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Agent communication basics

Intermediateโฑ 10 min read๐Ÿ“… Updated: 2026-02-17

๐Ÿ’ฌ Introduction โ€“ Agents Need to Talk!

Single agent alone work pannalaam. But multiple agents collaborate pannanum na, communication essential! ๐Ÿค


Think of it like a team project:

  • ๐Ÿ‘จโ€๐Ÿ’ผ Manager assigns tasks
  • ๐Ÿ‘ฉโ€๐Ÿ’ป Developer builds features
  • ๐Ÿงช Tester finds bugs
  • ๐Ÿ“ Writer creates docs

They all need to communicate to succeed! Same for AI agents! ๐Ÿค–๐Ÿ’ฌ๐Ÿค–


Agent Communication = How agents share information, coordinate tasks, and collaborate to achieve goals.


This article covers:

  • ๐Ÿ“จ Message passing fundamentals
  • ๐Ÿ”„ Communication patterns
  • ๐Ÿ“‹ Protocols and standards
  • ๐Ÿค Coordination strategies
  • โš ๏ธ Common pitfalls

๐Ÿ“จ Message Passing Fundamentals

Basic unit of agent communication = Message


Message Structure:

code
{
  "from": "researcher_agent",
  "to": "writer_agent",
  "type": "task_result",
  "content": "Found 5 key trends in AI...",
  "metadata": {
    "timestamp": "2026-02-17T10:30:00",
    "priority": "high",
    "task_id": "research-001"
  }
}

Message Types:


TypePurposeExample
**Task Assignment**Delegate work"Research this topic"
**Task Result**Return findings"Here are the results"
**Status Update**Progress report"50% complete"
**Query**Ask for info"What's the deadline?"
**Response**Answer query"Deadline is Friday"
**Error**Report problem"API call failed"
**Coordination**Synchronize"Ready for next step"

Every message should have: sender, receiver, type, content, timestamp! ๐Ÿ“จ

๐Ÿ”„ Communication Patterns

Pattern 1: Request-Response ๐Ÿ”„

code
Agent A: "Search for AI trends" โ†’
Agent B: โ† "Here are 5 trends: ..."

Simple, synchronous. One asks, one answers.


Pattern 2: Publish-Subscribe ๐Ÿ“ข

code
Agent A publishes: "New data available"
Agent B (subscribed): Receives notification
Agent C (subscribed): Receives notification
Agent D (not subscribed): Doesn't know

One-to-many communication. Great for events.


Pattern 3: Broadcast ๐Ÿ“ก

code
Manager: "Meeting at 3 PM" โ†’ ALL agents

One agent sends to all. For important announcements.


Pattern 4: Pipeline (Chain) โ›“๏ธ

code
Agent A โ†’ output โ†’ Agent B โ†’ output โ†’ Agent C

Sequential processing. Each agent adds value.


Pattern 5: Blackboard ๐Ÿ“‹

code
Shared Space (Blackboard):
- Agent A writes research findings
- Agent B reads findings, writes analysis
- Agent C reads analysis, writes report

Indirect communication via shared space.


PatternBest ForCoupling
Request-ResponseDirect queriesTight
Pub-SubEvent notificationsLoose
BroadcastTeam announcementsLoose
PipelineSequential workflowsMedium
BlackboardCollaborative workLoose

