Being a System Architect in the Age of AI: Tools Change, But the
How is the artificial intelligence revolution affecting system architecture? With 20 years of experience, I evaluate AI's promises and the unchanging.
21 posts found.
How is the artificial intelligence revolution affecting system architecture? With 20 years of experience, I evaluate AI's promises and the unchanging.
A practical guide on strategies to optimize the cost and freshness of embeddings in AI applications. Data changes, re-indexing, and…
Strategies for balancing cost and performance when serving AI models. Pragmatic approaches and real-world experiences.
My experiences with architectural trade-offs and their operational costs when designing AI agent tool-use capabilities.
I examine the quality of Retrieval-Augmented Generation (RAG) systems in my side projects and whether it always needs to be at the highest level...
Exploring defense mechanisms against prompt injection attacks targeting large language models and the associated costs...
Develop actionable and effective strategies in 5 steps to protect Large Language Models (LLMs) from Prompt Injection attacks. Practical solutions based on my.
I explore methods for improving retrieval quality in Retrieval-Augmented Generation (RAG) systems, with concrete examples and cost analyses.
I provide a pragmatic perspective by examining the cost and performance limits of AI agents' tool usage with real-world scenarios.
I examine the limits of AI agents' tool usage and the complexity introduced by adding more tools. Practical takeaways from my real-world experiences.
I examine the real-world advantages and disadvantages of running your own LLM locally in terms of cost, performance, and flexibility.
I examine the measures I've taken against prompt injection in AI applications, their costs, and their practical effectiveness based on my own experiences.
I explain the intricacies of LLM inference caching and what to consider when balancing cost and latency, with practical examples.
A deep dive into the real-world risks of agent tool usage and why these risks are often overlooked, based on Mustafa Erbay's experiences...
I delve deep into the idempotency issues I encountered in an AI-powered pipeline, the resulting data loss, and my solution process. Real-world experiences and.
I'm sharing how I step-by-step resolved an unexpected error I encountered in an AI pipeline on a Sunday morning, and the lessons I learned from the process.
I'm sharing my experiences with hidden mistakes in AI projects that unknowingly consume time and resources, based on my own side project.
Ensuring data integrity in AI-powered content pipelines is critical. I'll share practical approaches, from ingestion to output, for issues I've encountered in.
I explain how I design and implement retry and idempotency mechanisms to effectively manage errors encountered in AI pipelines.
Discover what AI model drift is, its types, its silent effects in production, and how we can build proactive strategies to counter this critical threat.
Find out how machine-learning models lose performance over time and why Model Drift is a silent killer for the AI systems you run in production...