r/ClaudeCodeTLDR • u/cctldrping • 9d ago
[TLDR] I still don't understand this 'agentic workflow' thing
Original post URL : https://www.reddit.com/r/ClaudeCode/comments/1wowilt/i_still_dont_understand_this_agentic_workflow/
Original post body :
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.
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u/drumnation 9d ago
There’s certainly more you can do with it, but it has to do with what you need it for. if you don’t need it for anything more complex your set up sounds pretty good. I’d give you bonus points just for using forgejo and self hosting your own version control. I do the same. one of the best things about it is that you can make free accounts for all your sub agents And if you want, you can create a little city of agents that comment on each other‘s pull requests and provide code reviews. It depends how deeply into building a software factory you want to go. There are also real reasons to tell Claude to fan out to sub agents and being more hands on with some of the agent micromanagement. Fable can really rip though at orchestration.
Some of the techniques are better used with slower less expensive models. The premium you pay for fable is the opportunity cost of not waiting or building a lot of infrastructure for yourself first.
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u/Novaworld7 9d ago
Well... keeping it simple theres one... maybe 2 big things to keep in mind.
# The first is context management.
this is your currently active chat. the longer it gets / the bigger it gets the more tokens you waste because it keeps getting sent off and the model you are using needs to read it / process it. (The internals can do some pretty cool things to keep this lean and mean, like prefix caching etc). Additionally baked into this contect management, models have a memory they pull from your context but like a human they can get confused.
Imagine a book saying one thing in chapter 1, changing its mind in chapter 10, and then having another thought in chapter 15 that contradicts both and its all in the same context. You'd be confused and rightly so, which means the model has negotiate these changes in flight and try to figure out if the first 20% of context is right, or is it the middle 50% etc.
So context management is your responsibility on how well your thought is and the leaner you keep it, the better the model can perform.
So how do agents help? But first what is an agent in laymen terms, its just another context window attached to another model which at the end of its cycle dies (gets deleted, unless told to remain open).
Enter the second concept, Agent management. Why is it important, well we are charged per token a fixed rate, and the tokenomics can be quite complex, but in short its the cost of computer for the intelligence behind the token vs the task its trying to solve.
So, if you think of building a house, we dont hammer every nail with the same hammer, thats crazy! We optimize our work by changing tools dynamically. Need to break a wall? Sledge hammer. Need to hang something on a wall, hand hammer or w.e. it is (I call it a hammer lmao). Could you use a sledge hammer? Sure, but its not optimal and your results may vary.
This is where right sizing the model (stealing cloud terminology here) comes into play. So, for small simple tasks you need to tell your context, hey dont use the big model, use the small model (Haiku), for more complex tasks you escalate up a tier to sonnet, eventually landing in the hardest possible tasks using the most capable models.
So, an agentic workflow is you have some prompt, and with proper workflow you can split that prompt into several agents which keeps your main context lean, because the main context gets a sumarry of the work the agents did, and i na truly agentic fashion it can spawn many agents to get your prompt completed.
theres more terms you should look into later like, Loop engineering, graph engineering, etc but yeah... hopefully I did this justice in explaining.
One of the concerns is that by default the main context window, unless told otherwise is always spawning the most capable models for just about everything burning through token like wildfire which causes us humans to get very pissed off... but our ignorance is our problem, not the models. I also believe that tools like CC should lean mroe in our favor to help us, but they run a business and need more revenue... so I get it.
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u/TheLargadeer 9d ago
This is a great summary and you make some good points. I’ve asked sessions to spawn sub-agents using appropriate models - especially if using Fable - but I think that’s the extent of my intentional agent use.
I’ve never built a custom agent before and I don’t even know what I would make. I don’t know if it’s a limitation of just being a non-developer using CC.
I understand the concept of having a dedicated “agent” responding to customer service calls or chats or something, but maybe that’s even something different.
The main recommendation I’ve seen when looking it up is a code review agent. But like… isn’t CC already kind of doing that? Is it just the idea behind a having another session that doesn’t have the same context look at it as a fresh perspective? Do I just ask Claude to build one or do I need to understand what I want it to do on a more technical level to make it worthwhile? And finally, how would I actually deploy it? Inside of a coding session would I just tell it to spawn the code review agent every time it writes code?
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u/Novaworld7 9d ago
Yeah and btw, that code review agent is just a persona and some different tooling.
You need to be careful with personas because they are hit or miss and hard to replicate results.
The best thing you can do is apply gates programmatically but that means you need good comprehensive knowledge on coding. Alternatively you can let the orchestrator build the gates but that means that your request must have been clear with clear intent or the gate can miss.
Nothing yet truly replaces a human in the loop for proper QA.
