LEADING Business Solution GmbH

Projektübernahme & Delivery für kritische Microsoft-Vorhaben. Dynamics 365 · Power Platform · Azure · Senior-only · Architekt als Owner

[Yarchi @undefinedKi]

THE GUY WHO WON ANTHROPIC'S HACKATHON JUST GAVE AWAY HIS ENTIRE CLAUDE CODE PLAYBOOK FOR FREE. 10 MONTHS OF WORK, ALL PUBLIC

Affaan Mustafa won the Anthropic x Forum Ventures hackathon by building a full startup in 8 hours with Claude Code. Then he open-sourced the exact setup that did it. It's called Everything Claude Code, and it turns Claude from one assistant into an entire engineering team

Repo: affaan-m/ecc

This isn't a prompt pack. It's a system he refined over 10+ months of daily use shipping real products

What's inside:

A huge library of skills, dozens of specialized subagents, and ready-made commands, all working together. Each piece does one job. One subagent reviews security against OWASP standards. One optimizes memory so Claude stops forgetting earlier decisions around hour three. One learns from your past sessions and projects so the setup gets smarter the more you use it. Others handle planning, test-driven development, and language-specific code review

Instead of one assistant writing code, you get an orchestrated team. A main session delegates to the right specialist when the task calls for it, the way a real dev team splits work

The best part: it's not locked to one tool. It runs in Claude Code, Cursor, Codex and OpenCode, across Windows, Mac and Linux. Free, MIT licensed

This is the difference between using Claude like a search box and running it like a team that ships. The guy spent 10 months figuring out what actually works so you don't have to

Bookmark this

[arc. @arceyul]

el ingeniero que construyó Claude Code acaba de publicar un video de 28 minutos sobre cómo escribir prompts que realmente funcionan

he visto cursos de 300$ que no cubren lo que él muestra en los primeros 10 minutos

archivos CLAUDE.md, atajos de memoria, sesiones paralelas, patrones de prompting

todo en un video y completamente gratis

funciona seas desarrollador, principiante o alguien que lleva meses usando Claude

[Ajit kumar @ajitcodes]

Learn AI for free directly from top companies.

1 - Anthropic:
https://t.co/1M15GC7cOY

2 - Google:
https://t.co/AIkLM6XjVL

3 - Meta:
https://t.co/UWdSCK5daz

4 - NVIDIA:
https://t.co/B458g8uF1u

5 - Microsoft:
https://t.co/UChXyK2ZQh

6 - OpenAI:
https://t.co/Do088drBz6

7 - IBM:
https://t.co/4XKRjVNMKA

8 - AWS:
https://t.co/36WQ7H0vfT

9 - https://t.co/saSYDpvXFf:
https://t.co/mtt2yYxm6a

10 - Hugging Face:
https://t.co/YYHwWDpwPF

👇Comment "Learning" if you find this helpful.

Repost so others can take help.

Must bookmark for future reference.

[Mushtaq Bilal, PhD @MushtaqBilalPhD]

https://t.co/ERrKQgLB3w

[Dhairya @dkare1009]

🚨 Anthropic just launched its first official AI certification
And it's FREE !

Here's everything you need to know 👇

📌 What it is:
The Claude Certified Architect, Foundations (CCA) launched on March 12, 2026
It's a proctored, 60-question exam testing real production architecture decisions

📌 What it covers:
1. Agentic Architecture & Orchestration → 27%
2. Tool Design & MCP Integration → 18%
3. Claude Code Configuration & Workflows → 20%
4. Prompt Engineering & Structured Output → 20%
5. Context Management & Reliability → 15%

The biggest chunk is agentic architecture
That tells you exactly where the industry is heading

📌 How to access it :
Prep courses → Free for everyone on Anthropic Academy
Exam → Free via the Claude Partner Network (any org can join)

🔗 Register : https://t.co/nIg4ghl0FL
🔗 Prep courses : https://t.co/1Q2BatnZfF

Want more guides and updates like these ?

