Ron Mitchell

Short summary AI “agents” — autonomous, task-focused AI assistants that can act across apps and data — have moved from lab demos to real business use. Companies are using them to draft follow-up emails, update CRMs, generate weekly sales reports, and even run multi-step workflows without constant human intervention. That shift is making routine work […]

Summary A new wave of AI agents and agent frameworks is making it practical for businesses to automate multi-step workflows, generate timely reports, and act on insights without heavy engineering. These agents can connect to CRMs, BI tools, calendars, and ticketing systems to fetch data, run queries in plain language, create summaries or dashboards, and

Quick summary AI agents — systems that can act on your behalf by calling APIs, updating systems, sending messages, and creating reports — have moved from demos into everyday business tools. Over the last year we’ve seen major platforms and startups release ready-to-use agents and low-code agent builders that connect to CRMs, calendars, email, and

Short summary AI “agents” — autonomous or semi‑autonomous AI that can act on your behalf across apps and data — moved from demos to real business pilots in 2023–2024. Firms are now embedding agents into CRMs, reporting pipelines, and back‑office systems to qualify leads, update pipelines, generate automated reports, and handle routine approvals. The result:

AI agents are here — how businesses can turn autonomous AI into real ROI Quick summary Autonomous AI agents — tools that can act on behalf of users to complete multi-step tasks — moved from hype to practical use in 2023–24. Companies are now using agents for things like automated lead follow-up, routine customer support

Summary In the past year the conversation has moved from “what if” to “what works.” Major cloud providers and startups have released easier tools for building AI agents — autonomous or semi-autonomous software that can read data, take actions (send emails, update CRMs, generate reports), and interact with humans. Companies are already piloting agents for

Short summary AI agents — autonomous software that reads, decides, and acts across apps — are no longer just research demos. Businesses are increasingly using them to draft personalized sales outreach, update CRMs, generate weekly management reports, triage support tickets, and orchestrate routine workflows. These agents combine large language models (LLMs) with retrieval-from-your-data (RAG), API

Summary AI agents — autonomous, task-focused AI that can access apps, pull data, and take actions — are moving from research demos into real business pilots. Teams are using agents to draft client follow-ups, reconcile reports across systems, triage customer tickets, and automate routine sales tasks. The shift isn’t just about better chat: it’s about

Quick summary AI agents — autonomous, task-focused systems built from large language models plus data connectors — are graduating from lab experiments into real business apps. Thanks to cheaper compute, mature agent frameworks (think LangChain/AutoGen-style tools), and better retrieval (RAG) for company data, more teams are using agents to automate routine work: updating CRM records,

Quick summary AI agents — small, goal-directed AI programs that can act across apps and data — have moved from research demos into real business use. Companies are now using them to run routine workflows: draft sales outreach, triage support tickets, update CRMs, and generate weekly reports with narrative commentary. These agents combine large language