๐Ÿ—๏ธ Agent Communication Architecture

๐Ÿ—๏ธ Architecture Diagram
```
โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”
โ”‚            COMMUNICATION LAYER              โ”‚
โ”‚                                             โ”‚
โ”‚  โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”   โ”‚
โ”‚  โ”‚       ๐Ÿ“ฌ MESSAGE BUS / BROKER        โ”‚   โ”‚
โ”‚  โ”‚  Route โ”‚ Queue โ”‚ Prioritize โ”‚ Log    โ”‚   โ”‚
โ”‚  โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜   โ”‚
โ”‚         โ”‚            โ”‚          โ”‚            โ”‚
โ”‚   โ”Œโ”€โ”€โ”€โ”€โ”€โ–ผโ”€โ”€โ”€โ”€โ”€โ” โ”Œโ”€โ”€โ”€โ–ผโ”€โ”€โ”€โ”€โ” โ”Œโ”€โ”€โ–ผโ”€โ”€โ”€โ”€โ”€โ”€โ”    โ”‚
โ”‚   โ”‚ ๐Ÿ‘จโ€๐Ÿ’ผ Managerโ”‚ โ”‚๐Ÿ”Researchโ”‚ โ”‚โœ๏ธ Writer โ”‚    โ”‚
โ”‚   โ”‚  Agent    โ”‚ โ”‚  Agent  โ”‚ โ”‚  Agent  โ”‚    โ”‚
โ”‚   โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜    โ”‚
โ”‚         โ”‚            โ”‚          โ”‚            โ”‚
โ”‚   โ”Œโ”€โ”€โ”€โ”€โ”€โ–ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ–ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ–ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”   โ”‚
โ”‚   โ”‚       ๐Ÿ“‹ SHARED STATE / MEMORY       โ”‚   โ”‚
โ”‚   โ”‚  Task Board โ”‚ Results โ”‚ Context      โ”‚   โ”‚
โ”‚   โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜   โ”‚
โ”‚                                             โ”‚
โ”‚   โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”   โ”‚
โ”‚   โ”‚       ๐Ÿ“Š MONITOR & LOGGING          โ”‚   โ”‚
โ”‚   โ”‚  Message count โ”‚ Latency โ”‚ Errors   โ”‚   โ”‚
โ”‚   โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜   โ”‚
โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜
```

๐Ÿค Coordination Strategies

Multiple agents coordinate panna different strategies irukku:


1. Centralized Coordination ๐Ÿ‘‘

  • One manager agent controls everything
  • Sub-agents report to manager
  • Manager decides next steps

ProsCons
Clear controlSingle point of failure
Easy to trackManager bottleneck
PredictableLess flexible

2. Decentralized Coordination ๐ŸŒ

  • No single controller
  • Agents negotiate with each other
  • Consensus-based decisions

ProsCons
No bottleneckHarder to track
Fault tolerantPotential conflicts
ScalableMore complex

3. Hybrid Coordination ๐Ÿ”„

  • Manager for high-level planning
  • Peer-to-peer for execution details
  • Best of both worlds!

Recommendation: Start with centralized (simpler), move to hybrid for production! ๐ŸŽฏ

๐ŸŽฌ Communication in Action โ€“ Customer Support

โœ… Example

Multi-Agent Customer Support System:

code
[Customer]: "My order #456 hasn't arrived and I was charged twice"

[Router Agent] โ†’ Classifies: ORDER_ISSUE + BILLING_ISSUE
  โ†’ Sends to Order Agent + Billing Agent (parallel)

[Order Agent]:
  โ†’ Queries order DB
  โ†’ Message to Router: "Order #456 shipped, delayed due to weather.
     ETA: Feb 19. Tracking: TRK789"

[Billing Agent]:
  โ†’ Queries payment DB
  โ†’ Message to Router: "Double charge confirmed. 
     Refund of โ‚น1,500 initiated. Ref: REF-321"

[Router Agent] โ†’ Combines responses
  โ†’ Sends to Response Agent

[Response Agent] โ†’ Crafts unified reply:
"Hi! I checked your order #456 โ€“ it's on the way, delayed 
by weather (ETA Feb 19, tracking: TRK789). I also found the 
double charge and initiated a โ‚น1,500 refund (Ref: REF-321). 
Should arrive in 3-5 business days. Anything else? ๐Ÿ˜Š"

4 agents, 1 seamless response! โœจ

๐Ÿ“‹ Communication Protocols

Agents communicate panna standardized protocols help pannum:


1. Natural Language Protocol ๐Ÿ’ฌ

  • Agents chat in plain text
  • Flexible but ambiguous
  • Best for: Creative collaboration

2. Structured Message Protocol ๐Ÿ“Š

json
{
  "action": "SEARCH",
  "params": {"query": "AI trends", "limit": 5},
  "response_format": "JSON"
}
  • Clear, unambiguous
  • Best for: Tool-using agents

3. Function Calling Protocol ๐Ÿ”ง

  • Agent A calls Agent B as a function
  • Typed inputs/outputs
  • Best for: Tight integration

4. Event-Driven Protocol ๐Ÿ“ก

code
Event: "new_data_available"
Payload: {"source": "api", "records": 100}
Subscribers: [analyst_agent, report_agent]
  • Loose coupling
  • Best for: Scalable systems

ProtocolReliabilityFlexibilityComplexity
Natural LanguageLowHighLow
Structured MessageHighMediumMedium
Function CallingVery HighLowMedium
Event-DrivenHighHighHigh

โš ๏ธ Communication Challenges

Challenge 1: Context Loss ๐Ÿ“‰

Agent A knows something, but forgets to tell Agent B

*Fix:* Explicit context passing in every message


Challenge 2: Message Ordering ๐Ÿ”ข

Messages arrive out of order

*Fix:* Timestamps + sequence numbers + message queue


Challenge 3: Infinite Loops ๐Ÿ”„

Agent A asks B, B asks A, A asks B...

