[AI Knowledge Point] What are Agentic Workflows?

Recently I saw an article introducing Agentic Workflows on weaviate’s blog . It was very well written and I would like to introduce it to you.

If Agent is an intelligent entity in action, then Workflows is the path it takes to complete tasks. Today, let’s talk about the logic and capabilities behind this combination, as well as why I think it has great potential✨.

What are Workflows?

Let’s talk about workflows first. We actually use workflows every day, such as filling out forms, approvals, and automatic reimbursements, with fixed rules and clear steps.

However, once the task becomes complex, such as "fixing a bug", "researching a topic", "analyzing market trends" - it cannot be done step by step, but requires:

✅Judgement 

✅ Search

✅ Reflection 

✅ Multi-step execution

At this time, traditional automation is stretched to its limits, and Agentic Workflows begins to shine.

? What are Agentic Workflows?

In a word:

Agentic Workflows = processes by which AI agents dynamically complete a series of tasks.

It is not a one-time answer like ordinary LLM, but continuous planning → use of tools → self-reflection → then action .

Imagine having an “automation intern” who not only answers your questions, but also breaks down tasks, finds tools, looks at results, and improves solutions until the goal is achieved.

? How does an Agent start moving?

Behind Agentic Workflows, there is actually a complete "AI behavior system":

? Reasoning skills

Think like a human, decompose complex tasks (task decomposition), and plan steps.

Tool use ability

It connects to search engines, databases, APIs, code executors, etc. For example, if you ask "What's wrong with this code?", it can run it first and then answer.

Memory

Remember the last conversation or failure experience to avoid repeating mistakes and achieve personalization.

Simply put: this is not a "question-and-answer robot" but an "AI assistant" with an action chain.

What are the “smart modes” in workflow?

This is particularly interesting. Agentic Workflows has three very representative working modes:

1. Planning Pattern

Break down complex problems first, such as "refactoring a piece of code" → divide it into four steps: reading, diagnosing, rewriting, and testing.

2. Tool Use Pattern

It is not a "closed-door" system. You can search for information, adjust databases, execute codes, and even send emails!

3. Reflection Pattern

Not satisfied with the result? Reflect on yourself! Find out where you went wrong and make another round of revisions. You don’t need to be watching all the time.

I personally like the reflection mechanism very much, especially in programming tasks, it feels like the AI ​​is really "learning" something.

✨ Application scenario: The key is whether you can really use it!

Here are a few use case scenarios that I think have particular potential:

? Agentic RAG

It does not simply pull data from the knowledge base, but will break down the query, determine whether the information is reliable, and rewrite the question if it is not reliable. ? It can be used in deep question and answer, law, and medical.

Agentic Research Assistant

Like Perplexity Deep Research and GPT-4 Turbo browser version: it can perform multiple rounds of searches + integration + output complete conclusions, like an intern researcher.

 Agentic Programming Assistant

For example, Claude Code and Cursor's Agent allow you to write your own code, check and rewrite the code when errors occur during operation, and help you send PR (yes, Pull Request).

What are its advantages compared to traditional processes?

✅Adaptable  : Rules are not set in stone, they will respond to changes  dynamically

✅Learn  from mistakes : the more you use it, the smarter you become, and you won’t repeat the same mistakes 

✅Handle  complex tasks : multi-step, multi-tool collaboration, much more reliable than one-time Q&A 

✅Scalability  : One agent is not enough? Get an "agent team" !

⚠️ But it’s not a panacea…

Also remind yourself: not all problems require an “intelligent agent”.

❌ It's overkill for simple tasks 

❌ The smarter it is, the harder it is to control. Permissions must be clearly defined. 

❌ Sensitive decisions cannot be completely handed over to AI

My experience is: the more complex the task, the more worthwhile it is to use Agentic Workflow; the more repetitive the process, the more suitable it is for traditional automation.

 To sum up in one sentence:

Agentic Workflow = Workflow that uses AI Agents to dynamically complete tasks

It is no longer a "tool" but more of an "actor".

If you are also exploring the use of AI for automatic programming, building assistants, and building AI applications, I recommend that you pay attention to this concept - it is likely to be one of the future main lines of Agent applications?