Ron Mitchell

Quick story Over the past year, we’ve moved past demos and playbooks: AI agents — autonomous, task-focused AI workflows that can read systems, take actions, and follow up — are being deployed in real business processes. Sales teams are already using them to qualify leads, draft and personalize outreach, update CRMs, and produce end-of-day reports. […]

Quick summary AI agents — autonomous, tool-using versions of large language models — are moving from labs into everyday business use. Major cloud and platform vendors now offer low-code agent builders and integrations with CRMs, calendars, and reporting systems. That means companies can build “smart assistants” that qualify leads, update records, create reports, triage support,

Quick summary AI agents — purpose-built, semi-autonomous assistants that can fetch data, write messages, run reports, and even trigger actions — are shifting from experiments to real business use. Instead of one-off proofs of concept, more teams are putting agents into production to automate sales outreach, generate recurring reports, and run routine operational workflows. Why

Quick summary AI “agents” — autonomous, goal-driven AI workflows that can read, act, and coordinate across apps — have moved from experiment to enterprise-ready. Vendors and startups have shipped low-code agent builders, better retrieval systems for company data, and connectors into CRMs, ERPs, and BI tools. That combination makes it practical to automate complex, multi-step

Summary AI agents — autonomous virtual assistants that can take multi-step actions (think: research leads, draft emails, update CRMs, and generate reports) — went from hacker projects to enterprise-ready tools in 2024. Vendors and open-source frameworks made it easier to chain LLM calls, connect to data, and wrap guardrails around agent behavior. The result: businesses

Quick summary AI “agents” — small, goal-driven systems that can access your data, take actions, and talk to people or apps — moved from lab demos to real business pilots in 2024. Teams are using agents to qualify leads, pull and summarize sales data, automate routine follow-ups, and trigger workflows across CRMs, Slack, and help

What’s new Over the past year we’ve seen a clear shift: AI agents — autonomous, connected AI helpers that can run tasks across apps — are moving from demos into real business work. Instead of a single model answering questions, modern agents combine retrieval (company data), workflow tools (CRMs, calendars, ticketing), and business rules to

Big picture (the story) In 2024 we hit a tipping point: enterprise-grade AI agents — configurable, multi-step AI assistants that can connect to internal systems and act on behalf of users — moved from demos into day-to-day business use. Major cloud and LLM providers released toolkits and integrations that make it faster and safer for

Quick summary AI “agents” — autonomous, task-focused assistants that can read systems, run queries, and act on your behalf — are moving from research demos into real business tools. You’re already seeing this in CRM copilots, BI assistants that build recurring reports, and automation tools that draft outreach, summarize meetings, and update records across systems.

Quick summary Over the past year organizations have moved from experimenting with large language models to deploying AI agents — autonomous programs that can access tools, systems, and data to complete real business tasks. Major cloud vendors and startups now offer agent frameworks and orchestration platforms that let an AI agent pull CRM data, run