AI Logs API: A Practical Guide to Useful Events
Design AI events that connect requests, model attempts, validation, and outcomes without filling logs with sensitive content.
KNOWLEDGE FOR THE OBSERVABLE STACK
Every event.
A clearer story.
Make sense of AI logs, application events, and everything in between. Practical guides for the people building a more understandable stack.
19 topic guides. 10 deeper reads.
From the first event to the full picture.
THE EVENT VIEWILLUSTRATIVE
A request, explained.
Different systems. Shared context.
- request.acceptedRequest context established
+0 ms - model.completedUsage recorded · content omitted
+840 ms - response.sentApplication outcome recorded
+912 ms
EVENT RECORD / JSON
{
"event": "model.completed",
"request_id": "req_example_42",
"attempt": 1,
"latency_ms": 840,
"usage": {
"input_tokens": 1024,
"output_tokens": 216
},
"content_capture": "off"
}A small event. Enough context to investigate.
AI / CODE / PEOPLE / INFRASTRUCTUREFollow the signals
THE LOGSAPI UNIVERSE
Your stack.
Every side of the story.
One connected collection of guides. Pick a system, understand its events, and see how the pieces fit together.
Browse the topic directory/01
AI & LLM
Follow model requests, conversations, prompts, token usage, and agent actions.
/02
Developer operations
Connect application behavior to source changes, services, hosts, and mobile devices.
/03
Connected work
Understand the events between a message, a call, a customer record, and a meeting.
/04
Identity & assets
Build useful evidence around sign-in decisions, wallet activity, and tokenized assets.
THE SIGNAL / FIELD NOTES
A little context.
A lot more clarity.
Go deeper with practical explanations, useful examples, and the tradeoffs behind a good logging decision.
Read all 10 articles
LLM Token Logging: Measure Usage, Latency, and Cost
Build an interpretable record of LLM usage, timing, retries, and cost estimates while preserving incomplete accounting states.
Agent Logs: Trace Tool Calls, Retries, and Outcomes
Connect agent runs to their tool calls, permissions, retries, parallel work, and final outcomes through a clear execution record.
BUILD WITH INTENTION
Good logs start
with good questions.
A useful event makes the next investigation easier. Design around the evidence you need and the context you can responsibly keep.
Build a better pipeline01
Give the event a meaning.
Name the thing that happened. An accepted request, a finished attempt, and a verified outcome each answer a different question.
02
Keep the connection.
Preserve the identifiers that relate a request to its attempts and downstream work. The relationship often explains more than another payload dump.
03
Know what to leave out.
Choose fields deliberately. Treat access, sensitive content, and retention as part of the logging design from the beginning.
A FEW GOOD QUESTIONS
Find your
starting point.
New to logs, APIs, or observability? Begin here and follow the topic that fits your work.
What is a logs API?
A logs API is an interface for sending, retrieving, or querying event records. The useful details depend on the system: a timestamp, an event type, a source, an outcome, and identifiers that connect related work. Start with the AI logging guide for an example of how to design that context.
Where should I start with AI and LLM logs?
Start with a question you want to answer: which attempt failed, why the response was slow, or where the usage came from. Then choose a small event contract. The LLM topic guide covers request and attempt context; the Token guide focuses on usage evidence.
How are logs different from traces?
A log records an event or observation. A trace connects timed operations in a request or workflow. Used together, they can help you move from a specific event to the surrounding work. The agent tracing article explores those relationships in multi-step tasks.
Should prompts, credentials, or message bodies be logged?
Decide what the investigation actually requires before collecting content. Metadata is often a useful starting point; secrets and authentication material should stay out of routine diagnostics. Read the prompt privacy guide for version references, access, and retention decisions.
What can I find on LogsAPI.com?
LogsAPI.com is a collection of topic guides and practical articles for developers and technical teams. Explore all 19 topics, from AI and agents to Linux, CRM, and MFA, or browse The Signal for longer explanations.