Tobias Braun

[Python Developer @PythonDvz]

𝗧𝗼𝗽 𝟲 𝗥𝗔𝗚 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲𝘀 𝗲𝘃𝗲𝗿𝘆 𝗔𝗜 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿 𝘀𝗵𝗼𝘂𝗹𝗱 𝗸𝗻𝗼𝘄 ⚡︎

Picking the wrong one is why your AI project is underperforming.

1️⃣ Simple RAG
Retrieve top-k chunks from a vector store, then generate.
→ Use cases: FAQ bots, internal knowledge assistants, support.

2️⃣ Hybrid RAG
Combines semantic and keyword search, then reranks the results.
→ Use cases: Enterprise search over messy or technical docs where pure vector search misses exact terms.

3️⃣ Corrective RAG (CRAG)
Scores retrieved content for relevance and triggers a fallback search when it's weak.
→ Use cases: Medical, legal, financial. Anywhere a wrong answer is expensive.

4️⃣ Self-RAG
The model decides when to retrieve and critiques its own output before answering.
→ Use cases: Technical documentation, deep research, exploratory writing.

5️⃣ Graph RAG
Retrieves over a knowledge graph of entities and relationships, not just isolated chunks.
→ Use cases: Scientific discovery, legal reasoning, multi-hop questions where connections matter.

6️⃣ Agentic RAG
An agent routes queries, runs multi-step retrieval, and validates across sources and APIs.
→ Use cases: Automated research, market intel, executive dashboards.

Most teams default to Simple RAG and wonder why accuracy stalls.

The architecture isn't the afterthought. It's the decision that determines whether your RAG system actually works.

Match the architecture to the problem. Not the other way around.

Which one are you running in production right now? 👇

#AI #RAG #LLM #AIEngineering

[0xMarioNawfal @RoundtableSpace]

The Hugging bay, The Pirate bay for open LLM's, model weights downloadable with torrents.

This is a game changer.

https://t.co/nuZQ68aluH

[Tom Dörr @tom_doerr]

Awesome CV generates resumes and cover letters using local LaTeX

https://t.co/BSGToHcA3D

[Visual Studio Code @code]

🤖 Ready to get started with Agentic Development in @code?

We've put together 3 free courses covering everything from building your first AI agent to customizing and extending agent workflows.

A quick breakdown 🧵👇

[Rohit Kumar Tiwari @_rohit_tiwari_]

Builds GPT-like LLMs from scratch in PyTorch

> Breaks the LLM architecture into simple parts.
> Beginner friendly.
> Fully hands on.

https://t.co/sbqfNxbBVC

> Everything explained step by step.
> Just 10 notebooks.

01_tokenization.ipynb
02_token_embeddings.ipynb
03_positional_embeddings.ipynb
04_self_attention_mechanism.ipynb
05_multi_head_self_attention.ipynb
06_feedforward_neural_networks.ipynb
07_residual_connections.ipynb
08_layer_normalization.ipynb
09_transformer_block.ipynb
10_mini_gpt.ipynb

[precis0x @precisox]

Acaban de lanzar una herramienta brutalmente útil y 100% open source

Se llama docker android y permite ejecutar un emulador completo de Android dentro de un contenedor Docker.

Sí, leíste bien: puedes tener un teléfono Android virtual completo, aislado, reproducible y fácil de desplegar con solo un comando de Docker.

Por qué es interesante?

- Es minimalista y altamente personalizable
- Funciona en modo headless (sin interfaz gráfica)
- Soporta aceleración por hardware con KVM
- Puedes elegir la versión de Android que necesites (varios API levels disponibles)
- Incluye ADB listo para usar
- Se integra perfectamente con scrcpy para controlar la pantalla de forma remota
- Ideal para CI/CD, pruebas automatizadas, desarrollo y debugging

Todo está en un solo contenedor Docker, lo que significa que puedes levantar entornos Android limpios, consistentes y escalables en segundos, sin tener que instalar emuladores pesados localmente ni lidiar con configuraciones complicadas.