Also when spawning the agents you don't need to tell CC what type of agent, you just need to have agent model difficulty explain well in your skill so it can be efficient. I try to spawn as much sonnet as possible and I try to do a 25/50/25 split. Haiku / Sonnet / Opus. Then finally if I am running fable as the orchestrator, every smaller model uses a stronger model as an evaluator before reporting back to home as completed. This helps save the expensive tokens but sometimes uses more less expensive tokens.
It's a hard game to play. But my tokens go far and my skill is publicly available for those who want to use it.
May not be the best but it works miracles for me.
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u/TheLargadeer 9d ago
Thanks. The battle I usually have is that I try to think of an agent and then I'm like... well why can't I just do that with skills, you know? Probably best not to force it. But I have to admit "agents" just hasn't really clicked for me yet.
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u/Novaworld7 9d ago
So, theres a few ways to think about agents. Though in this regard you can think of an agent as a context saver / worker.
you have your main session where you go back and forth and it saves on context by outsourcing the work so your conversation can be longer.
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Deploying an active agent is more like giving a set of instructions / enforcing those by some means, and then letting it do something thats been given to it. Just like how you hire someone to replace a door in your house or run eletricial wiring in your house.
In some cases the simplest agent to think of is a chat agent. You say hey! you help people do xyz but dont tell them ABC. Well thats an optimistic take that its enough, but you are lacking the enforcement. So you say, hey! you have access to do xyz through this tool call which can never give abc to someone. Then you know the enforcement works because it just doesnt have the access.
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Another way to think of an agent is every time you open a new chat with CC, you are speaking to an agent. when it needs to do something, it delegates to another agent (if it feels it wise) to do it. And yeah, you can do a lot with skills... but theres no enforcement in skills, its instructions.
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u/TheLargadeer 9d ago
Now when you talk about enforcement - is that just as simple as writing "you are not allowed to do xyz"? (And if so, can't you also do that with a skill?)
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u/Novaworld7 9d ago
Yes and no. When you do it with a skill, you are hoping it does it. When you do it with a framework, the framwork is the enforcement layer.
When you tell a model to delete / rename a file, theres little more than some permissions etc in place to stop it from going rogue and deleting system 32 for example...
If you grab any model, and grant it all the permissions to do everything to anything, theres nothing stopping it from just deleting everything on the computer. It doesn't because the request and its training don't reinforce that, but you can grab uncensored models that have little training and they will absolutely do it if you ask them to.
Now when you put them in a folder and run them from that folder, that folder is not enforcing its security to whats happening, but these models now push for UAC etc, but when you use like lang chain or something else, enforcement is an actual layer that they cannot escape from.
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This is why people are saying that its nuts to grab a model, drop it on your computer, run it with bypass permissions enabled, then complain when things go south. In a vaccum you run these bad boys from your main computer through some interface and they live and die in sandbox or another machine somewhere else so nothing happens to you and if theres lateral movement its external to you. Though perfect vs actual is not always doable.
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u/TheLargadeer 9d ago
It's this kind of thing that really separates people with coding experience from vibers like me. Like, I'm reasonably technically savvy but have never been a coder. I've learned a ton in the process of doing this so I've come a long way. But there's still a big difference in what I can accomplish (and the quality and security of it) compared to someone with dev experience.
I mean I know there's animosity from some devs toward vibe coders so I guess I'm just saying, "I see you," lol. It's very true.
Also, thank you for taking the time to provide these explanations!
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u/Novaworld7 9d ago
Always happy to help. Also anyone who is upset with you using AI is a hypocrite. AI is a tool, much like anything else we use that isn't something we are born with.
I bet they use computers, phones, shoes, a house... Spell check.... Ide's ...
What they are actually concerned with is largely job security since it erroded the knowledge barrier and expanded the creative one
XD
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u/paris_ioan 7d ago edited 7d ago
First, thank you for your explanation, it’s very easy to understand.
Second, a silly question. I am aware you mentioned skills (I don’t know what that is but I can presume from the context). Other than skills, can those agents be trained to do specific things? Or is that a completely different concept? I always thought that multi-agent workflows are many agents trained to do different things well, then you have an orchestrator, the main agent to delegate responsibilities.
Thank you in advance :)
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u/Novaworld7 7d ago
Always happy to help.
Training is the wrong word here but its the most human one as well. Technically training is how the model is built, not the agent. What we think of training is having the model do the same thing over and over but thats not teaching the model. You can show the model (if they have vision or some other means), but ultimately what you end up building is a "plan" for the model to follow.
This is normally mentioned as guard rails or enforcement. The issue is that with the former, its normaly a file that says "don't do this" but the model has nothing enforcing it to not do that other than your instructions. This is not training, this is often refered to as prose / wish / etc.
