Ron Mitchell

Quick summary Big cloud and AI vendors (OpenAI, Microsoft, Google and others) have rolled out easy ways to build custom AI agents and assistants this year. These tools let non‑developers configure agents that can access company data, call apps (CRMs, calendars, reporting tools), and follow simple workflows — without starting from scratch. Why this matters […]

Short summary AI agents — task-focused AI “workers” you can customize and connect to your systems — have moved from R&D demos to real business tools. Cloud platforms and agent builders now let non‑technical teams create agents that do things like follow up on leads, generate weekly KPI reports, or trigger workflows across CRM, finance,

Short summary AI “agents” — small, goal-driven systems that can read, plan, and take actions across apps — have moved from demos to real business pilots. Thanks to better integrations, safer controls, and faster models, companies can now automate multi-step work (like updating CRM records, generating weekly reports, or triaging customer requests) without building everything

Quick summary AI agents — purpose-built, autonomous assistants that connect to your systems and act on instructions — have moved from R&D demos to real business pilots. Instead of only answering questions, modern agents can qualify leads, update CRM records, generate weekly sales reports, route tasks, and complete multi-step workflows by calling your tools (calendar,

Quick summary Over the last 18–24 months we’ve seen a surge in practical “autonomous AI agents” — software that can take multi-step actions (research, draft emails, update systems, generate reports) with minimal human direction. These agents are no longer just experiments: vendors and early adopters are embedding them into sales workflows, customer support triage, reporting

Summary Recent advances in “custom GPTs” and agent frameworks (think ChatGPT plugins, LangChain-style agents, and platform-built agent builders) have made it much easier for companies to create purpose-built AI agents that access company data, run workflows, and automate tasks. These agents can pull from your CRM, generate sales outreach, assemble executive reports, summarize customer calls,

Quick summary Major cloud vendors and AI platforms are pushing “AI agents” — goal-orientated assistants that can access your systems, run multi-step tasks, and act without constant human prompting. Instead of one-off chat responses, these agents can qualify leads, pull and summarize reports, update CRMs, and trigger downstream processes. Why this matters for business –

Quick summary AI “agents” — software that combines large language models with tools (APIs, databases, calendars, CRM systems) to take multi-step actions — have moved from research demos into real business use. Teams are using agents to draft and personalize sales outreach, automate recurring reports, triage customer requests, and run monitoring/alerting workflows. The technology stacks

Short summary AI agents — small, goal-driven systems that can read your data, take actions, and talk to tools — have moved from research demos into real business tools. No-code agent builders and tighter CRM/reporting integrations make it possible to automate routine sales work, generate on-demand reports, and keep processes moving without constant human hand-holding.

Short summary AI “agents” — conversational models that act on your behalf (schedule, research, update systems, generate reports) — have moved beyond demos. Vendors like Microsoft and Google added copilots and tool-using models, and more businesses are piloting agent-driven workflows for sales outreach, customer support triage, and automated reporting. Why this matters for business –