What are Agentic-Workflows?

"Wait, this thing is making its own decisions...?"

This was my honest reaction when I, as a content marketer at Giselle, first used a "process that thinks and makes decisions on its own" - a new type of workflow.

I had started what I thought would be a routine article creation task, but the workflow suddenly decided "this approach won't resonate with readers" and began inserting additional checks and evaluations.

If you've ever felt that "even after setting up efficient workflows, you end up constantly intervening to handle irregularities," this new approach might completely overturn that concept.

The Limitations of Traditional Workflows: Barriers Revealed in Article Creation

To understand agentic workflows, let me first reflect on the traditional process I use daily for "article creation."

Until now, article creation followed this fixed flow:

1. Research and information gathering
2. Article structure creation
3. Draft writing
4. Editing and tone adjustment
5. CMS formatting

While this appears efficient, I regularly encountered problems like these:

• Issues discovered at Step 1: "Oh, this angle doesn't have enough information. Back to theme setting..."
• Problems realized at Step 3: "Now that I'm writing, this is getting too technical compared to what I intended. Need to adjust from the structure..."
• Discoveries at Step 4: "After editing, the overall tone is inconsistent. Need to fix from the writing stage..."

In other words, "problems discovered in later stages → returning to earlier stages" happened frequently. This was because each step operated independently, lacking a function to oversee and make decisions about the entire process.

Humans basically manage workflows chronologically, focusing on "the current step," which leads to situations like "only realizing structural problems when writing" or "discovering information gaps only during editing." Traditional workflows lacked the ability to predict the interrelationships and impacts between different stages in advance.

Most exhausting of all was constantly worrying during work: "Will I be able to create a structure with this amount of information?" "Will this structure resonate with readers?" "Is it okay to continue writing like this?" - humans had to keep stopping at each stage to make anxious judgments.

When Processes Started Thinking: My Agentic Workflow Experience

Facing these challenges, I decided to try agentic workflows with Giselle.

Initially, I was skeptical. "How is this different from traditional article creation flows?" But when I actually ran it, it was clearly something different.

Experience 1: Dynamic Decision-Making During Research

This happened when I was creating an "AI Tool Comparison Article."

Normally, the process would go "Research → Structure → Writing," but I noticed that the agentic workflow had collected far more detailed technical materials than I had planned. When I checked Giselle's logs to understand why:

"The collected information is too superficial (expertise score 30%). Based on reader search intent analysis, more technical detailed information is needed. Executing additional specialized resource investigation."

It had made this decision and automatically shifted the research approach toward deeper investigation. I didn't instruct this. The workflow itself had determined that "this level of information would result in low article value" and switched to higher-quality information gathering.

As a result, instead of the initially planned "tool feature comparison," it became a deep article including "technical considerations during implementation."

Experience 2: Compatibility Checking During Structure Creation

Another impressive experience occurred when creating an article about "Marketing Strategy."

During the structure creation phase, I noticed that the created structure had been adjusted to be more beginner-friendly than usual. When I checked Giselle's logs:

"The created structure is too biased toward technical terminology (readability score 45%). Adjustment needed to suit the intended readers (marketing beginners to intermediate level)."

I discovered it had made this judgment. Traditionally, I would realize "this structure is too difficult for beginners" during the writing stage and manually adjust the structure. However, the agentic workflow had evaluated reader compatibility at the structure creation point and automatically adjusted the structure level.

Experience 3: Real-time Tone Consistency Management During Writing

The most surprising experience occurred during the writing phase.

When creating an "Enterprise Solution Introduction" article, I felt that the overall tone was naturally becoming unified as the writing progressed. When I later checked the logs, it appeared that the workflow had made the following decision midway:

"Tone inconsistency detected in written sections (formality level: Section 1 at 80%, Section 2 at 45%). Executing tone adjustment to maintain overall consistency."

It then automatically adjusted to a unified business tone throughout, resulting in a highly readable article.

