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Documentation Index

Fetch the complete documentation index at: https://docs.olly.new/llms.txt

Use this file to discover all available pages before exploring further.

When interacting with Olly, you can choose how Olly answers your questions by selecting a mode before sending your prompt. Each mode is optimized for a different type of task, balancing speed and depth of reasoning. You can change the mode at any time while chatting with Olly.

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Supported modes

Olly currently supports two modes:
  • Fast mode: optimized for speed and simplicity.
  • Focus mode: optimized for deeper reasoning and investigation.
Fast Mode demo You can choose a mode from the input bar each time you send a prompt, and it takes effect immediately. Switching modes is possible at any time during the conversation. This allows you to start fast and switch to deeper analysis only when needed.

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Fast mode

Fast mode is designed for quick responses and lightweight tasks.
  • Model used: GPT-5 mini
  • Best for:
    • Simple questions
    • Quick lookups
    • Basic data queries
  • Characteristics:
    • Very fast response time
    • Simplified reasoning optimized for speed
Use Fast mode when you need a quick answer to simple questions, fast lookups, or basic data queries where speed matters more than deep reasoning. Examples:
  • “Show error rate for checkout service in the last hour”
  • “What is the current CPU usage of node-3?”
  • “List alerts fired in the last 10 minutes”

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Focus mode (default)

Focus mode is Olly’s default and most powerful mode.
  • Model used: GPT-5.1
  • Best for:
    • Complex investigations
    • Root-cause analysis
    • Exploratory observability questions
  • Characteristics:
    • Deeper analysis and reasoning
    • Takes longer to respond than Fast mode
    • Uses multiple specialized sub-agents, each acting as an expert in a specific domain (for example, logs agent).
Choose Focus mode for in-depth analysis tasks, such as investigating issues, uncovering root causes, or exploring observability data that require a deeper level of analysis. Examples:
  • “Why did latency spike after the last deployment?”
  • “Investigate the root cause of intermittent 5xx errors”
  • “Correlate error logs with recent infrastructure changes”