Ali Tariq

💼 Entrepreneur
🏅Crypto Evangelist

[Brij Pandey @LearnWithBrij]

Most people use Claude Code like autocomplete.

But Claude Code is actually a full agent operating system.

And most engineers are only using Layer 1.

Here’s the architecture nobody explains properly:

🧠 Layer 1 — CLAUDE.md

This is the agent’s constitution.

Your:
→ architecture rules
→ coding standards
��� repo structure
→ naming conventions
→ workflows

All live here.

Always loaded.
Always active.

This is what turns Claude from “generic AI” into “your engineering team’s AI.”

📚 Layer 2 — Skills

Reusable expertise modules.

Claude dynamically loads the right SKILL.md only when needed.

That means:
→ cleaner context
→ lower token usage
→ specialized execution
→ less hallucination

The important part most people miss:

Skills can fork into isolated subagents.

So your main context stays clean while deep tasks execute separately.

This is where Claude starts feeling agentic instead of conversational.

🛡️ Layer 3 — Hooks

The most underrated layer in the stack.

Hooks are deterministic infrastructure triggers:

→ PreToolUse
→ PostToolUse
→ SessionStart
→ Stop

This is NOT AI reasoning.

It’s programmable guardrails.

Examples:
→ auto-run linting
→ block dangerous bash commands
→ enforce repo policies
→ send Slack notifications
→ auto-format outputs
→ inject runtime context

Production reliability happens here.

Most teams skip this layer completely.

Huge mistake.

🤝 Layer 4 — Subagents

This is where Claude Code becomes a true multi-agent system.

Delegate tasks downward.
Receive results upward.

Each subagent gets:
→ isolated context
→ separate tools
→ different permissions
→ independent models

No context bleed.
No recursive chaos.
Hard boundaries by design.

You stop thinking:
“One AI assistant”

And start thinking:
“Distributed cognitive workers.”

📦 Layer 5 — Plugins

The distribution layer.

Bundle:
→ skills
→ hooks
→ commands
→ agents
→ workflows

into one installable package.

One command:
Entire team inherits the same behavior instantly.

This is how organizations operationalize agentic engineering.

Not prompts.
Infrastructure.

The gap between:
“AI demo”

and

“Production-grade agent system”

is usually one of these five layers.

Most people are still prompting.

A few are engineering cognition.

That’s the real shift happening right now.

Follow for deep dives on Claude Code, MCP, Hooks, multi-agent systems, and agentic AI architecture.

[Ali Tariq @bcsleuth]

@rezkhere Seedance

[Ali Tariq @bcsleuth]

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Set up your #GradientSentry Node and be part of the future.

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[Abstract @AbstractChain]

PG was researched and designed to solve the fundamental misalignment between users, builders, and governance.

PG can be implemented on any L2 blockchain that has a native governance token and a sequencing system.

Read the full research paper here: https://t.co/0hUB7i3yGr

[Ali Tariq @bcsleuth]

@onic_pk 618

[Ash Crypto @AshCrypto]

Me trying to catch the $LUNA bottom

[Ali Tariq @bcsleuth]

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[Mdex.com @Mdextech]

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