Ron Mitchell

AI story (short summary) AI “agents” — autonomous, goal-driven AI that can run tasks end-to-end — have started moving out of lab experiments and into real business workflows. Improvements in large language models, easier connectors to CRMs and databases, and low-code orchestration tools are letting companies automate complex tasks like sales outreach, meeting follow‑ups, invoice […]

Summary AI agents — software that can autonomously perform multi-step tasks across apps, documents, and data — are no longer experimental. Over the last year we’ve seen tools that can research, draft and send emails, update CRMs, generate reports, and even trigger downstream automations without constant human direction. That means teams can offload recurring, time-consuming

Quick summary AI “agents” — autonomous programs that combine large language models with tools, plugins, and data connectors — are shifting from lab demos into real business use. Instead of one-off chat responses, these agents can fetch CRM records, run queries against databases, generate reports, send emails, and even open tickets or book meetings —

Quick summary AI “agents” — purpose-built, task-focused AI systems that can plan, act, and integrate with your apps — moved from labs into real business tools in 2024. Major cloud vendors and open-source projects released low‑code agent frameworks that make it faster to build assistants that do things like summarize accounts, create reports, route tickets,

Short summary AI “agents” — autonomous assistants built on large language models that can run multi‑step workflows, call apps, and generate reports — are no longer a lab experiment. Over the past year major vendors and startups have pushed agent frameworks into business tools. That means AI can now do things like gather data from

Quick summary AI “agents” — software that can take multi-step actions (run queries, send emails, update systems, and generate reports) — are moving from lab experiments into everyday business use. Instead of just answering questions, these agents can act on your behalf: pull CRM data, build and send a personalized outreach sequence, or produce weekly

The story (short) AI agents — small, task-focused systems built on large language models that can act across apps and services — moved from demos into real business use in 2024. Companies now deploy agents that can qualify leads, book meetings, triage tickets, and stitch together data from CRMs, calendars, and reporting tools to complete

What’s happening Autonomous AI “agents” — tools that can take multi-step actions (searching data, writing emails, updating systems) without constant human prompts — have moved beyond lab demos. Major cloud and workflow platforms are adding agent frameworks and connectors so businesses can run controlled, repeatable tasks: qualify leads, summarize calls, create reports, and even trigger

Summary AI “agents” — autonomous, task-focused AI assistants you can customize — have moved from demos to real deployments. Major platform vendors now offer low-code agent builders and integrations, and more companies are using agents to handle repeatable sales, support, and ops work. That means organizations can automate more of the routine work that blocks

Quick summary AI “agents” — autonomous assistants that combine large language models, tool use, and API integrations — are moving from labs into real business workflows. Major platform providers have shipped agent-building frameworks that let companies create agents that run multi-step tasks: qualify inbound leads, generate and deliver sales reports, open and follow up on