$ man parallel-agents

Parallel Agents

Running multiple AI tasks simultaneously instead of one at a time. While one agent researches companies, another monitors campaigns, and a third drafts content. Concurrency for AI workflows.

sequential AI work is slow. if you ask Claude to research 5 companies, then check your campaign stats, then draft a LinkedIn post — that's 3 tasks in a row. with parallel agents, all 3 run at the same time. the research agent searches Exa. the monitoring agent checks Smartlead. the content agent drafts the post. you get all 3 results back in the time it would take to do one. this is especially powerful for morning ops — instead of checking each tool one by one, I launch parallel agents that check everything simultaneously and return a unified brief.

I use parallel agents in Claude Code for multi-tool operations. when I need to enrich a batch of companies, I'll spin up an Explore agent to search the codebase while a general-purpose agent runs Exa queries and another handles data processing. for daily monitoring, parallel agents check Smartlead stats, scan for new web reveals, and review overnight Slack messages — all at once. the key is knowing which tasks are independent (can run in parallel) vs dependent (need results from a previous step). research tasks are almost always parallelizable. data processing that depends on research results is not. getting this right is the difference between a 5-minute morning brief and a 30-minute manual check.