Agentic Workloads
Agentic Workloads on Beyond Market Intelligence: a running collection of 3 stories we have gathered and hand-picked because they are worth your time. Every post here touches on agentic workloads 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 agentic workloads, 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.
DeepSeek Harness launches as open source rival to Claude Code, alongside V4-Pro on API with higher prices
DeepSeek is expanding beyond model development, launching DeepSeek Harness v0.1, an open-source agent harness designed as an alternative to tools like Anthropic’s Claude Code. Alongside this, the company released DeepSeek-V4-Pro, an updated flagship model optimized for agentic workloads, now accessible via DeepSeek’s web interface, mobile app, and API. While V4-Pro offers enhanced capabilities and OpenAI Responses API support, developers should note a shift to peak and off-peak API pricing, beginning Sunday, Aug. 16, which will substantially impact costs.
No cloud, no GPUs, no problem: Liquid AI's new model LFM2.5-2.6B brings powerful AI agents to devices as small as a Raspberry Pi
Liquid AI has unveiled LFM2.5-2.6B, a new open-weight language model designed to bring powerful AI agents to devices as small as a Raspberry Pi – a significant step toward accessible edge AI. This model, boasting 2.6 billion parameters and a 128,000-token context window, runs entirely on local hardware without cloud inference or GPUs, ideal for high-volume tasks like automation and connectivity-limited environments. Explore how this innovative solution transforms data management and expands possibilities for enterprises, as highlighted in our recent coverage of Qwen 3.8-Max.
Writer's AI harness cuts token spend nearly 40% — without sacrificing accuracy
Enterprise AI faces a growing ROI challenge: while powerful foundation models excel in experimentation, production costs can quickly become unsustainable. New research from Writer demonstrates a solution accessible to engineering teams, revealing dramatic reductions—up to 41%—in task costs by optimizing the AI harness, the orchestration layer surrounding these models. This approach, which cuts token spend by nearly 40% without sacrificing accuracy, highlights the critical need to shift focus from simply increasing model size to refining system design.