AI Engineering Insights
from the Tensorplay Team
Featured Posts
RAG vs Fine-Tuning: How to Choose the Right Approach for Your LLM
One of the most common questions we get from engineering teams is: "Should we fine-tune our model or...
Why Your LLM Prototype Fails in Production (And How to Fix It)
Every week, a startup team demos their new LLM-powered product and it looks brilliant. The model ans...
Recent Posts
Reducing LLM Inference Costs by 60%: A Case Study
When a B2B SaaS company came to us, their AI features were a success story — too successful. Their m...
From PoC to Production: An Honest Engineering Timeline
One of the most frequent conversations we have with new clients starts the same way: "We have a work...
Securing AI Applications: The Threat Model You Haven't Thought About
Enterprise teams investing in AI security are mostly focused on the wrong things. Compliance checkli...
Fine-Tuning Llama 3 with QLoRA: A Practical Guide
QLoRA (Quantized Low-Rank Adaptation) changed the economics of LLM fine-tuning. Before QLoRA, fine-t...
Designing AI-Powered APIs: Patterns and Pitfalls
Building an API that wraps an AI model sounds straightforward — take input, call model, return outpu...
Building a Multi-Agent AI System That Actually Works in Production
The demos for multi-agent AI frameworks look incredible. Autonomous agents planning, executing, and ...
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