agents
agents on Beyond Market Intelligence: a running collection of 5 stories we have gathered and hand-picked because they are worth your time. Every post here touches on agents 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 agents, 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.
How to Run Claude Code Agents for 24+ Hours
Unlock sustained coding productivity with Claude Code Agents running continuously – even for 24+ hours. This guide explores how to leverage these powerful AI assistants to streamline your engineering workflows and tackle complex projects with unprecedented efficiency. Discover practical techniques for maintaining and optimizing long-running agents, transforming your coding process. For a foundational understanding of setup and configuration, see "A Beginner’s Guide to Setting Up Claude Code for High Performance Agentic Programming" and elevate your agentic programming skills.
Top 10 GitHub Repositories Trending in July 2026 (AI, ML & GenAI Edition)
July 2026’s GitHub Trending reveals a clear shift: the rise of AI agents. Forget isolated research; the top repositories now center on autonomous coding, security, and even trading agents, alongside the critical infrastructure supporting them. We’ve analyzed star growth, momentum, and practical application to identify the ten most impactful projects. Discover these transformative tools—ranked by significance—that are shaping the future of AI development. For deeper insights into the evolving AI landscape, explore our analysis of the Kimi model and its implications.
Using Classical ML to Empower AI Agents
AI agents are rapidly evolving, but achieving true operational efficiency requires more than just the latest neural network architectures. A pragmatic approach involves leveraging the proven strengths of classical machine learning. This post explores the significant value of building upon existing ML foundations to empower AI agents, ensuring stability and predictable performance. We’ll examine how integrating established techniques can address key challenges in agent design.
QCon AI Boston: Production AI Moves Beyond Prompts to Platforms, Harnesses, and Evals
QCon AI Boston 2026 addressed a critical shift: Production AI moving beyond initial prompt-based exploration to robust platforms, harnessed agents, and rigorous evaluations. The conference centered on the operational challenges of deploying AI agents at scale, emphasizing improved context management and robust security measures—including a "harness" approach to contain agent access. Attendees explored a comprehensive engineering model for AI, recognizing the need for mature infrastructure. For further insight into agent security concerns, see our recent article, "The agent security gap."
Google's Genkit Ships Agents API with Detached Turns and Human-in-the-Loop for TypeScript and Go
Google’s Genkit Agents API, now in preview for TypeScript and Go, represents a significant advancement in AI agent development. This framework streamlines complex workflows by packaging message history, tool loops, streaming, and state persistence into a unified `chat()` interface. Notably, detached turns enable continuous agent operation even after client disconnection. Furthermore, interruptible tools introduce a crucial human-in-the-loop capability, ensuring control and security through anti-forgery validation when resuming tasks.