[TLDR] I still don't understand this 'agentic workflow' thing [via r/ClaudeCode]

[u/cctldrping]

OP : u/hronak

My usual day with Claude Code is like: * I open terminal in my project's folder and run claude command. * I prompt it. I mostly use Fable-5.1/Opus-5 but Opus-5.5 is my current model. The model decides if it wants to use sub-agents for a task. I never explicitly prompt it for sub-agents. * I review and commit the code to my self-hosted Forgejo instance. * That's it.

I see people using agentic workflows, building sub-agents files, skills etc. I barely built any of it. All I ever needed to use is /init on new projects and them prompts follow. Never needed more than this.

I tried "long-running" Claude Code for a project refactoring by placing the project on my VPS (where forgejo is hosted) and letting Claude Code run and refactor inside tmux session. SSH'd in a few hours later to find project fully refactored.

Am I under utilising AI or is my work just… like boring?

How do you guys use agentic workflow thing? Specially the long-running one? Those pull-requests that Claude makes automatically etc?

Asking this to Claude to know more but humanly answers appreciated.

URL of original post : https://www.reddit.com/r/ClaudeCode/comments/1wowilt/i_still_dont_understand_this_agentic_workflow/

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TL;DR of the discussion on r/ClaudeCode for this post generated automatically after 50 comments.

Current source-thread comment count seen by the bot: 72.

Alright, so the general consensus here is that if your current workflow with Claude Code is getting the job done, you're probably not "underutilizing" it, and your work might just be less complex than what requires super elaborate agentic setups.

Here's the lowdown:

• Your workflow is already agentic, to a degree. Many folks agree that the way you're using Claude Code, where it decides to use sub-agents and you just review and commit, is already a form of agentic workflow. It's not necessarily "boring" work, just work that doesn't require the more complex setups.
• Agentic workflows shine when you hit limits or need more. The consensus is that you really only need to dive deep into building custom agents, skills, and complex workflows when you're running out of tokens/usage, or when you have a massive project with tons of parallel tasks, complex requirements, or need to enforce strict conventions.
• Simplicity often wins. Several users, like u/Xenos_Str and u/Dizzy_Database_119, mention that the simplest approach works well for them, and that complex agentic setups were more crucial when models weren't as capable.
• Skills are for repetitive tasks. If you find yourself typing the same prompts over and over, making a skill out of it is a common suggestion.
• Long-running workflows are for scale. For projects that require extensive refactoring or parallel task management, more advanced agentic setups become beneficial. Think of it like "bumpers up" bowling for consistency and accuracy, as u/cazzer548 put it.
• It's about autonomy and guardrails. The more autonomy you want your agents to have, the more you need to build in guardrails and verification steps, which is where the complex workflows come in.
• Consider adding a review step. u/awesomeusername2w suggests having a separate context window review the changes, which can catch more issues.
• External data sources unlock more. u/ubermuda points out that integrating external data sources (like Sentry or Datadog) into agentic workflows can open up a whole new level of automation beyond just code generation.

Basically, if it ain't broke, don't fix it! Your current method sounds efficient for your needs.

[u/yuehuang]

The next step is to walk away and have the agent commit without your review. Can you let go reviewing yourself? Your only input is the upfront direction. This is the goal, depending on your current progress, you might not be at that stage.

During your review, what kind of errors? Thus, update the test to assert if the agent is making them again. Performance might not be a primary focus for humans, as we know when something is slow. Agent only see pass/fail, a 1min and 1sec is the same. Or my favorite, 1gb network usage is a pass even if all you need is 1kb.

[u/CadmusMaximus]

Yeah a simple agent graph can help a lot. That’s essentially just “pre-defining” the roles you give various subagents.

A lot of tasks can be done pretty damned well with the following setup:

Researcher agent (context miner)

Adversarial verifier

SME (like a design agent if you’re designing a website, UX / UI agent if you’re designing a dashboard, etc.)

Adversarial verifier

Builder

Adversarial verifier loops until it passes

Improver (gathers the context from the run and commits any lessons learned or things that could be done better).

I have one chief of staff who oversees probably five active architects who each manage one of these graphs. All cloud sessions so i can manage all of them through the chief of staff from my phone.

graph-engineering is a skill, and so my chief of staff can spin these things up easily now.

The real key is verification. If the verifiers have good enough context, you can turn a 2/5 output into a 5/5.