Previously, I would notice "the tone is inconsistent" during the editing stage, then need to manually adjust the entire piece. However, the agentic workflow had been monitoring tone consistency in real-time during writing and optimizing it.

The True Nature of "Thinking Processes": Fundamental Differences from Traditional Approaches

Through these experiences, the essence of agentic workflows became clear to me.

Traditional Workflows: Fixed Rails

A → B → C → D

• Each step operates independently
• Proceeds according to pre-designed human routes
• Even when problems arise, the process itself doesn't change
• Humans monitor and manually intervene as needed

Agentic Workflows: Thinking Rails

A → [Decision] → B or B' → [Evaluation] → C or Return → [Optimization Decision] → D

• Situation evaluation and decision-making at each step
• Real-time route changes
• Self-checking quality and goal achievement
• Humans provide direction while fine adjustments happen automatically

In other words, agentic workflows mean "giving thinking ability to the process itself."

Traditional Workflow vs Agentic Workflow Comparison

Business Process Revolution: Applications Beyond Article Creation

This concept of "thinking processes" brings revolutionary changes to business processes beyond article creation.

1. Customer Support Response

Customer inquiry handling has traditionally been dominated by the fixed approach of "classifying and routing to appropriate staff." However, agentic workflows enable instant analysis of inquiry content and urgency, allowing for dynamic selection of optimal response strategies.

Traditional: Inquiry received → Classification → Staff assignment → Response → Completion
Agentic: Inquiry received → [Urgency/complexity analysis] → Optimal response method selection → [Customer satisfaction prediction] → Approach adjustment as needed → Completion

2. Product Development Process

In new product or service development, it's not uncommon to need directional adjustments from the planning stage due to market need changes or technical challenges. Agentic workflows can evaluate market data and progress at each development stage, and automatically determine when to pivot or conduct additional research as needed.

Traditional: Market research → Planning → Development → Testing → Launch
Agentic: Market research → [Needs depth analysis] → Planning adjustment → Development → [Mid-stage pivot evaluation] → Additional research or continue development → Launch

3. Sales Process

In sales activities, the optimal approach method often differs for each prospect, and traditionally this process has relied heavily on experience and intuition. Agentic workflows make it possible to analyze lead characteristics and response patterns, adjusting strategies in real-time.

Traditional: Lead acquisition → Approach → Proposal → Closing
Agentic: Lead acquisition → [Prospect score analysis] → Approach method optimization → [Response pattern evaluation] → Proposal content adjustment → Closing

4. Marketing Campaign Management

In marketing campaigns, strategic adjustments during execution are often required due to target audience reactions and market trend changes. Agentic workflows can monitor performance in real-time and perform dynamic optimization based on data.

Traditional: Campaign planning → Content creation → Launch → Performance tracking → Report
Agentic: Campaign planning → [Audience segment analysis] → Content personalization → Launch → [Real-time performance monitoring] → Dynamic optimization → [Predictive trend analysis] → Continuous improvement

5. Documentation and Knowledge Management

In organizational documentation, optimization according to information update frequency and usage patterns is often a challenge. By utilizing agentic workflows, it becomes possible to analyze context for automatic updates and continuously improve based on usage patterns.

Traditional: Document creation → Review → Approval → Storage → Periodic updates
Agentic: Document creation → [Context analysis] → Auto-generation → [Accuracy verification] → Dynamic updates → [Usage pattern analysis] → Continuous optimization

6. Content Creation and SEO Optimization

In content creation, SEO strategy adjustments are sometimes frequently needed due to search engine algorithm changes and competitive situations. Agentic workflows are expected to enable dynamic optimization throughout the entire process from search intent analysis to performance monitoring.

Traditional: Topic planning → Content creation → Publication → SEO review → Performance analysis
Agentic: Topic planning → [Search intent analysis] → Content creation → [Real-time SEO optimization] → Publication → [Performance monitoring] → Content adjustment → [Trend prediction] → Strategic updates

7. Data Analysis and Reporting

In data analysis work, there's often a need to continuously verify data quality and analysis result validity, and traditionally this process has heavily depended on human checks. Agentic workflows can incorporate automated judgment processes from data quality evaluation to insight verification.

