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Practical articles on AI, DevOps, Cloud, Linux, and infrastructure engineering.

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Real-World RAG Incidents: Lessons from a Production Rollout
••March 22, 2025

Real-World RAG Incidents: Lessons from a Production Rollout

A field report from rolling out retrieval-augmented generation in production, including cache bugs, bad embeddings, and how we fixed them.

KU
Kiril urbonas
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Real-World RAG Incidents: Lessons from a Production Rollout
••March 15, 2025

Real-World RAG Incidents: Lessons from a Production Rollout

A field report from rolling out retrieval-augmented generation in production, including cache bugs, bad embeddings, and how we fixed them.

KU
Kiril urbonas
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Troubleshooting: LLM Gateway Design for Multi-Provider Inference
••March 9, 2025

Troubleshooting: LLM Gateway Design for Multi-Provider Inference

LLM Gateway Design for Multi-Provider Inference. Practical guidance for reliable, scalable platform operations.

KU
Kiril Urbonas
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Real-World RAG Incidents: Lessons from a Production Rollout
••March 8, 2025

Real-World RAG Incidents: Lessons from a Production Rollout

A field report from rolling out retrieval-augmented generation in production, including cache bugs, bad embeddings, and how we fixed them.

KU
Kiril urbonas
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Real-World RAG Incidents: Lessons from a Production Rollout
••March 1, 2025

Real-World RAG Incidents: Lessons from a Production Rollout

A field report from rolling out retrieval-augmented generation in production, including cache bugs, bad embeddings, and how we fixed them.

KU
Kiril urbonas
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AI Agents in DevOps: From Copilots to Autonomous Automation in 2025
••February 28, 2025

AI Agents in DevOps: From Copilots to Autonomous Automation in 2025

How AI agents are moving from read-only copilots to autonomous automation with guardrails. Best practices for approval gates and rollback.

KU
Kiril urbonas
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Field Notes: LLM Gateway Design for Multi-Provider Inference
••December 1, 2024

Field Notes: LLM Gateway Design for Multi-Provider Inference

LLM Gateway Design for Multi-Provider Inference. Practical guidance for reliable, scalable platform operations.

KU
Kiril Urbonas
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Deep Dive: LLM Gateway Design for Multi-Provider Inference
••May 20, 2024

Deep Dive: LLM Gateway Design for Multi-Provider Inference

LLM Gateway Design for Multi-Provider Inference. Practical guidance for reliable, scalable platform operations.

KU
Kiril Urbonas
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Practical Guide: LLM Gateway Design for Multi-Provider Inference
••February 13, 2024

Practical Guide: LLM Gateway Design for Multi-Provider Inference

LLM Gateway Design for Multi-Provider Inference. Practical guidance for reliable, scalable platform operations.

KU
Kiril Urbonas
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Fine-tuning Large Language Models: A Practical Guide
••February 12, 2024

Fine-tuning Large Language Models: A Practical Guide

Learn how to fine-tune LLMs like Llama 2, Mistral, and GPT models for your specific use case. Includes LoRA, QLoRA, and full fine-tuning techniques.

KU
Kiril Urbonas
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Fine-tuning Llama 3 on Consumer Hardware
••January 1, 2024

Fine-tuning Llama 3 on Consumer Hardware

Optimization techniques like LoRA and 4-bit quantization to run state-of-the-art models locally.

KU
Kiril Urbonas
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