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Future of AI Agents

Autonomous agents are moving from demos to workflows β€” here's what's next for teams.

Where we are today

Agents combine LLMs with tools: browsers, APIs, calendars, and code runners. Most production use is human-supervised β€” approve before send, review before deploy.

Multi-agent teams for research and ops.

Deeper CRM and support integrations.

Smaller, cheaper models running specialized sub-tasks.

Risks & guardrails

Hallucinated actions, data leaks, and runaway API costs. Teams need permissions, audit logs, and kill switches.

How to prepare

Start with one bounded workflow (e.g. weekly report generation). Measure time saved and error rate before expanding agent autonomy.