6d ago · 16 min read · TLDR: Most teams should start with managed LLM APIs because they buy speed, reliability, model quality, and low operational burden. Move to self-hosted or open-weight models only when you have stable workloads, hard privacy or compliance constraints,...
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Apr 9 · 3 min read · We Rebuilt Our RAG Pipeline 4 Times — Here's the Architecture That Finally Served 50K Daily Queries Under 800ms Building a production RAG system that scales is harder than it looks. We learned this the hard way—through four complete rebuilds, each ex...
Join discussionMar 29 · 21 min read · TLDR: 🧠 Choosing the right LLM can save you 80% on costs while maintaining quality. This guide provides a decision framework, cost comparison, and practical examples to help engineering teams select between GPT-4o, Claude, Llama, and Mistral based o...
Join discussionMar 29 · 19 min read · TLDR: 🧠 Context windows are LLM memory limits. When conversations grow past 4K-128K tokens, you need strategies: sliding windows (cheap, lossy), summarization (balanced), RAG (selective), map-reduce (scalable), or selective memory (precise). LangCha...
Join discussionFeb 28 · 7 min read · TL;DR RAG is still the default for fast-changing knowledge, citations, and compliance-heavy use cases. Fine-tuning is for behavior, not your constantly changing knowledge base. Long context did not kill RAG; recent benchmarks show there is no univer...
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Feb 27 · 7 min read · TL;DR RAG is still the default for fast-changing knowledge, citations, and compliance-heavy use cases. Fine-tuning is for behavior, not your constantly changing knowledge base. Long context did not kill RAG; recent benchmarks show there is no univer...
Join discussionFeb 9 · 5 min read · AI Is Now Application Infrastructure AI is no longer an experiment or a bolt-on feature. In modern products, it behaves like core infrastructure similar to authentication, search or payments. The difference:AI systems are probabilistic, model-driven ...
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Feb 2 · 6 min read · From Basics to Breakthroughs: Technologies, Research, Best Practices, and Applied Challenges 1. Introduction Large Language Models (LLMs) have transitioned from experimental research artifacts to foundational infrastructure for modern software syste...
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