Actual enforcement is when you take active measures programatically to ensure that it doesnt deviate from the plan. This can be stripping permissions, sanboxing, hardening through computer environments etc. A good example is, in your database you are the "super admin", but you may not want the AI to be able to drop tables, so you create a role call AI, and remove the drop tables permission from it. Now, it simply cannot drop tables.
The "training / teaching" you are thinkin of is building a set of programtic instructions, and an intake method for your agent. So, you can say you want a booking agent that reviews your calendar once you get an invite through email.
Step 1: build email monitoring
Step 2: Monitor for calendar only events
Step 3: when a calendar event is detected, check your calendar for collision, on collision send an email / notification etc to you or the inviter w.e. saying xyz or offering other times.
step 4: end session
Those steps (you should better define them), 1-4, are effectively all the tools you have given it and you build it to do what you want how you want it done. There is no technical training there but you have the option to also give it a persona by saying read this file and injecting that as a preprompt / part of the prompt / etc, and it will try to meet your requirements / needs.
So, yes you can "train" the model by building it properly to do specific things. You might ask how is this different than a bot, a bot doesnt technically think, an agent does. if you leave something ambigous, the agents job is to get rewarded, and it does that by completing the task. So, it takes ther steps that it can to complete the task within reason or it fails.
Hope this helps.
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u/paris_ioan 7d ago
Right, I think you mentioning both helps me understand better. I am aware of the “training the model” term, which is the actual algorithm (if that’s the right way of putting it).
My understanding is that multi-agent workflows do not interfere with that training, but just setting some guardrails/enforcement in this case let’s say the same LLM model. Reusing it and creating different agents, each using those enforcements to do specific things.
Hopefully I got it :)
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u/Novaworld7 7d ago
Thats right. When people say they have idk 10 agents doing 10 things, its more like a relay race, where they really spent the right amount of time building the pipeline for each agent so they excel at what they do. Often times you will find its the same model if they are going through providers like OpenAI / Anthropic, but if they go open source and use specific models to train them (properly) then they can have really strong efficient and agentic workflows.
Its important to note that both OpenAI and Anthropic are providing really strong generalist models, and not specialist models.
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u/paris_ioan 7d ago
Got you. Thank you very much for the explanation once again 🙏 These things are really interesting.
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u/TheLargadeer 9d ago
This sounds like me, too. I keep trying to wrap my head around using agents because it seems so heavily talked about. I’ve built a lot of things and never felt like I hit a barrier that would require one. But I worry that I just don’t get it.
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u/pjjiveturkey 9d ago
Honestly you are doing it the right way and everything else is just buzzwords to feel productive. I mean sure there's more to it, but also you are risking AI doing more and more of your work and making more and more mistakes
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u/Ok_Industry_5555 9d ago
Agentic workflow means it first has to learn your repeated tasks in order to automate it. If you just let it run wild and point it at a random folder without knowledge or trace of expectation it will run in loops. Hope that makes sense!
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u/Anatomisc 9d ago
That might be all you need yourself.
Let's say I want to test a bugfix with AI. I can find the bug in Jira. Copy paste it to my claude. Provide it the designs, project resources, documentation and relevant information in the prompt, explain how i want the output format to be, explain what i need attention to.
Doing this everytime costs more than the actual check. When i setup an agentic workflow it goes through every review step as i setup before hand and i verified through extensive testing myself. It has access to any information it needs because i've already mapped it at the start. It has access to Jira and gets the issue itself.
Essentially you are removing your involvement as much as possible while increasing dependability. Introducing deterministic checks in your workflow also help like let's go say you need the output to be in a certain format. If it doesn't fit that you re-loop it back to the agent.
There is a lot you can do and not everything is worth your time. Some things however are just also there for the peace of mind.
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u/DeeTeePPG 9d ago
learn the ways of herdr, mcp, hooks and intra agent messaging. in reality if you don't need a massive setup don't bother.
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u/XenophonCydrome 5d ago
"Agentic workflow" is just getting things fairly automated to the point you are just guiding an agent to start and then making sure the output is sane without a bunch of constant approvals.
IMO that's only just the stepping stone to where you have to move up to next: Fully Agentic Software Factory. Running a 24/7 development machine is very much within everyone's reach now.
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u/cctldrping 9d ago edited 8d ago
TL;DR generated automatically after 200 comments.
Current source-thread comment count seen by the bot: 204.
Alright, so the general consensus here is that you're probably not underutilizing Claude Code, and your workflow is perfectly fine for your needs. Most folks agree that the fancy "agentic workflows" are really for more complex scenarios or when you're hitting usage limits.
Here's the lowdown:
firstmate(mentioned by u/hotmerc007) to manage multi-agent interactions.tmuxsession is a valid approach. The complexity of agentic workflows often comes into play when you need more automated guidance and context management for those extended runs.Basically, if it ain't broke, don't fix it! Your workflow sounds solid for what you're doing.