Multi-Agent AI Pipeline: Build Sequential Agent Workflows That Chain Results

TL;DR: A multi-agent pipeline runs agents in sequence where each agent receives the previous agent's output as context. Build a Research → Write → Review pipeline in 5 minutes. Cost per pipeline run: $0.10-0.25. This guide covers three pipeline patterns with exact setup steps.

Most people use one AI agent at a time. They paste a prompt, get a result, then paste that result into another prompt for the next agent. Manual. Slow. Error-prone.

A multi-agent pipeline automates this chain. Agent 1 produces output. Agent 2 receives that output as input. Agent 3 receives both. The result at the end is the combined work of all agents, each building on the last.

This guide shows you three pipeline patterns you can set up today.

Related: How to Coordinate Multiple AI Coding Agents · AI Agent Task Board · AI Agent Workflows: 10 Examples · Build AI Workflows Without Code

What Is a Multi-Agent Pipeline?

Pipeline vs Team vs Single Agent

Pattern	How It Works	Best For
Single agent	One agent handles entire task	Simple tasks, quick queries
Team	Lead agent delegates to parallel workers	Independent subtasks
Pipeline	Agents run in sequence, each feeds the next	Multi-step processes where steps depend on previous output

Pipelines excel when each step transforms or enriches the work of the previous step. Research informs writing. Writing informs review. Review produces the final output.

The Data Flow

Input → Agent 1 → Output 1 → Agent 2 → Output 2 → Agent 3 → Final Output

Each agent sees: the original task + all previous agents' outputs. This context accumulation is what makes pipelines powerful — Agent 3 benefits from the combined work of Agents 1 and 2.

Three Pipeline Patterns

Pattern 1: Research → Write → Review (Content Pipeline)

Use case: Producing researched, reviewed content automatically.

Step	Agent	Model	Cost	Time
1	Researcher	Gemini 2.5 Pro	Free	30s
2	Writer	Claude Sonnet	$0.08	90s
3	Reviewer	Claude Haiku	$0.02	20s

Total: $0.10 per piece of content, ~2.5 minutes.

Researcher prompt:

"Research the following topic and provide: key data points, current trends, competitor angles, and unique insights. Return structured findings."

Writer prompt:

"Using the research findings above, write a [blog post/report/email] about [topic]. Target audience: [description]. Tone: [professional/casual]. Length: [words]. Include specific data from the research."

Reviewer prompt:

"Review the content above for: factual accuracy against the research, grammar and readability, tone consistency, and completeness. Suggest specific improvements if needed."

Pattern 2: Analyze → Plan → Implement → Verify (Development Pipeline)

Use case: Building a feature from a high-level description.

Step	Agent	Model	Cost	Time
1	Analyst	Gemini 2.5 Pro	Free	30s
2	Architect	Claude Sonnet	$0.05	30s
3	Implementer	Claude Sonnet	$0.12	2min
4	Verifier	Claude Haiku	$0.02	20s

Total: $0.19 per feature, ~3.5 minutes.

Analyst prompt:

"Analyze the codebase for how similar features are implemented. Identify patterns, conventions, and integration points relevant to: [feature description]."

Architect prompt:

"Based on the codebase analysis, design the implementation for: [feature description]. Include: files to modify, API design, database changes, and implementation order."

Implementer prompt:

"Implement the feature following the architecture plan. Write production code with error handling. Include tests for new functionality."

Verifier prompt:

"Verify the implementation: does it match the architecture plan? Are there security issues? Do the tests cover the new functionality? Flag any problems."

Pattern 3: Discover → Diagnose → Fix → Test (Bug Fix Pipeline)

Use case: Fixing reported bugs automatically.

Step	Agent	Model	Cost	Time
1	Discoverer	Gemini 2.5 Pro	Free	30s
2	Diagnostician	Claude Sonnet	$0.05	30s
3	Fixer	Claude Sonnet	$0.10	90s
4	Tester	Claude Haiku	$0.02	20s

Total: $0.17 per bug fix, ~3 minutes.

See the full bug-fix pipeline guide: AI Agent Bug Fixing Workflow.

Setup Guide (5 Minutes)

Step 1: Create an Account

Go to ivern.ai/signup. Free, no credit card. You get 3 squads and 15 tasks.

