Releases·Tool Release
Blazo: open-source local, real-time observability for AI agents (MVP on GitHub)
Blazo, an open-source observability product for AI agents, is available on GitHub as an MVP. It ingests agent telemetry — runs, traces, tool calls, LLM calls, errors, latency, tokens — and shows execution live in a local UI with no account required. It targets developers debugging why agents are slow, stuck, or failing, and is explicitly not an agent builder, playground, or evaluation platform.
45 engagement1 sourceSun, Sep 27, 2026, 01:55 PM
AI Overview
- Blazo is open-source AI-agent observability tracking runs, traces, tool/LLM calls, errors, latency, tokens, plus stuck-loop detection — install locally, no account
- Built with TypeScript, Bun, Next.js, OpenTelemetry, and SQLite; currently an MVP targeting diagnostics of slow, stuck, or failing agents, not a builder or eval platform
Related
Products·building
Tracewell: Open-source observability dashboard for AI agents
Tracewell is an early open-source observability tool that lets developers add a tiny Python SDK to their AI agent applications to inspect traces locally in a dashboard. It captures prompts, responses, latency, token usage, estimated cost, success/error status, tool calls, and rule-based failure detection, helping developers debug and monitor agent performance.
Tracewell is an early open-source observability tool that lets developers add a tiny Python SDK to their AI agent applications to inspect traces locally in a dashboard. It captures prompts, responses, latency, token usage, estimated cost, success/error status, tool calls, and rule-based failure detection, helping developers debug and monitor agent performance.
1 engagement1 sourceredditTue, Jul 28, 2026, 12:26 PM
Releases·Tool Release
Obyflow – open-source, CLI-first observability tool for debugging AI apps
Obyflow, an open-source and free CLI-first observability tool for debugging AI applications, has been released on GitHub. It consolidates traces, LLM calls, vector searches, errors, and framework steps into one view to help developers diagnose failures. Its release gives practitioners a dedicated debugging path for AI apps without a paid platform.
Obyflow, an open-source and free CLI-first observability tool for debugging AI applications, has been released on GitHub. It consolidates traces, LLM calls, vector searches, errors, and framework steps into one view to help developers diagnose failures. Its release gives practitioners a dedicated debugging path for AI apps without a paid platform.
1 engagement1 sourceredditSat, Sep 12, 2026, 05:22 AM
Products·building
Local-first debugger for AI agent execution with SQLite traces
TraceMotive is a local-first tracing and debugging tool for AI agent execution, providing step-by-step visibility into agent runs. It uses SQLite to store traces and spans, and offers a timeline and inspector to help developers understand and fix agent behavior. Built by a non-traditional developer using AI-assisted development, it addresses the need for clearer debugging in AI agent workflows.
TraceMotive is a local-first tracing and debugging tool for AI agent execution, providing step-by-step visibility into agent runs. It uses SQLite to store traces and spans, and offers a timeline and inspector to help developers understand and fix agent behavior. Built by a non-traditional developer using AI-assisted development, it addresses the need for clearer debugging in AI agent workflows.
2 engagement1 sourceredditWed, Aug 12, 2026, 02:13 PM
Products·launched
Traccia: Vendor-neutral observability and runtime governance for AI agents
Traccia is a platform that provides observability, evaluation, runtime policy enforcement, and auditing for AI agents. It uses an open-source SDK that integrates with existing code with minimal changes, enabling developers to govern autonomous agent actions. It solves the problem of insufficient tracing and observability tools for the AI agent era.
Traccia is a platform that provides observability, evaluation, runtime policy enforcement, and auditing for AI agents. It uses an open-source SDK that integrates with existing code with minimal changes, enabling developers to govern autonomous agent actions. It solves the problem of insufficient tracing and observability tools for the AI agent era.
1 engagement1 sourcehackernewsFri, Aug 21, 2026, 06:20 PM
Products·launched
Local terminal observability dashboard for Claude Code and Codex
Aether provides a live terminal dashboard that visualizes native local traces from Claude Code and Codex, showing context growth, cost, latency, tools, compactions, code changes, agents, and per-turn input work. It requires no SDK, API key, cloud backend, or additional model calls, solving the problem of understanding and debugging LLM agent behavior locally for developers using these tools.
Aether provides a live terminal dashboard that visualizes native local traces from Claude Code and Codex, showing context growth, cost, latency, tools, compactions, code changes, agents, and per-turn input work. It requires no SDK, API key, cloud backend, or additional model calls, solving the problem of understanding and debugging LLM agent behavior locally for developers using these tools.
1 engagement1 sourceredditFri, Jul 17, 2026, 07:39 PM