Browsing: prompt

print(“\nPART 5 ── Datasets & experiments ————————————–“) DATASET = “capital-cities-tutorial” langfuse.create_dataset(name=DATASET, description=”Capital-city QA benchmark”) _items = [ (“What is the capital of France?”, “Paris”), (“What is…

if proxy_alive(): print(“\n[10] Mixed 10-prompt workload…”) workload = [ “Capital of France?”, “Read foo.py”, “Type hint for a list of dicts”, “Lowercase: HELLO”, “One-sentence summary of…

Most ML projects do not fail because of model choice. They fail in the messy middle: finding the right dataset, checking usability, writing training code, fixing…

Image by Editor   # Introduction  Creating a website is significantly more accessible than it was in the past. Artificial intelligence website builders can now generate a…

AI demos often look impressive, delivering fast responses, polished communication, and strong performance in controlled environments. But once real users interact with the system, issues surface…

Image by Author   # Introduction  Prompt engineering had its moment to shine for a reason. It was the fastest way to get useful behavior out of…

I’ve always been a proponent of using Gemini in Google Sheets to help me generate new sheets, clean and organize data, analyze and visualize information, pull…

Summary created by Smart Answers AIIn summary:PCWorld reveals an effective AI prompting strategy for major decisions that focuses on balanced analysis rather than biased recommendations.The approach…

Prompt engineering has become the most practical AI skill you can learn today. Whether you’re using ChatGPT, Claude, or Gemini, the quality of your prompts directly…

Large context windows have dramatically increased how much information modern language models can process in a single prompt. With models capable of handling hundreds of thousands—or…