Ron Mitchell

Quick summary Over the past year we’ve seen a wave of purpose-built AI agents — customizable “GPTs” and low-code agent builders that connect language models to your systems, data, and APIs. Instead of one-size-fits-all chatbots, these agents are trained and configured to handle specific business tasks: personalized sales outreach, automated financial reporting, customer triage, contract […]

Story summary There’s a clear shift right now: AI isn’t just a chat tool anymore — it’s becoming an “agent” that can act autonomously across systems. Modern AI agents can read your CRM, draft outreach, update deals, generate weekly reports, and even trigger workflows without constant human prompting. Vendors and startups are rolling out agent

Quick summary This year we’ve seen a clear shift: businesses are moving from point AI tools (single-use chatbots, isolated models) to AI agents — autonomous, task-focused assistants that live inside CRMs, inboxes, and reporting stacks. These agents can draft outreach, enrich leads, schedule and follow up automatically, and even update forecasting models in real time.

Hook AI agents — autonomous software that can complete tasks, run workflows, and talk to other systems — are no longer just experiments. They’re becoming everyday tools for sales, operations, and reporting. That matters now because the teams that adopt them first are seeing faster lead response, fewer manual reports, and smarter automation. The story

Short summary AI agents — small, purpose-built AI systems that can read documents, query databases, and take actions — are rapidly moving from proofs-of-concept to real business tools. Advances in retrieval-augmented generation (RAG) and vector databases let these agents access your internal knowledge (CRM, product docs, spreadsheets) and produce accurate, context-aware answers, reports, and automated

Quick summary – Over the past year there’s been a clear shift: AI agents — autonomous, task-focused bots that can interact with systems, fetch data, and take actions — are moving from experiments into real business use. – New low-code agent platforms, better retrieval-augmented generation (RAG), and deeper integrations with CRMs and ERPs make it

Short summary AI “agents” — autonomous software that can execute tasks, make decisions, and interact with systems — have moved beyond demos. More companies are using them for lead qualification, order routing, automated forecasting, and real‑time reporting. Instead of one-off automations, teams are building small, purpose-built agents that connect to CRMs, databases, and dashboards to

Quick summary AI agents — software that can understand goals, pull data, and take actions across apps — are moving from labs into real business use. Instead of only answering questions, modern agents can draft and send emails, update CRMs, generate month-end reports, triage support tickets, and trigger workflows across tools. Companies piloting agents report

Quick story Over the last year we’ve seen a rapid shift from single-purpose AI tools to “AI agents” — systems that can run sequences of actions, call internal systems, and complete multi-step business tasks (think: pull CRM data, enrich leads, draft follow-up emails, and update forecasts). Vendor offerings (custom GPTs, agent platforms and Copilot-style products)

Quick summary AI “agents” — models that act on your behalf, use tools, and follow multi-step workflows — have moved fast from academic demos to practical business tools. Over the last year you’ve likely seen vendors and startups offering agent frameworks that connect language models to calendars, CRMs, databases, and reporting tools. That means businesses