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AAAbstract Algorithmsabstractalgorithms.devApr 17 · 17 min read

Managed API LLMs vs Self-Hosted Models: When to Switch and When Not To

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

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MVMohit Vermaaiwithmohit.hashnode.devApr 9 · 3 min read

We Rebuilt Our RAG Pipeline 4 Times — Here's the Architecture That Finally Served 50K Daily Queries Under 800ms

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...

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AAAbstract Algorithmsabstractalgorithms.devMar 29 · 23 min read

LLM Model Selection Guide: GPT-4o vs Claude vs Llama vs Mistral — When to Use Which

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

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AAAbstract Algorithmsabstractalgorithms.devMar 29 · 20 min read

Context Window Management: Strategies for Long Documents and Extended Conversations

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

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MSManuela Schrittwieserneuralstackms.techMar 2 · 9 min read

Building Production-Grade AI-Powered SaaS

Introduction Building a SaaS platform has become increasingly synonymous with integrating AI capabilities. But here's what many teams get wrong: an AI-powered SaaS isn't just a traditional SaaS applic

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UMUmesh Malikumesh-malik.hashnode.devFeb 28 · 7 min read

RAG vs Fine-Tuning for LLMs (2026): Production Guide

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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UMUmesh Malikumesh-malik.hashnode.devFeb 27 · 7 min read

RAG vs Fine-Tuning for LLMs (2026): What Actually Works in Production

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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MSManuela Schrittwieserneuralstackms.techFeb 23 · 6 min read

The 2026 Developer Guide to Vector Databases

Vector databases are no longer “experimental AI tooling.” In 2026, they are foundational infrastructure for search, copilots, internal knowledge systems, recommender engines and AI-native products. Ho

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MSManuela Schrittwieserneuralstackms.techFeb 9 · 5 min read

Building AI Features into Apps: OpenAI, Ollama and Hugging Face

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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MSManuela Schrittwieserneuralstackms.techFeb 2 · 6 min read

Guide to Fine-Tuning Large Language Models

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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Trending tags this week

Managed API LLMs vs Self-Hosted Models: When to Switch and When Not To

We Rebuilt Our RAG Pipeline 4 Times — Here's the Architecture That Finally Served 50K Daily Queries Under 800ms

LLM Model Selection Guide: GPT-4o vs Claude vs Llama vs Mistral — When to Use Which

Context Window Management: Strategies for Long Documents and Extended Conversations

Building Production-Grade AI-Powered SaaS

RAG vs Fine-Tuning for LLMs (2026): Production Guide

RAG vs Fine-Tuning for LLMs (2026): What Actually Works in Production

The 2026 Developer Guide to Vector Databases

Building AI Features into Apps: OpenAI, Ollama and Hugging Face

Guide to Fine-Tuning Large Language Models