N-Gram House - Page 3
Agentic Systems vs Vibe Coding: How to Pick the Right AI Autonomy for Your Project
Agentic coding lets AI build code on its own; vibe coding helps you build it together. Learn which approach fits your project-prototype, maintenance, or production-and how to avoid the hidden risks of each.
How Design Teams Use Generative AI for Wireframes, Creative Variations, and Asset Generation
Generative AI is transforming how design teams create wireframes, variations, and assets-cutting hours off workflows but requiring new skills. Learn how top teams use AI without losing creativity or control.
Choosing Opinionated AI Frameworks: Why Constraints Boost Results
Opinionated AI frameworks reduce choice to increase speed and results. Learn why constrained workflows outperform flexible tools in real-world use, from startups to Fortune 500 companies.
Text-to-Image Prompting for Generative AI: Master Styles, Seeds, and Negative Prompts
Master text-to-image prompting with styles, seeds, and negative prompts to generate high-quality AI images. Learn how Midjourney, Stable Diffusion, and Imagen 3 handle prompts differently in 2026.
Adapter Layers and LoRA for Efficient Large Language Model Customization
LoRA and adapter layers let you customize large language models with minimal resources. Learn how they work, when to use each, and how to start fine-tuning on a single GPU.
Replit for Vibe Coding: Cloud Dev, Agents, and One-Click Deploys
Replit lets you code, collaborate, and deploy apps in your browser with AI-powered agents and one-click launches. No setup. No installs. Just build.
Synthetic Data Generation with Multimodal Generative AI: Augmenting Datasets
Synthetic data generation using multimodal AI creates realistic, privacy-safe datasets by combining text, images, audio, and time-series signals. It's transforming healthcare, autonomous systems, and enterprise AI by filling data gaps without compromising privacy.
Scheduling Strategies to Maximize LLM Utilization During Scaling
Smart scheduling can boost LLM utilization by up to 87% and cut costs dramatically. Learn how continuous batching, sequence scheduling, and memory optimization make scaling LLMs affordable and fast.
Measuring Hallucination Rate in Production LLM Systems: Key Metrics and Real-World Dashboards
Learn how top companies measure hallucination rates in production LLMs using semantic entropy, RAGAS, and LLM-as-a-judge. Real metrics, real dashboards, real risks.
Ethical Considerations of Vibe Coding: Who’s Responsible for AI-Generated Code?
Vibe coding speeds up development but shifts ethical responsibility to developers who didn't write the code. Learn why AI-generated code is risky, how companies are handling it, and what you must do to avoid legal and security disasters.
Health Checks for GPU-Backed LLM Services: Preventing Silent Failures
Silent failures in GPU-backed LLM services cause slow, inaccurate responses without crashing - and most monitoring tools miss them. Learn the critical metrics, tools, and practices to detect degradation before users do.
Latency Management for RAG Pipelines in Production LLM Systems
Learn how to cut RAG pipeline latency from 5 seconds to under 1.5 seconds using Agentic RAG, streaming, batching, and smarter vector search. Real-world fixes for production LLM systems.
