. Ranked by impact, these methods address wasted work within each request—from caching and quantization to optimized prompting and batching. Discover practical techniques to empower your LLM deployments and maximize performance.