[Rohit @ai_rohitt]

The creator of Claude Code teaches more about vibe-coding in 30 minutes than most tutorials do in hours.

Save this — it'll change how you build forever.

[Suryansh Tiwari @Suryanshti777]

This AI System Design guide teaches RAG better than most courses.

And I'm giving it away for free (Only for First 4500)

Inside:
• RAG fundamentals & chunking strategies
• Hybrid retrieval (BM25 + vector search)
• Production-level RAG architecture
• Evaluation & RAGAS metrics
• Hallucination reduction techniques
• End-to-end LLM system design

How to get it:
• Follow me (must so I can DM)
• RT + Like
• Comment "book"

I'll dm you

[LEADING Business Solution GmbH @crmonline]

🇩🇪 We’re hiring.
Join a team of specialists who get things done – structured, focused, and together with genuinely good people.

❌No chaos.
❌No politics.

Just solid work and a strong team.

[God of Prompt @godofprompt]

https://t.co/ZutljGjKRV

[Ashish Pratap Singh @ashishps_1]

If you want to get good at System Design in 1 month, learn these 30 concepts in the next 30 days:

Thread (with resources) ↴

[Shraddha Bharuka @BharukaShraddha]

Most people use these terms like they mean the same thing:

Generative AI
Agentic AI
AI Agents

They don’t.

Confusing them leads to bad product decisions.

Here’s the simplest way to understand the difference 👇

━━━━━━━━━━━━━━━

1️⃣ Generative AI

You give a prompt.
AI generates something.

→ Text
→ Images
→ Code

Powerful, but reactive.

No planning.
No decisions.
No execution.

Think: content creation engines.

━━━━━━━━━━━━━━━

2️⃣ Agentic AI

Now AI starts to reason and plan.

It can:
• Choose tools
• Call APIs
• Break problems into steps
• Execute workflows

Still guided.
Still controlled.

But much more useful for real business tasks.

Think: AI with intent.

━━━━━━━━━━━━━━━

3️⃣ AI Agents

This is where things change completely.

AI Agents can:

• Act autonomously
• Adapt to environments
• Execute multi-step tasks
• Improve from outcomes

They don’t just respond.

They operate systems.

Think: digital workers.

━━━━━━━━━━━━━━━

Why this matters:

If you use Generative AI where you need Agents
→ you hit a ceiling fast.

If you deploy Agents without guardrails
→ you create chaos.

The future isn’t just:

“AI that talks.”

It’s:

AI that works.

Are you still experimenting with prompts
or already building agent-first systems? 👇

#AI #AgenticAI #AIAgents #GenerativeAI #Tech #Startups #AIEngineering

[tut_ml @tut_ml]

Most people treat Claude Code like a smarter chat window.

That works… until your project grows.

This structure highlights something deeper: once you move beyond single prompts, you need separation of concerns. The same principles we use in software engineering apply here, too.

Look at the layout carefully.

CLAUDE.md is not just a note file. It becomes project memory.

It defines:
→ Standards
→ Constraints
→ Tone
→ Non-negotiables
→ Guardrails

Instead of repeating instructions in every prompt, you centralize them. That reduces token waste and behavioral drift.

Then you see skills/.

This is where things get powerful. A skill is essentially a reusable workflow.

If you’re repeatedly doing:
-Code reviews
-Refactoring
-Output formatting
-Structured analysis

It should not live in an ad-hoc prompt. It should live as a reusable capability.
That shifts you from prompting to system design.

Next, hooks/.

Hooks are underrated. They let you enforce checks:
→ Clean tool output
→ Validate structure
→ Log commands
→ Transform JSON

If you’re not using hooks, you’re manually correcting outputs that could have been automated.

Then the repository itself stays modular:
-docs/ for architecture decisions
-src/ for actual logic
-tools/ for scripts and utilities

This prevents your AI layer from bleeding into your application layer.

