Ron Mitchell

Big picture Over the last year we’ve moved past proof-of-concept AI demos. Major vendors and startups are shipping “AI agents” — systems that can run multi-step tasks, pull from your data, and act inside apps (think: draft outreach, update CRM records, build recurring reports). That shift means AI is no longer just a productivity boost […]

The story in a sentence Autonomous AI agents — the apps that can talk to your CRM, pull data, draft outreach, and generate dashboards — are no longer just lab experiments. Improvements in large language models, APIs, and integration tools mean businesses can deploy them for real tasks: sales follow-up, routine reporting, and workflow automation.

Quick update Over the past year major platform vendors (OpenAI, Microsoft, Google) have made it much easier for businesses to build custom AI agents — small, purpose-built AI assistants that can interact with your apps, fetch data, run workflows, and produce human-friendly outputs. These tools are moving from developer experiments into real business deployments: think

Short summary Autonomous AI agents — tools that can perform multi-step business tasks by themselves — have gone from research demos to practical tools across industries. Major platforms now let teams deploy agents that read emails, qualify leads, update CRMs, generate reports, and trigger downstream automations without constant human direction. Why this matters for businesses

Short summary AI agents — autonomous, goal-oriented tools that connect to apps, fetch data, and take actions — are moving out of labs and into real business workflows. Over the last year we’ve seen a wave of pilots across sales, finance, and ops: agents that draft and send outreach, reconcile accounts using bank and ERP

Summary AI “agents” — autonomous or semi‑autonomous software that can act on your behalf across apps and data — have moved from research demos into real business use. Companies are using agents to run follow‑ups, generate and distribute sales reports, qualify leads, and automate routine decisions. Platforms and toolkits (think orchestration frameworks and plug‑and‑play connectors)

Story summary AI agents — autonomous, goal‑driven assistants built from large language models, connectors, and simple automation — are moving out of pilots and into real business workflows. Instead of only answering questions, these agents can now complete multi‑step tasks: qualify leads across CRM and email, prepare quarterly sales reports by combining data from BI

What’s happening AI agents — autonomous systems that can connect to calendars, CRMs, databases and apps to complete multi-step tasks — are no longer a niche experiment. New tools and integrations make it easier for these agents to pull data, run analyses, create reports, and act on decisions without a human typing every step. Why

Quick summary AI agents — autonomous software that can read, reason, and take actions across your tools — moved from research demos to practical business use in the past year. Major platforms and frameworks now make it easier to connect agents to CRMs, calendars, BI tools, and ERPs so they can monitor pipelines, generate reports,

Summary AI agents — software that can read, decide, and act across apps — are no longer experimental. Over the past year, major vendors and startups have shipped easier-to-connect agent toolkits and prebuilt connectors for CRMs, calendars, email, and reporting tools. That lets businesses automate end-to-end tasks (e.g., qualify a lead, update a CRM, draft