Repositorio oficial 100% open source - MIT License

Estás trabajando en pruebas de apps Android, automatizaciones o entornos de desarrollo? Esta herramienta puede ahorrarte muchísimo tiempo y dolores de cabeza.

Cuéntame para qué la usarías?

Repo en los comentarios 👇

[Vivek | Cybersecurity @VivekIntel]

🎓 Blockchain Development Resources — One of the Most Comprehensive Free Web3 Learning Collections

Whether you're starting with blockchain fundamentals or diving into smart contract security, DeFi, NFTs, DAOs, and Zero-Knowledge Proofs, this repository brings together hundreds of free learning resources in one place.

What you'll find:

✅ Blockchain & Web3 learning platforms
✅ Solidity, Rust, Vyper, Golang, and smart contract development
✅ Ethereum, Solana, Polygon, Celo, NEAR, Avalanche, and more
✅ Free courses, tutorials, documentation, and books
✅ Smart contract security & auditing resources
✅ DeFi, NFTs, DAOs, and Zero-Knowledge Proofs (ZK)
✅ Developer tools: Hardhat, Foundry, Remix, Ethers.js, Web3.js, OpenZeppelin, IPFS, MetaMask, and more
✅ Blockchain games and hands-on labs for practical learning

Perfect for aspiring blockchain developers, smart contract engineers, Web3 builders, and security researchers.

🔗 https://t.co/QUmERt5SFM

#Blockchain #Web3 #Ethereum #Solidity #SmartContracts #DeFi #NFT #Crypto #Web3Development #LearnToCode #OpenSource #CyberSecurity

[Tom Dörr @tom_doerr]

Hex editor designed for reverse engineers

https://t.co/fFKFWDXDS4

[Tom Dörr @tom_doerr]

Collection of Windows Subsystem for Linux distributions and tools

https://t.co/RTqzrjuAVg

[7h3h4ckv157 @7h3h4ckv157]

OSINT Mapping Tool 📍

A small web app for organizing OSINT research. Jot down identifiers (social handles, phones, vehicles, whatever), pin places on a map (Google or OpenStreetMap), and wire the two together.

Resource: https://t.co/buW03MhgmD

[Mike Overton @mikeoverton21]

New wallpaper drop 🚀

Shields up! Red Alert! This weeks its the red alert version of the Enterprise E Vessel Status

Free download: https://t.co/MctzwUDeHy

#wallpaper #scifi #startrek #startrektng

[GitHub Projects Community @GithubProjects]

A collection of 92+ copy-paste-ready AI agent patterns built on the AI SDK, with live previews and full templates for building your own agent workflows.

- Competitor Research Agent for automated competitive intelligence and battle cards
- Data Analysis Agent with interactive visualizations and insight detection
- Accessibility Audit Agent for WCAG 2.1 compliance scanning
- 4 full-stack agent templates including ecommerce multi-agent and RAG platforms

Explore it here:
https://t.co/pW56a5k97z

[Vaishnavi @_vmlops]

FastAPI
for AI Engineers

https://t.co/AmyaVEFjma

[Shraddha Bharuka @BharukaShraddha]

Difference Explained Well 📚📘

Save it for later 💯

#llm #rag #ai #agent #agenticai

[Tom Dörr @tom_doerr]

Adds text layer to scanned PDFs

https://t.co/a1WtywVmOp

[Tom Dörr @tom_doerr]

Curated list of Obsidian plugins, themes, and community resources

https://t.co/O3Zt6tNroW

[Tom Dörr @tom_doerr]

Collection of patterns for building software with AI assistance

https://t.co/B2VUWUh260

[tut_ml @tut_ml]

Best LLMs Courses- https://t.co/LY41Y8jQqO

[Alif Khan @Alifkhanzxx]

A senior Google engineer just dropped a 421-page doc called Agentic Design Patterns.

Every chapter is code-backed and covers the frontier of AI systems:

→ Prompt chaining, routing, memory
→ MCP & multi-agent coordination
→ Guardrails, reasoning, planning

This isn’t a blog post. It’s a curriculum. And it’s free.