Start Simple, Ship Fast
Building an AI application is more accessible than ever. You do not need a PhD or massive compute resources. With AI APIs, you can add intelligent capabilities to any application with a few lines of code.
Choose Your Approach
API-first: Use Claude, GPT, or Gemini APIs to add AI to your existing application. This is the fastest path — no model training or infrastructure management. Open-source model: Run Llama or Mistral locally for privacy and control, but be prepared to manage infrastructure.
Start with an API unless you have specific privacy or cost requirements that demand local deployment.
Building Blocks
Prompt engineering: Craft effective prompts that get reliable, useful outputs from the model. Context management: Provide relevant information with each request (user data, documents, conversation history).
Output handling: Parse, validate, and present AI responses. Handle edge cases like model refusals, unexpected formats, and hallucinations. Error handling: Implement retries, fallbacks, and graceful degradation.
Your First Project Ideas
Start with something useful to you: a tool that summarizes articles, a chatbot that answers questions about your documentation, a writing assistant that matches your style, or an AI-powered content tagger.
The key is starting. Ship a simple version, get feedback, and iterate. For prompt engineering tips, see our dedicated guide.