AI Agents for Work
A practical guide to AI agents for work, with examples across sales, recruiting, marketing, operations, research, and data extraction.
The short answer
AI agents for work are most useful when they complete multi-step workflows across the tools your team already uses. The value is not another chat answer. The value is finished work.
Why teams care now
Most work is fragmented across browser tabs: inboxes, CRMs, spreadsheets, dashboards, job boards, and docs. A browser-native agent can move through those surfaces and turn them into output.
Where agents help first
The best starting workflows are repetitive, cross-tool, and easy to verify: lead research, candidate sourcing, weekly reports, competitor monitoring, and data extraction.
Bottom line
Teams should not ask where to use AI in the abstract. They should identify the browser admin they repeat every week and turn that into an agent workflow.
FAQs
Is this a replacement for a chatbot?
Not exactly. Strawberry is for browser-native work: research, tabs, connected apps, recurring routines, and finished outputs. Chatbots are better for isolated questions.
Can Strawberry run this workflow repeatedly?
Yes. Strawberry supports routines and reusable companions, so repeated sales, recruiting, research, and operations workflows can become scheduled or repeatable.
Where should I start?
Start with one workflow that already costs you time every week: lead research, candidate sourcing, competitor monitoring, inbox triage, or reporting.
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