Ron Mitchell

Summary Autonomous AI agents — software that can plan, act, and follow up with little human intervention — are no longer just demos. Over the past year we’ve seen more off‑the‑shelf agent platforms, open‑source frameworks, and enterprise toolkits that make it practical for companies to deploy agents for real work: prospect research and outreach, recurring […]

Quick summary AI agents — models that can carry out tasks, call tools, and act across systems — have crossed the “toy” threshold and are now delivering real business outcomes: faster reporting, lower support costs, and more qualified sales conversations. Advances in model capability, tool integration, and inexpensive automation mean teams can replace repetitive work

Short summary: Over the last 12–18 months we’ve seen a clear shift: AI agents — systems that can take multi-step actions, access your apps (CRM, calendar, reporting tools), and carry out workflows autonomously — have moved from demos into real business use. Companies are using agents to draft and send personalized outreach, summarize meetings and

What’s happening AI agents — autonomous bots that can act across apps, fetch data, draft messages, and follow a sequence of tasks — have moved from lab demos into real business tools. Over the last year major cloud and SaaS vendors rolled out easier ways to build and connect agents, and companies are piloting them

Quick summary AI agents — software that uses large language models to act autonomously across apps and data — moved from experimental demos into real business use in 2024–25. Major platforms (enterprise copilots, cloud providers and third‑party agent frameworks) now let companies automate tasks like lead qualification, CRM updates, invoice processing and routine reporting. The

Quick story AI “agents” — autonomous AI that can read data, take actions, and talk to apps — have moved from research demos to real business use. Over the past year we’ve seen vendors and early adopters stitch large language models, retrieval-augmented knowledge, and API/action connectors into agents that do end-to-end work: draft and send

What’s happening Over the last 12–18 months we’ve moved past “chatbots” to practical, customizable AI agents: purpose-built AI that can access your data, run workflows, update systems (CRM, calendars, BI) and act on behalf of teams. Platform marketplaces and low-code agent builders now let non‑engineers create domain-specific agents for things like sales outreach, customer triage,

Quick story AI agents—autonomous, task-focused AI that can act on your behalf—are moving from labs into everyday business use. Companies are using agents to draft personalized outreach, update CRMs, generate weekly sales reports, and automate routine approvals. The result: faster workflows, fewer manual errors, and teams that spend more time on strategy and customer relationships

Short summary AI agents — software that combines large language models with automation to act on your behalf — have shifted from research demos to practical tools that businesses use every day. Instead of just answering questions, modern agents can pull data from your CRM, generate outreach, update records, and produce recurring reports. Advances like

Short summary AI “agents” — software that uses large language models to run tasks, call APIs, and keep working without constant human prompting — are moving from experiments into real business use. Companies are using agents to generate weekly performance reports, qualify leads, automate CRM updates, route exceptions to humans, and run recurring analytics that