Ron Mitchell

Story summary AI “agents” — LLM-based systems that can act on your behalf (for example: qualify leads, pull and summarize reports, or automate approvals) — have moved from experiments into practical business use. Recent months have shown more companies building agents that connect securely to internal data, run repeatable workflows, and hand off to humans […]

Quick summary AI “agents” — autonomous, multi-step AI assistants that can search systems, run processes, and act on behalf of users — moved from lab demos into real business projects this year. Major vendors and open-source projects released agent frameworks, and companies are combining agents with retrieval-augmented generation (RAG), vector databases, and low-code orchestration tools

Summary AI “agents” — autonomous, goal-driven AI that can run multi-step tasks — are no longer just experiments. Over the last year, more companies have put agents into production to do things like qualify leads, draft and follow up on outreach, summarize market and sales signals, and assemble regular reports from multiple systems. These agents

Quick summary Major vendors and dozens of startups are rolling out easy-to-build AI agents and conversational BI tools that let non-technical teams ask questions in plain English and get automated, actionable reports or automated workflows. In short: AI is moving from “nice to have” tools to practical systems that run parts of your business —

Summary AI agents — autonomous, task-focused AI that can run workflows, fetch data, and take actions inside apps — are no longer just experiments. Businesses are using them to draft customer outreach, automate recurring reports, and handle routine operational tasks. That means faster responses, fewer manual steps, and clearer visibility for leaders. Why this matters

Short summary AI agents — software that can plan and execute multi-step tasks on its own — have moved from tech demos to real business use. Over the last year we’ve seen major AI platforms make it easier to build customizable agents, and startups are adding connectors to CRMs, ticketing systems, and analytics tools. That

AI story (short summary) AI agents — autonomous, goal‑directed software that can take multiple steps to complete a task — are moving out of labs and into everyday business workflows. Companies are using them to triage support tickets, qualify leads, generate and update reports, schedule meetings, and automate routine back‑office work. The result: faster turnaround,

What happened OpenAI’s March 2024 rollout of custom “GPTs” and the wave of low‑code agent tools from major vendors made it much easier for companies to build AI agents that act on their behalf — not just answer questions. These agents can access CRMs, calendars, ticketing systems, and databases to do tasks like draft outreach,

Short summary AI agents — autonomous apps that read your systems, generate decisions, and take actions — are no longer just experiments. Companies are using them to automate sales outreach, update CRMs, generate real-time reports, and run routine operational workflows. The result: faster responses to leads, fewer manual errors, and more time for reps to

Short summary In the past year we’ve moved from “chatbots” to true AI agents — autonomous programs that can run multi-step tasks, access your systems, and make decisions or recommendations. Major cloud providers and enterprise software vendors have added agent frameworks and integrations, and startups are building industry-specific agents for sales, HR, and finance. Why