#Prompt Engineering
44 articles with this tag
AI Search Isn't Keywords, It's Topics
AI search requires a shift from keywords to topics and prompts, using data-driven analysis of interest scores and competitor gaps.
Langfuse: Domain Expertise Crucial for AI Self-Improvement
Langfuse's Annabelle Schäfer explains why domain expertise is crucial for AI self-improvement, advocating for high-signal target functions and expert-driven data.
AI Agents Need Feature Flags for Safety, Says Engineer
Backend engineer Sachin Gupta argues AI agents need specialized feature flags beyond traditional tools to manage their complex behaviors and mitigate risks.
Context Engineering: Making AI Smarter and More Reliable
Google Senior AI Engineer Smitha Kolan explains context engineering, a key technique for building more reliable AI systems by curating data inputs instead of simply lengthening prompts.
AI Workforce Management: The New Train Wreck
AI's promise has inverted, making humans cheaper. Now, effective AI workforce management is critical to avoid costly inefficiencies and harness true potential.
Ted Johnson on AI: Prompts as Punch Cards
Ted Johnson of JoinIn AI argues that AI interaction is stuck in the past, comparing prompts to punch cards and calling for a shift towards more natural, participatory AI design.
Rachel Nabors: Local AI Models for Frontier Results
Rachel Nabors advocates for using smaller, on-device AI models, showcasing their efficiency, cost savings, and performance benefits over large frontier models.
Dominik Tornow: The Prompt is the Platform in AI
Dominik Tornow of Resonate argues that AI development is shifting towards prompt engineering, making 'The Prompt is the Platform' a reality by 2026.
CrewAI: Taming AI Agent Costs
CrewAI outlines strategies to combat rising AI agent costs by optimizing token spend through orchestration and infrastructure controls.
Vincent Koc on Adaptive AI Evaluation
Vincent Koc of Comet ML discusses the limitations of static AI evaluation and the shift towards adaptive, intent-based methods for measuring AI agents.
Samuel Colvin on Optimizing AI Agents in Production
Samuel Colvin, Pydantic CEO, discusses optimizing AI agents in production using GEPA and Logfire's managed variables at AI Engineer Europe.
Andrej Karpathy: AI Models Need Human-Like Reasoning
Andrej Karpathy discusses the evolution of AI from programming to prompting, emphasizing the current need for models to develop human-like reasoning.
AI Agents Failures & How To Stop Them
Danilo Campagna from Posthog discusses common LLM code generation failures and strategies for improvement, focusing on context, architecture, and human error.
Cloudflare's AI Code Review Overhaul
Cloudflare has engineered a sophisticated, multi-agent AI code review system to eliminate bottlenecks and improve code quality.
OpenAI's Ryan Lopopolo on Harnessing AI for Software Engineering
OpenAI's Ryan Lopopolo discusses how AI agents are reshaping software engineering, emphasizing the shift towards human oversight and strategic prompt design.
7 Skills for Effective Agent Engineering
IBM AI Engineer Bri Kopecki outlines 7 key skills for building effective AI agents, emphasizing system design, tool integration, and reliability beyond basic prompt engineering.
OpenAI's Prompting Playbook
OpenAI outlines essential steps for crafting effective AI prompts, emphasizing clarity, context, and output specification for better results.
ChatGPT's New Image Generation
OpenAI's ChatGPT now generates images from text prompts, enabling rapid visual content creation and iteration through precise user instructions.
ChatGPT: Your AI Writing Assistant
OpenAI details how ChatGPT can act as a powerful co-pilot for professional writing, streamlining drafting, revision, and audience adaptation.
LLM Evaluators: Beyond Naive Judgments
Mahmoud Malaeb of Argenta discusses the limitations of naive LLM judges and introduces GEPA, an optimization framework for building more accurate LLM evaluators using a data flywheel approach.
Meta-Harness: AI Optimizes AI Development
Researchers unveil Meta-Harness, a novel AI system that automates harness optimization, leading to faster and more capable LLMs.
OpenAI Tames AI Chaos with Instruction Hierarchy
OpenAI's new IH-Challenge dataset trains AI models to prioritize instructions, enhancing safety and mitigating risks like prompt injection.
Cracking OpenAI's Training Data Secrets
A novel emoji-based technique allows researchers to infer the composition of OpenAI's training data, suggesting the inclusion of reasoning traces.
Salesforce AI Careers: A New Talent Pipeline Emerges
Dynamic UI Controls Elevate AI Prompt Refinement
Brave Leo Skills Streamline Browser AI Workflows
Salesforce SLDS 2 Ushers in Agentic AI Era for UI Design
Engineering Predictability: The Evolution of LLM Prompting
Microsoft's ECHO Language Model learns from failure
Gemini 2.5 Pro Transforms Video Processing with Single API Calls
Ayo Adedeji, Google\'s Developer Relations Engineer, boldly declared, \"Or, you could just not do any of that.
Gemini 2.5 Pro Transforms Video Processing with Single API Calls
Ayo Adedeji, Google\'s Developer Relations Engineer, boldly declared, \"Or, you could just not do any of that.
Prompt Engineering: The New Literacy for an AI-Augmented Future
Agentic AI Marketing Skills: 5 Essential Competencies Every Marketer Needs in 2025
Marketers must become expert "creative directors" for AI systems, crafting detailed briefs that produce on-brand, engaging content at scale.
Agentic AI Marketing Skills: 5 Essential Competencies Every Marketer Needs in 2025
The marketing landscape is experiencing its biggest transformation since the digital revolution.
The 100-Page Prompt and Nano Banana
Nano Banana and the emergence of a 100-page prompt, as detailed in a recent \"Mixture of Experts\" podcast featuring Tim Hwang, Aaron Baughman, Chris Hay, an...
The 100-Page Prompt and Nano Banana
Nano Banana and the emergence of a 100-page prompt, as detailed in a recent \"Mixture of Experts\" podcast featuring Tim Hwang, Aaron Baughman, Chris Hay, an...
Braintrust Unveils Loop, Automating AI Model Evaluation
Warp Redefines Developer Workflow with AI-Native Terminal
The Unseen Tide: Decoding and Defeating AI Slop
ChatGPT's Visual Leap: A New Frontier in Prompt-Driven Creation
How to Master AI Interaction and The Art of Effective Prompt Engineering
Few-shot prompting involves providing examples of the desired output format or style. If an AI is asked to convert technical jargon into plain language, offering a few pairs of original and simplified sentences can significantly improve the quality and consistency of its subsequent conversions.
Mastering AI Fluency and Prompting Through Comprehensive Description
The first critical element of this descriptive mastery is PRODUCT DESCRIPTION: the ability to clearly define the characteristics of your desired output.
Prompt Optimization on Amazon Bedrock and Multi-Adapter Inference with SageMaker
<p>Users can optimize prompts across multiple models with a single API call.</p><p>Dynamic loading of adapters based on requests, facilitating hyper-personalized solutions in various industries.</p>
