7.2K
CAThis agent teams feature is a big step forward…
#vibecoding #claude #opus
@casey.aicreates
#Subagent
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8.1K
CHComment “Claude” to get my Claude code for non coders guides
@chase.h.ai
1.5K
CAWhen and when not to use agent teams in Claude code…
#vibecoding #claude #aiagents
@casey.aicreates
1.4K
MIPt. 3: What Goes Into /docs 🗂️ Agent-Ready Files (DRY Edition)
Keep it simple. Keep it reusable. Keep it Evergreen.🌲
Your /docs folder exists so agents don’t repeat work - DRY applies to context too.
Typical files your CLAUDE.md should point to:
– architecture.md
System overview, components, data flow
– decisions.md
Why things were built this way (very important)
– conventions.md
Naming, formatting, repo rules
– workflows.md
How things are built, tested, deployed
– integrations.md
APIs, services, auth, rate limits
– glossary.md
Domain terms and meanings
Why this works:
– One source of truth
– Less repetition in prompts
– More consistent agent behavior
Rule of thumb:
If you explain it twice, document it once.
Agents perform best when context is structured.
Pt. 1: The Golden Folder 🥇
Link: https://t.me/agentbuilderacademy/64
Pt. 2: Why Your CLAUDE.md Needs a Table of Contents for /docs 🗂️
Link: https://t.me/agentbuilderacademy/70
Happy Vibe Coding!
Michael
#aiagents #claudecode #vibecoding #aiengineer
@michael.negele
7.5K
CHComment “agent” to get Claude code guides + N8N templates sent your way!
@chase.h.ai
12.9K
SEObra brainstorming is probably the best Agent Skill library out there.
Check it out if you haven't !
#claudecode #agentskills #vibecoding
@seankochel
305
MIPt. 4: Docs Folder 🗂️ How Agents Actually Use It
Docs only work if agents know how to find them.
There are two modes:
Manual RAG → Autonomous RAG
Ways to interact with /docs:
– Manual (@file.md)
Precise but repetitive. Doesn’t scale.
– CLAUDE.md (Anchor)
Claude reads it automatically.
You reference docs by intent, not by path.
– Built-in RAG
Large repo? Claude searches your files on its own.
– MCP Servers
Power-user mode. Agents query docs autonomously across systems.
Rule of thumb:
If you’re still typing @file.md all day, your agents aren’t set up yet.
Pt. 1: The Golden Folder 🥇
Link: https://t.me/agentbuilderacademy/64
Pt. 2: Why Your CLAUDE.md Needs a Table of Contents for /docs 🗂️
Link: https://t.me/agentbuilderacademy/70
Pt. 3: What Goes Into /docs 🗂️ Agent-Ready Files (DRY Edition)
Link: https://t.me/agentbuilderacademy/71
Happy Vibe Coding!
Michael
#aiagents #documentation #vibecoding #aiengineering
@michael.negele
1.4K
MIPt. 5: Docs and CLAUDE.md 🧠 When Chat Isn’t Enough
You don’t always need docs.
If a simple prompt gets the job done and the agent understands your intent - perfect.
But once you start:
– fixing bugs
– rebuilding systems
– iterating over time
– collaborating with agents and humans
…chat alone breaks down.
That’s where docs and CLAUDE.md come in.
Why they matter:
– They capture intent
– They define constraints
– They prevent re-explaining decisions
– They align humans and agents
CLAUDE.md acts as the entry point.
Docs act as the shared memory.
Rule of thumb:
Chat is for exploration.
Docs are for systems.
Pt. 1: The Golden Folder 🥇
Link: https://t.me/agentbuilderacademy/64
Pt. 2: Why Your CLAUDE.md Needs a Table of Contents for /docs 🗂️
Link: https://t.me/agentbuilderacademy/70
Pt. 3: What Goes Into /docs 🗂️ Agent-Ready Files (DRY Edition)
Link: https://t.me/agentbuilderacademy/71
Pt. 4:
Happy Vibe Coding!
Michael
#aiagents #claudecode #claudeai #vibecoding
@michael.negele
5.6K
DESome of these new features in Claude code are slipping through the cracks.
Agent teams is a new experimental feature that you can enable in your settings.
I’m noticing that I’m getting results for complex tasks much faster than plan mode, which has been my go-to for debugging.
#claudecode #aicoding #vibecoding #aitips #aiagents
@deonnahodges
256
MIPt. 2: Why Your CLAUDE.md Needs a Table of Contents for /docs 🗂️
Agents need orientation, not just instructions.
A CLAUDE.md file with a clear table of contents pointing to your /docs folder gives agents:
– Fast navigation
– Immediate context
– Awareness of what exists and where
– Fewer wrong assumptions
Why this matters:
Without a map, agents guess.
With a map, they act deliberately.
Best practice:
– Use CLAUDE.md as the entry point
– Link to key .md files in /docs
– Keep it updated as the project evolves
Rule of thumb:
If agents can’t find it, they can’t use it.
This small step massively improves agent performance.
Happy Vibe Coding!
Michael
Link Pt. 1: The Golden Folder 🥇
https://t.me/agentbuilderacademy/64
#aiagents #aibuilders #claudecode #vibecoding #aiengineering
@michael.negele
1.1K
KGThe creator of Claude Code shared his workflow. One thing that stood out to me is that he pushes heavy use of sub-agents for tasks that are repeated across different chat sessions, like code reviews, security reviews, etc.
Sub-agents are specialized agents that run in a separate context window from your primary chat, and that separation comes with advantages.
As your main chat grows longer and more complex, performance can start to degrade because the model has to work within an increasingly large context.
When you stack additional work like “do a code review” onto an already massive context thread, you are forcing the model to process all of that accumulated context, even when it is not necessary for some sub-task.
Sub-agents avoid that by isolating focused tasks from your main chat, which keeps the active context window smaller and potentially improves the output quality of the model.
It may even reduce wasted tokens and make complex tasks feel cleaner and more controlled.
I have not tested it enough to say for sure, but it seems smart isolating repeatable tasks like this to maintain performance and better manage context.
Curious what y’all think(?). Are y’all using sub-agents in Claude or something similar in another tool?
@kg.codes
152
EUAgent-based coding feels unpredictable for a reason — and Cursor finally explained it clearly.
The mistake teams make is treating agents like smarter autocomplete.
They’re not.
Modern coding agents can:
→ Run for long stretches
→ Touch dozens of files
→ Refactor across a codebase
→ Iterate until tests pass
That means failure usually isn’t a model problem.
It’s an operating problem.
Cursor calls the missing layer the agent harness.
An agent’s output is shaped by three things:
→ Your instructions
→ The tools it’s allowed to use
→ Your follow-up and corrections
Change any one of those and the same model behaves differently.
Their most important recommendation is simple but non-negotiable:
plan before you let the agent write code.
Planning forces clarity on:
→ What you’re building
→ What “done” actually means
→ What success can be verified
Agents don’t know if they’re right unless you give them signals.
Tests, linters, typed languages, and clear failure states aren’t optional anymore — they’re how agents self-correct.
The shift most teams miss:
You’re not delegating to a junior dev.
You’re managing a very fast collaborator.
The advantage won’t go to whoever has the best model.
It will go to whoever has the best system for shipping reliable changes.
The model is the engine.
The harness is the vehicle.
And customers buy vehicles — not engines.
#artificial_intelligence #technology #AI #LLM #aiagent #openai #agents
@euginajordan
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