Recipes

Guidelines on how to effectively forecast using our API.

Writing good questions

Foresight works best when the question has clear resolution criteria: the event or value, the threshold, and the deadline.

• Name the event and deadline. "Will the Federal Reserve lower the target federal funds rate by at least 25 bps by December 31, 2026?" is clearer than "Will the Fed cut soon?"

• Use measurable thresholds. "Will the S&P 500 close above 7,000 on December 31, 2026?" is clearer than "Will stocks do well?"

• Ask one thing and choose the right answer type. Use binary for yes/no, continuous for a number, and multiple_choice for a fixed set of outcomes.

Improving accuracy

• Gather and provide relevant context.

• Turn on research for questions that depend on recent events—it lets the model gather live evidence and attach sources you can inspect via result.sources.

• Use ensemble predictions. Send the same request multiple times and use the median response.

• Fine-tune on your domain (enterprise). If you want to achieve better accuracy and cost on your domain, leveraging your internal data, see our enteprise platform.

Optimizing costs

• Curate your context. Implement custom context aggregation logic, tuned for your forecasting question.

• Use low reasoning. This will significantly reduce token usage, while still maintaining accuracy edge over the current frontier models. Note: avoid setting low max_tokens as this can result in the response being truncated during reasoning and no final prediction captured. Use "low" reasoning effort instead.