Ron Mitchell

Quick summary Autonomous AI agents — systems that take actions on your behalf (draft emails, update CRMs, run reports, and even follow up with customers) — are moving from labs into real business use. Companies are using them to automate routine work, personalize outreach at scale, and generate near-real-time reports that used to take hours […]

Summary of the story – In the last year the biggest practical shift in AI hasn’t been a single new model — it’s been the rise of autonomous AI agents and low-code agent builders. – These agents can perform multi-step tasks (e.g., research, draft outreach, update systems, generate reports) with little human supervision. They connect

Summary Autonomous AI agents — programs that can plan and act across apps without constant human prompts — moved from demo-stage to real business use in 2024–25. Companies are using them to qualify leads, update CRMs, run recurring reports, schedule meetings, and even manage simple customer-service escalations. The result: less time spent on repetitive tasks,

Quick story summary AI “agents” — autonomous software that plans, executes tasks, and talks to other apps — are no longer just research demos. Over the last year, more businesses have moved from pilot projects to production deployments of task-specific agents that handle sales outreach, customer triage, reporting automation, and back‑office workflows. Why this matters

Quick summary AI agents — autonomous software that can read, act, and coordinate across apps — have moved out of proofs-of-concept and into real workflows. Improvements in large language models, better integrations with CRMs and ERPs, agent-development frameworks, and more mature safety controls mean businesses can now deploy agents that actually do useful work: update

Story summary Over the past year we’ve moved from AI demos to real, running AI agents in business workflows. Major cloud and AI vendors have released agent frameworks that let teams deploy autonomous assistants that can open apps, call APIs, update CRMs, and produce reports — without a person typing every step. Why this matters

Quick summary AI agents — autonomous, task-focused AI that can act on your behalf (think: qualify leads, summarize meetings, automate reports) — moved from proof-of-concept to practical deployments in 2023–2024. Major platforms made agent-building easier, startups packaged agent workflows, and early adopters reported faster response times, better lead follow-up, and fewer manual tasks. Why this

What happened In the past year AI agents — self-directed models that can access tools, search company data, and take multi-step actions — moved from lab demos into real business use. Companies now deploy agents for tasks like lead research, automated outreach, report generation, and routine process automation. These agents combine language models with connectors

Summary Major CRM and analytics vendors are embedding autonomous AI agents into everyday business tools. Think AI that drafts outreach, updates records, generates on-demand reports, and runs routine workflows across systems — without waiting for a human to copy-paste data between apps. You’ve already seen this trend with things like Salesforce’s Einstein GPT and Microsoft’s

Quick summary A new wave of production-ready AI agents — autonomous assistants that can use apps, pull live data, and carry out multi-step tasks — is making headlines. Vendors and enterprises are finally moving beyond one-off chatbots to agents that qualify leads, schedule meetings, update CRMs, generate on-demand reports, and trigger downstream workflows without constant