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The Ultimate Weapon for Software Architects (Sponsored)
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This week’s system design refresher:
The Generative AI Tech Stack
24 Good Resources to Learn Software Architecture in 2025
ByteByteGo Technical Interview Prep Kit
Database Index Types Every Developer Should Know
The Agentic AI Learning Roadmap
12 MCP Servers You Can Use in 2025
SPONSOR US
The Generative AI Tech Stack
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GenAI refers to systems capable of creating new content, such as text, images, code, or music, by learning patterns from existing data. Here are the key building blocks for GenAI Tech Stack:
Cloud Hosting & Inference: Providers like AWS, GCP, Azure, and Nvidia offer the infrastructure to run and scale AI workloads.
Foundational Models: Core LLMs (such as GPT, Claude, Mistral, Llama, Gemini, Deepseek) trained on massive data, form the base for all GenAI applications.
Frameworks: Tools like LangChain, PyTorch, and Hugging Face help build, deploy, and integrate models into apps.
Databases and Orchestration: Vector DBs (such as Pinecone, Weaviate), orchestration tools (such as LangChain, LlamaIndex) manage memory, retrieval, and logic flow.
Fine-Tuning: Platforms like Weights & Biases, OctoML, and Hugging Face enable training models for specific tasks or domains.
Embeddings and Labeling: Services like Cohere, Scale AI, Nomic, and JinaAI help generate and label vector representations to power search and RAG systems.
Synthetic Data: Tools like Gretel, Tonic AI, and Mostly AI create artificial datasets to enhance training.
Model Supervision: Monitor model performance, bias, and behavior. Tools such as Fiddler, Helicone, and WhyLabs help.
Model Safety: Helps ensure ethical, secure, and safe deployment of GenAI systems. Solutions like LLM Guard, Arthur AI, and Garak help with this.
Over to you: What else will you add to this list?
How Top Fintech Engineering Teams Actually Ship (Sponsored)
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fintech_devcon is the technical conference where real builders share how they ship complex systems at scale.
Hear directly from engineers at Amazon, Block, Plaid, Chime, DocuSign, Gusto, and more.
Topics include:
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🔐 Onboarding, auth, and security
🧠 LLMs + fraud detection
🧰 Dev tooling + API design
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This is where fintech’s toughest engineering challenges get unpacked.
It’s all happening August 4–6 in Denver.
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