Ron Mitchell

Quick summary AI agents — autonomous, task-focused AI that can act across apps and data — have moved fast from research demos into real commercial use. Over the past year many vendors and startups shipped agent frameworks, pre-built workflows, and enterprise integrations that let companies automate multi-step processes (think lead triage, follow-up, quoting, and report […]

Quick story Autonomous AI agents — systems that can plan, act, and complete business tasks with minimal human direction — have gone from experimental demos to practical pilots across sales, finance, and operations. Over the last year organizations have started using agents to automate routine workflows (like lead qualification, invoice routing, and monthly reporting), orchestrate

Quick summary AI agents — software that carries out tasks end-to-end with minimal human handoffs — are no longer an R&D novelty. Companies are using them to generate regular sales and ops reports, automate repetitive workflows, triage customer requests, and trigger cross-team actions. That shift turns AI from a “tool” into an active part of

Summary AI agents — autonomous, goal-driven software that can search data, use apps, and take actions — are no longer just lab projects. Over the past year we’ve seen more companies embed agents into real workflows: sales teams use agents to draft personalized outreach and update CRMs, operations teams automate purchase approvals and exception handling,

Quick summary AI “agents” — software that can act, decide, and chain tasks with minimal human prompts — are no longer just tech demos. Over the last 12–18 months we’ve seen an uptick in companies using these agents for real workflows: prospecting and outreach, automated deal follow-ups, dynamic sales playbooks, and recurring operational reporting. The

Quick story AI agents — autonomous, multi-step bots that can read your CRM, draft emails, update records, and generate reports — are no longer just lab experiments. Over the last 12–18 months the market shifted from demos to production pilots: low-code agent builders, secure API connectors, and better governance tools make it realistic for teams

Quick summary AI “agents” — autonomous, goal-driven bots that combine large language models, connectors, and business logic — have moved beyond research demos into practical tools. Over the last year vendors and startups have shipped easier agent builders, prebuilt connectors to CRMs and data warehouses, and templates for tasks like lead qualification, customer triage, and

Quick summary AI “agents” — software that can plan, act, and follow up across apps — are no longer just experiments. Across sales, customer service, and operations, teams are deploying agents to do repeatable work: draft outreach, triage tickets, generate regular reports, and trigger downstream workflows. The result: faster responses, fewer manual steps, and clearer,

What happened Autonomous AI agents — software that can act on your behalf, chain tasks, and make simple decisions — are moving from research demos into real business use. Companies are combining agent frameworks (think Auto‑GPT/LangChain style flows) with enterprise copilots from major cloud providers to automate tasks like lead research, outreach personalization, CRM updates,

Big idea (short): Autonomous AI agents — software that can carry out multi-step tasks across apps — are maturing quickly. Businesses can use them to automate sales outreach, generate up-to-date reports, triage customer requests, and run routine back-office workflows. That’s real time and cost savings, not just tech hype. Why this matters to leaders –