Traditional: Data collection → Analysis → Report creation → Presentation → Archive
Agentic: Data collection → [Data quality assessment] → Analysis → [Pattern recognition] → Report generation → [Insight validation] → Presentation → [Action recommendation] → Continuous monitoring

8. Project Management and Team Coordination

In project management, there are frequently scenarios where plan adjustments are needed due to resource constraints or schedule changes. By utilizing agentic workflows, proactive adjustments can be expected through progress prediction and risk analysis.

Traditional: Project planning → Task assignment → Progress tracking → Status meetings → Completion
Agentic: Project planning → [Resource optimization] → Task assignment → [Progress prediction] → Real-time adjustments → [Team collaboration analysis] → Status optimization → [Risk mitigation] → Adaptive completion

9. Quality Assurance and Testing

In software development quality assurance, test strategy adjustments are often required according to code complexity and project characteristics. Agentic workflows are expected to enable predictive quality management using risk evaluation-based test generation and historical data.

Traditional: Test planning → Test execution → Bug reporting → Fix verification → Release approval
Agentic: Test planning → [Risk assessment] → Automated test generation → [Intelligent execution] → Bug analysis → [Priority scoring] → Fix verification → [Regression prediction] → Continuous improvement

Common to all cases is that processes evaluate situations and adjust themselves seeking optimal results.

Implementation Reality: Designing "Thinking Processes" with Giselle

You might wonder, "I understand the theory, but how do you actually create this?"

Giselle's appeal is that you can visually design these complex "thinking processes."

Using my article creation workflow as an example:

• Research Node: "Executes information gathering and data collection for the article"
• Information Quality Evaluation Node: "Evaluates whether collected information is sufficient for the article's purpose and identifies gaps"
• Structure Creation Node: "Creates the article outline and overall structure"
• Reader Compatibility Check Node: "Determines if structure and content suit the intended readers and decides adjustment approaches as needed"
• Writing Node: "Executes the actual article writing based on the approved structure"
• Consistency Monitoring Node: "Real-time evaluation of whether content during writing maintains tone and logical consistency"
• Optimization Decision Node: "Determines at each stage whether route changes are needed for better results"

You connect these nodes with lines and set conditional branches like "if this happens, proceed to this route." It's like drawing a flowchart where you can visually build "thinking processes."

No technical knowledge required. You simply express human thinking logic visually as workflows: "in this situation, I want this kind of decision."

The Future Brought by Agentic Workflows

After using agentic workflows for several months, my way of working has fundamentally changed.

Role Changes

Previous me: Process executor + monitor + adjuster
Current me: Strategic planner + quality manager

Fine decisions and adjustments are handled by the workflow, allowing me to focus on higher-level decisions—"what value to provide readers" and "what message to convey."

Productivity Changes

Article creation time was naturally reduced, but even more valuable is the reduction in mental burden.

Released from vague anxieties, I can now focus on creative aspects.

Quality Changes

Since workflows themselves have quality management functions, a certain level of quality is guaranteed. Work that previously had human oversights and inconsistencies is now standardized at the process level.

Final Thoughts: Working in the Era of "Thinking Processes"

"What are agentic workflows?"

My answer to this question is:

"A system that gives intelligence to processes themselves, collaborating with humans while pursuing optimal results."

This isn't just an automation tool. It's our thinking partner and collaborator for producing better results.

If traditional workflows are about "walking a predetermined path," agentic workflows are about "choosing the optimal path while walking toward the destination."

And this technology is already accessible through platforms like Giselle. Even without special technical knowledge, you can transform your business processes into "thinking processes."

The era of "thinking processes" has already begun. Why not experience this new way of working yourself?

Learning Resources: This article is designed to help Giselle users become familiar with key terminology, enabling more effective and efficient use of our platform. For the most up-to-date information, please refer to our official documentation and resources provided by the vendor.