*Fix:* Max message count per task, loop detection


Challenge 4: Conflicting Instructions โš”๏ธ

Agent A says "use formal tone", Agent B says "use casual"

*Fix:* Priority hierarchy, manager as tiebreaker


Challenge 5: Information Overload ๐ŸŒŠ

Too many messages overwhelm agent's context window

*Fix:* Message summarization, relevance filtering


Challenge 6: Latency โฑ๏ธ

Each agent interaction adds latency

*Fix:* Parallel communication, async processing


Prevention checklist:

  • โœ… Clear message format defined
  • โœ… Max iterations per conversation set
  • โœ… Context explicitly passed
  • โœ… Error handling for communication failures
  • โœ… Monitoring for unusual patterns

๐Ÿงช Try It โ€“ Simulate Agent Communication

๐Ÿ“‹ Copy-Paste Prompt
```
Simulate a 3-agent system handling this task:
"Analyze last month's sales data and create a presentation"

AGENTS:
1. DATA_AGENT: Accesses databases, runs queries
2. ANALYST_AGENT: Interprets data, finds insights
3. PRESENTER_AGENT: Creates slides and visuals

RULES:
- Show each message between agents
- Format: [SENDER โ†’ RECEIVER]: "message"
- Show at least 8 messages
- Include one error scenario and recovery

START:
[MANAGER โ†’ DATA_AGENT]: "Fetch last month's sales data 
from the database"

Continue the conversation...
```

Great way to understand multi-agent communication flow! ๐Ÿ”„

๐Ÿ› ๏ธ Tools for Agent Communication

Tool/FrameworkCommunication StyleBest For
**CrewAI**Role-based delegationSimple teams
**AutoGen**ConversationalChat-based collaboration
**LangGraph**State-based routingComplex workflows
**Swarm**Lightweight handoffsSimple agent switching
**RabbitMQ**Message queueProduction messaging
**Redis Pub/Sub**Event-drivenReal-time events
**gRPC**Function callsHigh-performance

For beginners: CrewAI or AutoGen โ€“ built-in agent communication! ๐Ÿš€

For production: LangGraph + Redis/RabbitMQ โ€“ scalable and reliable! ๐Ÿข

๐Ÿ’ก Communication Best Practices

๐Ÿ’ก Tip

1. Keep messages concise โ€“ Essential info only, no filler

2. Use structured formats โ€“ JSON > free text for reliability

3. Include context โ€“ Don't assume other agent knows everything

4. Set timeouts โ€“ Don't wait forever for a response

5. Log everything โ€“ Debug communication issues easily

6. Idempotent messages โ€“ Same message twice = same result

7. Acknowledge receipt โ€“ Confirm message received before processing

8. Version your protocols โ€“ Evolve without breaking existing agents

๐Ÿ”’ Security in Agent Communication

Agent communication secure pannanum:


ThreatRiskMitigation
**Message tampering**Altered instructionsMessage signing
**Impersonation**Fake agent sends messagesAuthentication tokens
**Eavesdropping**Sensitive data interceptedEncryption (TLS)
**Injection**Malicious prompts injectedInput validation
**DoS**Flood of messagesRate limiting

Minimum security:

  • โœ… Authenticate every agent (API keys/tokens)
  • โœ… Validate all incoming messages
  • โœ… Encrypt sensitive data in transit
  • โœ… Rate limit message frequency
  • โœ… Audit log all communications

๐Ÿ“ Summary

Key Takeaways:


โœ… Agent communication = Messages with sender, receiver, type, content

โœ… 5 Patterns: Request-Response, Pub-Sub, Broadcast, Pipeline, Blackboard

โœ… Coordination: Centralized (simple) โ†’ Hybrid (production)

