Ron Mitchell

Hook AI agents — autonomous tools that read your data, take actions, and follow up — moved from experiments into real business use in 2024–2025. Big cloud vendors and startups shipped agent frameworks, and more teams are using them to speed sales workflows, automate reporting, and reduce repetitive work. The story, in plain terms – […]

Quick trend snapshot – Over the last 12–18 months we’ve seen a clear shift: AI agents — autonomous, task-focused assistants built on large language models — are moving from proofs-of-concept to everyday business tools. – Low-code agent builders and tighter integrations with CRMs, ERPs, and BI systems mean teams can automate outreach, triage leads, produce

Story summary Major cloud vendors and startups are rolling out low-code “agent builder” tools that make it far easier to create AI agents — autonomous, multi-step bots that can read your systems, take actions, and produce human-ready outputs. Instead of one-off chatbots, these agents can: – pull data from CRMs and ERPs, – generate tailored

Quick summary AI agents — autonomous, task-focused AI that can research, act, and follow up without constant human prompting — are no longer just experiments. Over the past year vendors and startups have packaged agent frameworks, connectors, and pre-built workflows aimed at enterprise use: sales outreach, customer triage, automated reporting, and routine process automation. Businesses

Short summary AI “agents” — small, goal-directed systems powered by large language models — are finally moving out of demos and into real business workflows. Cloud vendors and startups are shipping agent toolkits and integrations that let these agents read your CRM, pull from spreadsheets, run basic analytics, and take actions (like creating tasks, sending

Quick summary AI agents — autonomous software that can read, decide, and act across apps — are no longer just lab projects. More companies are using agents to handle routine sales tasks, generate up-to-date reports from multiple data sources, and orchestrate cross-team workflows. That means less manual work, faster decisions, and clearer signals for leaders.

Summary Over the last year we’ve moved from “AI as a research demo” to “AI as a business teammate.” Agent-style models — AI that can take multiple steps, call tools, and follow up on tasks — are being embedded into sales and operations workflows. These agents can draft personalized outreach, update CRMs, prepare weekly dashboards,

Short summary Over the past year we’ve seen a clear shift: AI agents — autonomous systems that can access company data, carry out tasks, and act across apps — are moving from experimental demos into real business use. Teams are using agents to draft personalized outreach, update CRMs, run and summarize sales reports, and trigger

Quick summary AI agents — goal-oriented software that can research, draft, act, and follow up with minimal human direction — are no longer just lab demos. More companies are using agents to automate routine sales tasks, generate real-time reports, triage customer issues, and run recurring operational workflows. That shift is lowering turnaround times, reducing manual

Summary AI agents — software that can carry out multi-step tasks on your behalf — have moved from lab demos to practical business tools. Advances in agent frameworks, retrieval-augmented generation (RAG) for reliable answers, and low-code integrations mean agents can now handle things like lead qualification, data pulls and summaries, automated outreach, and recurring reporting