Prompt Engineering for Stable Diffusion
Learn how to craft effective prompts for Stable Diffusion using prompt structuring, weighting, negative prompts, and more to generate high-quality AI images.
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Understanding prompt engineering parameters
Learn how to optimize LLM outputs through strategic parameter settings. This practical guide explains temperature, top-p, max tokens, and other key parameters with real examples to help AI developers get precisely the responses they need for different use cases.
Model Context Protocol (MCP): Everything You Need to Know to Get Started
Learn how Model Context Protocol (MCP) revolutionizes AI integration, eliminating custom code and enabling standardized communication between LLMs and external systems. [Complete Guide with Examples]
COSTAR Prompt Engineering: What It Is and Why It Matters
Discover how Costar prompt engineering brings structure and efficiency to AI development. Learn this systematic approach to creating better prompts that improve accuracy, reduce hallucinations, and lower costs across different language models.
Mastering role prompting: How to get the best responses from LLMs
Learn how to get better AI responses through role prompting. This guide shows developers how to make LLMs respond from specific expert perspectives with practical examples and best practices.
Delimiters in Prompt Engineering
Learn how to use delimiters in prompt engineering to improve AI responses. This blog explains delimiter types, best practices, and practical examples for developers working with large language models
LLM Grounding: How to Keep AI Outputs Accurate and Reliable
Learn how to build reliable AI systems through LLM grounding. This technical guide covers implementation methods, real-world challenges, and practical solutions
Lifecycle of a Prompt
Learn how to master the prompt lifecycle for LLMs - from initial design to production monitoring. A practical guide for AI teams to build, test, and maintain effective prompts using Portkey's comprehensive toolset.
Challenges Agentic AI Companies Face in Enterprise Adoption
In this blog, we'll walk through the key hurdles teams face when bringing Agentic AI into enterprise environments
What is LLM Orchestration?
Learn how LLM orchestration manages model interactions, cuts costs, and boosts reliability in AI applications. A practical guide to managing language models with Portkey
Types of AI Guardrails and When to Use Them
A technical guide to implementing AI guardrails - covering input validation, output filtering, knowledge management, rate limiting, and compliance controls for production AI systems. Learn implementation patterns for safe, reliable AI deployment.
Why financial firms need granular governance for Gen AI
Learn how granular governance helps financial institutions scale AI systems securely, from maintaining compliance and protecting data to controlling costs and preventing misuse.
The State of AI FinOps 2025: Key Insights from FinOps Foundation's Latest Report
AI spending has doubled in enterprise environments, with a clear focus on establishing fundamentals before optimization. Dive into the latest FinOps Foundation report to understand how organizations are managing their AI infrastructure costs and what this means for your GenAI initiatives.
This is a summary blog focusing on AI trends
Open WebUI vs LibreChat: Choose the Right ChatGPT UI for Your Organization
Every organization wants to harness AI's transformative power. But the real challenge isn't accessing AI – it's doing so while maintaining complete control over your data. For healthcare providers handling patient records, financial institutions managing transactions, or companies navigating GDPR, this isn't just a technical preference – it's a business imperative.
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