Farol

What it does

AI agents fail silently and bill loudly. Farol tells you first. Add @trace to your agent and instantly get cost anomaly detection, full trace inspector, quality scoring, regression alerts, budget limits per agent, and a weekly digest email. No gateway. No proxy. No framework lock-in. Works with Anthropic, OpenAI, Gemini, LangChain, CrewAI, and more. Free tier · Open source SDK · From €20/mo

Monitor your AI agents automatically. One Python decorator tracks cost, latency, errors, and quality. Get alerts before your users do. Free tier, open source SDK.

Most developers find out their agent broke from an angry user. Farol tells you first. higher token costs after a prompt tweak last Tuesday. You noticed on Friday. from farol import trace @trace ( agent_name = "my-agent" , farol_key = "frl_..." ) def my_agent (task, run= None ): run[ "topic" ] = task # that’s it Product Farol tracks token spend per run and learns what's normal for each agent. The moment something costs 3× more than usual, you get an alert — before your cloud provider does. Set monthly budget limits and get notified the instant they're crossed. Open any run and see every tool call, LLM call, duration, and error reconstructed end to end. No log diving, no guessing. The trace…from usefarol.dev

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  Progress AI ObservabilityAug 2026 · telerik.com · ▲168

  Hi HN! We’re the team behind Fiddler, and we recently built an Agent Cache feature. It works by capturing an LLM request/response pair and, once caching is enabled, serving subsequent matching calls locally so duplicate requests never hit the provider. It’s meant to reduce three pains that show up together in agent development: token cost, feedback-loop latency, and output non-determinism. We’d love to hear your thoughts.

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  AI Observability by OpenObserveAug 2026 · openobserve.ai · ▲317

  OpenTelemetry-native observability for agents and LLMs

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  Oodle.ai – $10 per million agent tracesJul 2026 · oodle.ai · ▲31

  Hi HN, we're Kiran and Vijay! Over the past two years, we have built a columnar storage engine for observability: logs, metrics, and traces. Today, it's exciting for us to show what we've built on top of that foundation: LLM Agent Observability. Given how non-deterministic agents are, storing all traces without sampling was critical for us. But these traces tend to be in the MBs, sometimes GBs - we needed to store them inexpensively. We also needed the queries and analyses to be fast. To meet both these goals, we store them in S3 in our own parquet-like file format, and query them using AWS…

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  traceAIApr 2026 · github.com · ▲273

  Open-source LLM tracing that speaks GenAI, not HTTP.

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  FoilMar 2026 · getfoil.ai · ▲83

  An AI agent that monitors your AI agents

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  TraceaMay 2026 · tracea.dev · ▲80

  Datadog for AI agents with traces, RCA, and team memory

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  Germany's new sovereign AI model Kolibri▲424

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  Brila▲1,364

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  Life & fun · Apr 2026 · jaso1024.com

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  I built a tiny LLM to demystify how language models work▲915

  Built a ~9M param LLM from scratch to understand how they actually work. Vanilla transformer, 60K synthetic conversations, ~130 lines of PyTorch. Trains in 5 min on a free Colab T4. The fish thinks the meaning of life is food. Fork it and swap the personality for your own character.

  AI · Apr 2026 · github.com

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  Fathom 3.0▲800

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  AI · Apr 2026 · fathom.ai

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  Brutalist Concrete Laptop Stand (2024)▲786

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  Life & fun · Apr 2026 · sam-burns.com

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  I built a frontpage for personal blogs▲783

  With social media and now AI, its important to keep the indie web alive. There are many people who write frequently. Blogosphere tries to highlight them by fetching the recent posts from personal blogs across many categories. There are two versions: Minimal (HN-inspired, fast, static): https://text.blogosphere.app/ Non-minimal: https://blogosphere.app/ If you don't find your blog (or your favorite ones), please add them. I will review and approve it.

  AI · Apr 2026 · text.blogosphere.app