โœ… Protocols: Natural Language, Structured, Function Call, Event-Driven

โœ… Challenges: Context loss, ordering, loops, conflicts, overload

โœ… Security: Authentication, encryption, validation, rate limiting

โœ… Tools: CrewAI/AutoGen (simple), LangGraph+Redis (production)


Next article la APIs inside Agents paapom โ€“ agents external services epdi use pannเฏเฎฎเฏ! ๐Ÿ”Œ

๐Ÿ ๐ŸŽฎ Mini Challenge

Challenge: Design Agent Communication Protocol


Multi-agent system-ku communication protocol design panni structure define:


Scenario: 3-agent blog writing team (Researcher, Writer, Editor)


Step 1: Define Message Structure (4 mins)

Standard JSON message template create:

json
{
  "from": "researcher_agent",
  "to": "writer_agent",
  "type": "task_result",
  "task_id": "blog_001",
  "content": "Found 5 key trends...",
  "priority": "high",
  "timestamp": "2026-02-23T10:30:00",
  "requires_ack": true
}

Step 2: Define Communication Patterns (4 mins)

Researcher โ†’ Writer โ†’ Editor โ†’ User


Pattern: Pipeline (sequential)

  • Researcher finishes โ†’ sends to Writer
  • Writer finishes โ†’ sends to Editor
  • Editor finishes โ†’ sends to User

Step 3: Error Handling Protocol (3 mins)

  • Message timeout? โ†’ Retry 3 times
  • Agent not responding? โ†’ Escalate to human
  • Invalid message format? โ†’ Request reformat
  • Low quality output? โ†’ Request improvement

Step 4: Implement Message Flow (3 mins)

Pseudo-code:

code
Researcher executes research
โ”œโ”€ Creates message {"content": research_results}
โ”œโ”€ Sends to Writer queue
โ””โ”€ Waits for ack

Writer receives message
โ”œโ”€ Processes research_results
โ”œโ”€ Creates message {"content": draft}
โ”œโ”€ Sends to Editor queue
โ””โ”€ Waits for feedback

Editor receives message
โ”œโ”€ Reviews draft
โ”œโ”€ Sends final approval message
โ””โ”€ User gets result

Communication protocol complete! ๐Ÿ“จ

๐Ÿ’ผ Interview Questions

Q1: Agents epdi effectively communicate pannum?

A: Structured messages: sender, receiver, type, content, metadata. Ambiguity avoid. Context loss prevent. Protocol define. Example: {"from": "Agent A", "to": "Agent B", "type": "task", "content": {...}}


Q2: Agent communication patterns โ€“ when which use?

A:

  • Request-Response: Simple, synchronous, 1-1 communication
  • Pub-Sub: Events, broadcasting, decoupling
  • Pipeline: Sequential workflow (blog writing)
  • Blackboard: Shared state (collaborative)
  • Hybrid: Complex systems

Choose based on workflow type!


Q3: Agent communication la biggest challenge?

A: Context loss! Agent A-ku therinja details Agent B-ku clear auto come through? Illa! Explicitly pass pannanum. Standardized message format + comprehensive context = critical!


Q4: 10 agents communicate pannaa enna aagum?

A: Communication explosion! 10 agents = potential 45 message paths! Complexity, latency, cost explode. Solution: Hierarchical communication (central coordinator) or pub-sub (event-driven) use!


Q5: Agent communication security?

A:

  • Authentication: Verify sender identity
  • Encryption: Protect message content
  • Validation: Verify message structure
  • Rate limiting: Prevent spam
  • Audit logs: Track all communication

Production systems: All 5 implement pannum must! ๐Ÿ”’

โ“ Frequently Asked Questions

โ“ Agents epdi oruthu oruthu kitta pesเฏเฎฎเฏ?
Message passing, shared memory, event systems, or direct function calls. Most common method is structured message passing โ€“ JSON messages with role, content, and metadata.
โ“ Agent communication la biggest challenge enna?
Context loss between agents. Agent A ku therinja info Agent B ku theriyaadhu unless explicitly passed. Shared context management critical.
โ“ Human language la agents communicate pannuma?
Yes and No. Inter-agent messages can be natural language (LLM-to-LLM) or structured data (JSON/protocol buffers). Structured is more reliable, natural language is more flexible.
โ“ How many agents can communicate simultaneously?
Technically unlimited, but practically 3-10 agents optimal. More agents = more communication overhead = slower and more expensive.
๐Ÿง Knowledge Check
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