My vibe code mentor encouraged me to use subagents for tasks. While he used them for engineering stuff, I decided to test them with something I understood better: content strategy. In experimenting, I had a lot of fun realizing I could make mini-teams of Claude. I’m lazy about wearing all these hats myself, and it was really amazing.
WHAT ARE SUBAGENTS?
Subagents are specialized AI assistants that Claude Code can delegate tasks to. Each one operates in its own context window, separate from your main conversation. Here’s the flow:
- You → Ask Claude to do something
- Claude → Recognizes this needs a specialist and delegates to a subagent
- Subagent → Works independently in its own context
- Subagent → Returns results to Claude
- Claude → Synthesizes and presents the final output to you
Claude acts as the orchestrator - it decides when to use subagents, manages them, and consolidates their work into coherent responses.
THE TASK TOOL
When you ask Claude to use a subagent, it invokes the Task tool:
Use a subagent to research blog platforms and compare features
Claude spawns a research agent that:
- Searches the web
- Compares options
- Creates a summary
- Reports back to Claude
- Claude synthesizes and presents to you
EXAMPLE: CONTENT STRATEGY FOR THIS SITE
Here’s an example of how I used subagents for this blog:
I want to create a series of articles taking my learnings from
the various .mds I supply you + whatever makes sense to layer in
from best practices people have discovered around the web.
Use subagents to:
- Do web research on Claude best practices
- Look at Anthropic's documentation and guidelines
- Research what vibe coders are struggling with on Reddit
- Consolidate everything into themes
Give me a proposal of articles to write organized by theme.
Claude deployed multiple subagents in parallel:
I'll deploy subagents for this research:
- Research agent: Gathering Claude best practices from web
- Documentation agent: Analyzing Anthropic guidelines
- Community agent: Finding common pain points from Reddit
[45 seconds later]
Based on the agents' research, here's my proposal organized by theme...
I got a complete content strategy with 20+ article ideas organized into learning modules.
OTHER POWERFUL CONTENT-RELATED USE CASES
Research and validation:
Use a subagent to research what blog topics are trending
and find gaps in existing content
Documentation:
Use a subagent to write setup instructions based on
what we just built
Marketing copy:
Use a subagent to write meta descriptions and
social media posts for our content
WHEN TO DELEGATE VS DIRECT
Use subagents for:
- Research tasks
- Content creation
- Competitive analysis
- Idea generation
- Documentation writing
- Bulk operations
Do directly with Claude for:
- Code building
- Design decisions
- Architecture choices
- Bug fixing
- Real-time iteration
THE PARALLEL WORKFLOW (MULTI-CLAUDING)
My actual workflow building this blog:
Window 1: Claude Code
Building the homepage component...
Window 2: Claude (separate session in iTerm window)
While I build, use subagents to:
- Write 3 blog posts
- Research hosting options
- Create marketing copy
I build, subagents research and write, everything happens simultaneously. This “multi-clauding” approach lets you leverage subagents while keeping your main coding session focused.
SUBAGENT PROMPTING TIPS
Be specific about:
- Context: What background to consider
- Output format: Bullet points, paragraphs, markdown
- Length: Word count or scope
- Examples: “Like our existing posts”
- Constraints: “No technical jargon”
THE PARALLEL ADVANTAGE
Without subagents, you’re doing everything sequentially - build, then write content, then do SEO, then create marketing. It takes weeks and months.
With subagents, you parallelize. While you build the homepage, a subagent writes your about page. While you fix bugs, another researches keywords. While you style components, a third drafts blog posts.
In one night I got:
- 20+ blog posts drafted
- SEO strategy defined
- Marketing copy written
All while I focused on actually building the site. I built this entire blog in two days because I wasn’t doing everything myself, I was orchestrating subagents.
Anthropic’s multi-agent research system shows this approach can outperform single-agent systems by 90% on complex tasks. The key is parallel exploration - multiple agents tackling different aspects simultaneously.