Step 2: Add Your API Key

In Settings, add your Anthropic API key ($5 at console.anthropic.com). Keys are encrypted with AES-256.

Step 3: Create a Pipeline Squad

Click Create Squad. Choose the pipeline pattern you need:

Content Pipeline squad:

Agent Name	Model	Role
Researcher	Gemini 2.5 Pro	Gather data and insights
Writer	Claude Sonnet	Create content from research
Reviewer	Claude Haiku	Review and polish

Development Pipeline squad:

Agent Name	Model	Role
Analyst	Gemini 2.5 Pro	Codebase analysis
Architect	Claude Sonnet	Design implementation
Implementer	Claude Sonnet	Write code
Verifier	Claude Haiku	Check quality

Step 4: Assign Your First Pipeline Task

From the dashboard, create a task with the pipeline selected:

"Write a blog post about email marketing strategies for SaaS companies. Include current statistics, competitor analysis, and actionable tips for companies with under 1000 subscribers."

The task flows through Researcher → Writer → Reviewer automatically. Each agent's output streams to the dashboard in real time.

Step 5: Review the Final Output

The last agent in the pipeline produces the final deliverable. You see every agent's intermediate output on the task board, so you can trace how the result was built.

Cost Comparison: Pipeline vs Alternatives

Content Production (10 pieces/month)

Approach	Monthly Cost	Quality	Time/Piece
ChatGPT manual	$20 (subscription)	Good	45 min
Freelance writer	$500-2000	Varies	3-5 days
Jasper	$49 (subscription)	Moderate	20 min
AI Pipeline	$1-2 (API)	Very good	2.5 min

Feature Development (5 features/month)

Approach	Monthly Cost	Quality	Time/Feature
Senior developer	$8,000-15,000	High	1-3 days
Junior developer	$3,000-6,000	Moderate	3-5 days
AI Pipeline	$1 (API)	Good	3.5 min

The pipeline approach isn't replacing developers — it's handling the first draft of implementation that developers then refine.

Customizing Your Pipeline

Adding Steps

You can add more agents to any pipeline:

Research → Write → SEO Optimize → Review

Or for development:

Analyze → Plan → Implement → Security Review → Test → Deploy Plan

Each additional step adds ~$0.02-0.10 and 15-30 seconds.

Branching Pipelines

Some tasks benefit from parallel branches:

Research → [Writer 1: Blog Post]
         → [Writer 2: Email Version]
         → [Writer 3: Social Posts]
         → Review (all three outputs)

This produces multiple content formats from one research phase.

Conditional Steps

Configure the Reviewer agent to flag when the pipeline should loop:

"If the content scores below 8/10 on quality, send it back to the Writer with specific improvement notes. If 8/10 or above, approve and deliver."

Frequently Asked Questions

How is a pipeline different from just prompting the same agent multiple times?

A pipeline automates the handoff. Each agent specializes in one phase with an optimized system prompt. You set up the pipeline once, then every task flows through automatically. No manual copy-pasting between agents.

Can I use different AI providers in the same pipeline?

Yes. That's the recommended setup. Use Gemini 2.5 Pro for research (free, large context), Claude Sonnet for creative/implementation work (high quality), and Claude Haiku for review (fast, cheap). This is called cross-provider orchestration.

What if an agent in the middle produces bad output?

You can see each agent's intermediate output on the task board. If Agent 2 produces bad work, you can reject it and re-run just that step with better instructions. The pipeline continues from the corrected output.

How many agents can be in a pipeline?

There's no hard limit, but 3-5 agents is the sweet spot. More than 5 usually means the task should be split into multiple pipeline runs rather than one long chain.

Does the pipeline work for non-coding tasks?

Absolutely. The content pipeline (Research → Write → Review) works for any writing task: blog posts, reports, proposals, emails, social media content. The same pattern applies to research tasks, data analysis, and business workflows.

Get Started

1. Sign up free at ivern.ai/signup
2. Add your API key (Anthropic $5, or use Gemini for free research)
3. Choose a pipeline template — Content, Development, or Bug Fix
4. Assign your first pipeline task
5. Watch agents chain their work in real time

Stop manually passing output between AI agents. Automate the chain.

Set up your first AI pipeline →