Long-Term Analysis of Langfuse LLM Traces with ClickHouse
A verification log on normalizing Langfuse Observations and Scores into ClickHouse, then using SQL to inspect model-level cost, prompt-version quality trends, and retry-driven cost increases.
Tag
#agentops
Building the Foundation of an AI Chatbot with Cloudflare Pages, Workers, and AI Gateway
A small implementation experiment combining Cloudflare Pages, Pages Functions, Workers AI bindings, and AI Gateway to build an AI chatbot without exposing model credentials to the browser.
The Loop Ran, but I Could Not Tell What Worked
A verification article on sending a generate, evaluate, feedback, and regenerate loop to Langfuse so the improvement path can be traced by attempt, not just by final output.
Using Cloudflare AI Gateway patchLog to Grow LLM Evaluation Logs
A small experiment on adding feedback, score, and metadata back to Cloudflare AI Gateway logs so LLM request logs can become the start of an evaluation loop.
Rubrics and Evals Are Not Correct from Day One. Grow Them with Failure Logs
A small verification of how coarse evaluation criteria can pass weak LLM output. This article shows how to treat rubrics and evals as operational assets that improve through failure logs.
Can Langfuse Assistant Serve as an Entry Point for Operations Investigation?
Testing the Langfuse Assistant public beta against existing Sakana Fugu observations and ground truth calculated through the Public API.
Making Your Blog Readable by AI Agents: AIO with llms.txt and MCP Server
Making a personal blog discoverable by AI agents as Perplexity and ChatGPT replace traditional search. Implementation of AIO (AI Optimization) with llms.txt, JSON API, and MCP Server design—decision criteria for a 46-post blog.
When You Build a Minimal API Loop, You Stop Designing Prompts and Start Designing Stop Conditions
I implemented a minimal generate-evaluate-feedback-regenerate loop in a verification script. This post organizes the stop conditions and evaluation units that actually matter when stabilizing AI output.
Observing the Sakana Fugu API with Langfuse: Understanding Hidden Costs in Multi-Agent Systems
A hands-on report instrumenting Sakana Fugu's OpenAI-compatible API with Langfuse, measuring how latency, token consumption, and TTFT change across Level 1–3 tasks.
Observing the Black Box of a Multi-Agent API with Sakana Fugu and Langfuse
I subscribed to Sakana Fugu to understand its nature as an OpenAI-compatible API and to plan how to observe its black-box cooperative reasoning from the outside.
Streaming Flue Observe Events to Langfuse: Monitoring an Issue Triage Agent
An experiment log where I redact Flue 1.0 Beta observe events before sending them to Langfuse, tracking the issue triage workflow's runId, model, and results.
Reassessing My Morning Briefing Worker Now That Langfuse Monitors Has Arrived
I compare Langfuse Monitors with my custom Slack morning briefing worker to figure out which responsibilities should move to the official feature and which should stay custom.