AI Post

Big picture summary AI “agents” — autonomous workflows that combine large language models (LLMs) with data, APIs and tools — are moving rapidly from proofs-of-concept into real business use. Platforms and frameworks (agent builders, orchestration layers, and vector search for RAG) now make it practical to have AI that can read your CRM, run queries […]

Short summary AI “agents” — autonomous systems that can act across apps, fetch data, and complete tasks — have moved from demos to real business pilots. Vendors (and open-source projects) now combine large language models with retrieval-augmented generation (RAG), secure connectors, and low-code automation so agents can read your CRM, pull numbers, update systems, and

Quick summary AI agents — autonomous software that can read, decide, and act across apps — are no longer just lab experiments. Over the last year we’ve seen more companies deploy agents for tasks like lead qualification, automated outreach, cross-system reporting, and routine process steps. That shift matters because agents can reduce manual work, speed

AI agents are changing sales — practical steps for business AI, automation, and reporting Quick summary AI agents — autonomous, task-focused AI that can read your CRM, draft emails, book meetings, and create reports — are moving from demos into everyday business use. Instead of one-off prompts, companies are now connecting agents to live data

Quick summary AI agents — systems that autonomously complete multi-step tasks (think: read your CRM, draft outreach, schedule meetings, update records) — have moved from experiments into real business use. Companies are now connecting agents to calendars, CRMs, and internal data stores so the agents can act, not just advise. Why this matters for businesses

Quick summary Over the last year AI “agents” — autonomous assistants that can read your systems, take actions, and follow up — have moved from experiments to practical business tools. Major vendors and open-source frameworks now make it easier to connect agents to CRMs, calendars, knowledge bases and reporting tools. That means businesses can automate

Quick story Over the past year we’ve moved from generative AI as a writing tool to AI agents that act on your behalf inside business systems. Major vendors and startups now offer agent toolkits you can plug into CRMs, email platforms, and BI tools. Those agents can qualify leads, draft and A/B test outreach, schedule

The story in a sentence A recent wave of low‑code “custom GPTs” and AI agent tools from major vendors has made it much easier for non‑technical teams to build AI agents that automate tasks, generate reports, and act on live business data. Why this matters for your business – Faster outcomes: Sales reps and ops

A quick update (and why it matters for your business) In the last year we’ve seen a surge in practical, enterprise-ready AI agents — task-focused systems that can read your CRM, pull data from reporting systems, draft outreach, and even take multi-step actions with secure connectors. These aren’t just research demos anymore. Businesses are using

Quick summary AI “agents” — autonomous, connected AI that can read your systems, take actions, and interact with people — are no longer experiments. Low-code agent builders and pre-built connectors to CRMs, calendars, and data warehouses are letting teams automate tasks like lead follow-up, meeting summaries, and real-time sales reporting without months of engineering work.