cost-tracking

Teams are encountering increasing challenges in managing AI costs as usage scales across multiple teams and models, highlighting the need for strategies to evaluate workflow costs and implement efficient tracking.

Sapiom raises $35M Series A to build infrastructure for AI agents, focusing on cost management and launching three new products. The tweet highlights capabilities like multi-vendor API key management, per-agent cost tracking, and observability.

ccusage is an open-source command-line tool that helps developers inspect token usage and costs from local coding-agent CLI data, offering daily/weekly/monthly reports, model breakdowns, and JSON export.

DepthData is a system of record for tracking and managing a company's AI spending.

agentglass is an open-source local dashboard that provides real-time monitoring, cost tracking, and fleet management for multiple AI coding agents like Claude Code, Codex, and Gemini.

A developer shares a personal experience of unexpectedly high costs from a multi-agent AI system, sparking a discussion on cost tracking and observability in agent frameworks.

Trovis is a plugin for OpenClaw that records all agent actions, costs, and deviations, presenting them in plain English for better observability.

A developer argues that most production AI agents lack essential observability like session traces and cost tracking, comparing it to deploying a web app without monitoring. The article questions whether agent observability is an unsolved problem.

A tool to help developers accurately track AI costs while coding, eliminating guesswork.

A developer argues that voice call logs must include cost and token data, not just duration and status, to properly assess voice-agent economics, sharing a lesson from a stress test where cost fields were initially null.