What Are Agentic Workflows? The Complete Explainer

Agentic workflows are AI-driven processes where autonomous agents plan, execute, and adapt multi-step tasks without human intervention at each stage. Unlike traditional automation that follows rigid scripts, agentic workflows can handle unexpected situations, make decisions, and self-correct.

This is the most significant shift in enterprise automation since the cloud. Here's what you need to know.

From Scripts to Agents

Traditional Automation

Traditional automation follows if-then logic:

IF new lead in CRM
THEN send welcome email
IF email opened
THEN add to nurture sequence

It's powerful for predictable, repetitive tasks. But it breaks when:

• Inputs vary unexpectedly
• Decisions require judgment
• Processes need adaptation
• Errors need intelligent handling

Agentic Workflows

Agentic workflows use AI agents that:

• Understand intent - Parse natural language instructions
• Plan execution - Break down goals into steps
• Take actions - Execute through tools and APIs
• Observe results - Monitor outcomes
• Adapt behavior - Adjust based on feedback

The difference is autonomy. An agent decides how to accomplish a goal, not just whether conditions are met.

How Agentic Workflows Work

The Agent Loop

Every agentic workflow follows a core loop:

1. Receive Goal
2. Plan Approach
3. Execute Step
4. Observe Result
5. Decide Next Action
6. Repeat until complete

Example: Research a Company

Goal: "Research Acme Corp for our upcoming call"

Agent process:

1. Search for Acme Corp website → Found acmecorp.com
2. Extract company description → "B2B SaaS for HR"
3. Search for recent news → Found funding announcement
4. Check LinkedIn for key people → Found CEO, CTO profiles
5. Search for technology stack → Found Salesforce, AWS
6. Compile research summary → Delivered to user

At each step, the agent decides what to do next based on what it learned.

Components of an Agentic Workflow

1. The Agent Brain Usually a large language model (LLM) that reasons about tasks and decides actions.

2. Tools Capabilities the agent can use:

• Web search
• Database queries
• API calls
• File operations
• Communication channels

3. Memory State that persists across steps:

• Short-term: Current task context
• Long-term: Learned patterns, user preferences

4. Orchestration Logic that manages:

• Multi-step execution
• Error handling
• Timeout management
• Human escalation

Agentic vs Traditional: A Comparison

Aspect	Traditional Automation	Agentic Workflows
Input	Structured data	Natural language
Logic	Predefined rules	AI reasoning
Flexibility	Rigid paths	Adaptive
Error Handling	Fail or escalate	Self-correct
Complexity	Linear increase	Handles well
Setup	Code/configure	Describe goal

Real-World Agentic Workflows

Sales Prospecting

Traditional approach:

1. Export list from database
2. Manually enrich each company
3. Find contacts on LinkedIn
4. Copy to spreadsheet
5. Upload to CRM

Agentic approach: "Find 50 Series A fintech companies in the US hiring for sales, with verified emails for the VP of Sales, and add to HubSpot."

Agent handles all steps autonomously, adapting when data is missing or sources fail.

Customer Support

Traditional approach:

• Route ticket based on keywords
• Surface relevant KB articles
• Escalate if no match

Agentic approach: "Resolve customer issues by understanding context, searching knowledge base, checking account status, and taking appropriate action. Escalate complex issues to humans."

Agent reads tickets, understands nuance, takes actions (refunds, account changes), and knows when to escalate.

Report Generation

Traditional approach:

• Pull data from fixed queries
• Apply template formatting
• Send on schedule

Agentic approach: "Create weekly sales report highlighting pipeline changes, deal risks, and recommended actions for leadership."

Agent queries multiple systems, analyzes patterns, generates insights, and adapts the report format based on what's important that week.

Building Agentic Workflows

Step 1: Define the Goal

Be specific about outcomes, flexible about methods:

Good: "Qualify inbound leads by researching their company, assessing fit against our ICP, and routing qualified leads to the right rep."

Bad: "Process leads" (too vague)

Step 2: Identify Required Tools

What capabilities does the agent need?

• Data sources (CRMs, databases, APIs)
• Actions (send email, update records, notify humans)
• Information gathering (web search, document reading)

Step 3: Set Boundaries

Define what the agent can and cannot do:

• Budget limits (max credits per task)
• Action limits (never delete data without approval)
• Escalation triggers (when to involve humans)

Step 4: Build Incrementally

Start with simple workflows and add complexity:

Week 1: Agent researches companies Week 2: Add lead scoring Week 3: Add CRM integration Week 4: Add email drafting

Step 5: Monitor and Improve

Track agent performance:

• Success rate
• Time to completion
• Error frequency
• Human escalation rate

Use insights to refine prompts, add tools, and improve boundaries.

Common Agentic Workflow Patterns

Pattern 1: Research and Report

Goal → Gather Information → Analyze → Synthesize → Deliver

Best for: Competitive analysis, prospect research, market scanning

Pattern 2: Triage and Route

Input → Classify → Prioritize → Route → Track

Best for: Customer support, lead routing, issue management

Pattern 3: Monitor and Alert

Watch Sources → Detect Changes → Evaluate Significance → Notify

Best for: Competitor tracking, signal detection, compliance monitoring

Pattern 4: Process and Transform

Receive Data → Validate → Enrich → Transform → Deliver

Best for: Data pipelines, document processing, format conversion

Pattern 5: Coordinate and Execute

Plan → Delegate → Monitor → Aggregate → Report

Best for: Multi-agent systems, complex workflows, project coordination

Challenges and Limitations

1. Reliability

Agents can fail unexpectedly. Build robust error handling and human fallbacks.

2. Latency

Multi-step reasoning takes time. Set expectations and optimize critical paths.

3. Cost

LLM calls add up. Monitor usage and optimize for efficiency.

4. Transparency

Agent reasoning can be opaque. Log everything for debugging and auditing.

5. Control

Balancing autonomy with oversight is hard. Start conservative, expand gradually.

The Future of Agentic Workflows

We're in the early innings. What's coming:

• Standardized agent protocols - Common ways to build and connect agents
• Agent marketplaces - Pre-built agents for common workflows
• Self-improving agents - Systems that optimize their own performance
• Cross-organization agents - Agents that work across company boundaries
• Regulatory frameworks - Standards for enterprise agent deployment

Getting Started

If you're new to agentic workflows:

1. Pick one high-value, repetitive task to automate
2. Use a proven platform (Origami, Lindy, LangChain)
3. Start with human oversight at every step
4. Gradually increase autonomy as trust builds
5. Measure relentlessly to prove value

The teams that master agentic workflows will operate at a fundamentally different level of efficiency. The window to be early is still open.

---

Ready to build agentic workflows for sales?

Start Free 7-Day Trial (1,000 Credits) →