Ron Mitchell

Quick summary Over the past year we’ve seen a clear shift: AI agents and custom copilots are moving from demos to real business workflows. Low-code builders, improved LLM safety features, and easier integrations with CRMs and BI tools mean companies can now automate follow-ups, lead enrichment, routine reporting, and simple decision tasks with reliable results. […]

AI agents—autonomous systems that can carry out multi-step tasks, talk to your apps, and generate reports—are moving from labs into real business workflows. Advances in large language models and agent frameworks mean these tools can now handle routine sales outreach, compile cross-system reports, and trigger follow-up actions with minimal human oversight. Why this matters for

Summary AI “agents” — autonomous systems that read data, generate insights, and take actions — are moving from demos into real business use. Instead of static dashboards, companies are using agentic AI to summarize sales performance, flag at-risk deals, draft outreach, and even create tasks in CRMs automatically. The result: faster decisions, fewer manual reports,

Quick summary – Over the last 12–18 months, “AI agents”—small, task-focused AI assistants that can act across apps and data—moved from labs into mainstream products. Major vendors (Copilot-style tools, no-code agent builders, and plugin ecosystems) now let businesses automate multi-step work without full engineering projects. – These agents can do things like enrich leads, draft

Quick summary A new wave of low-code and “autonomous” AI agents is making it fast and inexpensive for companies to automate end-to-end tasks: from lead qualification and help-desk triage to cross-system reporting and order routing. These agents can read multiple data sources, call business systems, and take multi-step actions without constant human direction. Why this

Summary AI agents — autonomous software that can carry out tasks, make decisions, and interact with systems — moved from proofs-of-concept into mainstream business tools over the last 18 months. Major cloud providers rolled out agent frameworks, developer toolkits matured, and companies began using agents for customer triage, automated outreach, and on-demand reporting. Why this

Quick summary Over the last year we’ve seen autonomous AI agents — software that carries out multi-step tasks without constant human prompts — move from demos into real business use. Companies are using agents to run sales outreach sequences, generate and deliver automated reports, triage customer requests, and orchestrate routine workflows across SaaS apps. Vendors

Quick summary AI has moved past one-off chatbots and image generators. The newest wave — autonomous AI agents — combine planning, web or system access, and RAG-style data lookups to complete multi-step tasks: update CRM records, generate weekly sales reports, book meetings, and trigger automations across apps. Instead of asking a tool a single question,

Big update (short version) Major cloud and AI providers have pushed “AI agents” from research demos into easy-to-deploy products. These agents can securely connect to your CRM, spreadsheets, BI tools, and calendars to fetch data, create reports, take routine actions, and even run multi-step workflows. For businesses, that shift makes practical automation and smarter reporting

The story (short): Over the past year we’ve seen a clear shift from one-off AI features to purpose-built AI agents and low-code agent platforms. Big vendors and startups are giving companies tools to build autonomous assistants that do specific jobs — from generating weekly sales reports to triaging customer requests, drafting personalized outreach, and automating