When I started organizing projects this way, three things improved:
-Fewer repeated instructions
-More predictable outputs
-Easier collaboration

Especially once you add:
→ Subagents
→ MCP integrations
→ GitHub Actions automation
→ Plugin development

Without structure, context becomes clutter. With structure, Claude operates within clear boundaries.

This is not about making things complex. It’s about treating AI workflows like first-class engineering components instead of temporary chat experiments.

If you're learning Claude Code and want to see how I implement this step by step, from installation to CLI usage, skills, hooks, subagents, MCP, GitHub Actions, and plugins, I’ve recorded the full process while building real workflows.

This is the Claude Code Full Course Link- https://t.co/YSFcevvO4q

Image Credit- Brij Kishore Pandey

Happy Learning!

#claudecode #claudeai

[LEADING Business Solution GmbH @crmonline]

PP:UNDOC — Power Platform Undocumented APIs https://t.co/ZCjvdghOWr

[Aastha @aastha_mhaske]

Master AI agents 📚📘

[Tom Dörr @tom_doerr]

Dashboard for AI agent orchestration

https://t.co/0BkOTVcXkz

[tut_ml @tut_ml]

Most people treat Claude Code like a smarter chat window.

That works… until your project grows.

This structure highlights something deeper: once you move beyond single prompts, you need separation of concerns. The same principles we use in software engineering apply here, too.

Look at the layout carefully.

https://t.co/YF2dqGxlFx is not just a note file. It becomes project memory.

It defines:

→ Standards

→ Constraints

→ Tone

→ Non-negotiables

→ Guardrails

Instead of repeating instructions in every prompt, you centralize them. That reduces token waste and behavioral drift.

Then you see skills/.

This is where things get powerful. A skill is essentially a reusable workflow.

If you’re repeatedly doing:

-Code reviews

-Refactoring

-Output formatting

-Structured analysis

It should not live in an ad-hoc prompt. It should live as a reusable capability.

That shifts you from prompting to system design.

Next, hooks/.

Hooks are underrated. They let you enforce checks:

→ Clean tool output

→ Validate structure

→ Log commands

→ Transform JSON

If you’re not using hooks, you’re manually correcting outputs that could have been automated.

Then the repository itself stays modular:

-docs/ for architecture decisions

-src/ for actual logic

-tools/ for scripts and utilities

This prevents your AI layer from bleeding into your application layer.

When I started organizing projects this way, three things improved:

-Fewer repeated instructions

-More predictable outputs

-Easier collaboration

Especially once you add:

→ Subagents

→ MCP integrations

→ GitHub Actions automation

→ Plugin development

Without structure, context becomes clutter. With structure, Claude operates within clear boundaries.

This is not about making things complex. It’s about treating AI workflows like first-class engineering components instead of temporary chat experiments.

If you're learning Claude Code and want to see how I implement this step by step, from installation to CLI usage, skills, hooks, subagents, MCP, GitHub Actions, and plugins, I’ve recorded the full process while building real workflows.

This is the Claude Code Full Course Link- https://t.co/vyorOTkdVs

Image Credit- Brij Kishore Pandey

Happy Learning!

#ClaudeCode #claudeai

[Ihtesham Ali @ihtesham2005]

🚨 This GitHub repo just changed how I use Claude Code forever.

It's called claude-code-best-practice and I'm annoyed I didn't find it sooner.

I spent months manually re-explaining my stack every session.

This repo ends that permanently.

Here's what it ships with:

→ Production-ready agents that run without hand-holding
→ Persistent memory that never resets between sessions
→ Custom hooks wired to your exact workflow triggers
→ Skills built once, deployed across every project forever
→ Commands that make Claude Code feel like a full engineering team

Everything I was building manually from scratch.

Already done. Already working. Already open source.

100% Open Source.

[Charly Wargnier @DataChaz]

In case you were living under a rock this weekend,

Anthropic has launched free courses to master AI with certificates for $0.00

→ https://t.co/AvC7x0EWIk

[LEADING Business Solution GmbH @crmonline]

@dynamicsminds See you there!