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Building the first version of an AI workflow is usually easy. Connect an LLM to a few tools. Add some instructions. Let the model decide what to do next. Run the demo. It works. The problem starts later, when that workflow becomes part of a real process. Suddenly the important questions are not abou
Work management software company Asana Inc. today said it has completed the acquisition of StackAI Inc., a no-code platform for building artificial intelligence agents, in a deal that adds the ability to run automated workflows across the separate enterprise systems where companies keep their data.
Alibaba’s Qwen team has unveiled Qwen3.7-Max, a flagship model built for the agent era. Unlike conventional chatbot-focused LLMs, it is designed as a foundation for autonomous AI agents that can code, debug, use tools, manage workflows, and execute long-running enterprise tasks. Alibaba claims the m
Claude Code Routines: Automate AI Workflows on Autopilot in 2026 TL;DR Summary Claude Code Routines run on Anthropic's cloud infrastructure — your laptop can be closed, routines keep executing Three trigger types: schedule (cron, recurring or one-off), API (HTTP POST from any system), and GitHub eve
Local LLMs vs Cloud APIs: Building Offline-First AI Workflows Your AI workflow just went offline: Here's why developers are running models locally and saving thousands on API bills. Last month, a solo developer posted in the Indie Hackers forum about slashing his monthly OpenAI bill from $2,400 to $
How I turned LLM persona interviews into a repeatable customer research workflow The post From Ad Hoc Prompting to Repeatable AI Workflows with Claude Code Skills appeared first on Towards Data Science.
While testing different AI coding tools, I kept running into two recurring problems. The first one was cost. Using the same model to plan, implement, review, test, and document does not make much sense. Not every stage requires the same level of reasoning. The second problem was more important: when
