Alternatives
Products that do what Aladeen does
Local observability for your AI coding agents
- 1
- 2
Trace, evaluate, and improve AI agents in production
Aug 2026 · telerik.com
- 3AO
Hi! I’m Nathan: an ML Engineer at Mozilla.ai: I built agent-of-empires (aoe): a CLI application to help you manage all of your running Claude Code/Opencode sessions and know when they are waiting for you. - Written in rust and relies on tmux for security and reliability - Monitors state of cli sessions to tell you when an agent is running vs idle vs waiting for your input - Manage sessions by naming them, grouping them, configuring profiles for various settings I'm passionate about getting self-hosted open-weight LLMs to be valid options to compete with proprietary closed models. One…
Jan 2026 · github.com
- 4
AgentGrid▲77Hi HN, I’m Michael, I built AgentGrid with my friend Souren because we were tired of losing our coding sessions and couldn't keep track of what was actually being built across our many projects. Our approach was to use an infinite canvas desktop app for the TUIs we already know and love, mainly claude + codex. We drew inspiration from Figma and Railway. Overtime we added image nodes, notes, terminals, coding editors, source control, etc. I wasn't sure about it at first. It took me a month to give the first version Souren built a real try. What got me was an Apple System Update I've been…
Jul 2026 · agentgrid.sh
- 5
- 6
- 7
Trace LLM requests + costs with OpenTelemetry monitoring
Oct 2025
- 8
- 9
- 10
- 11
- 12
- 13
- 14IA
1. Headless mode Headless mode allows you to use the AI as a command-line utility for automation and scripting. In Claude Code you run it with the -p flag: claude -p, in codex - exec, opencode - run. 2. Ask human The traditional communication channel with the operator won't work in headless mode - we need to implement a dedicated tool. Here is an example of how this can be done https://github.com/sermakarevich/claude/tree/main/mcp/ask_hu... 3. Tasks queue Beads is a lightweight distributed graph issue tracker for AI agents, powered by Dolt. You can…
Jun 2026
- 15
- 16RT
Mar 2026 · github.com
- 17
Hello all, I'm a software developer. Over the last few months more and more of my work has turned into using coding agents instead of typing the whole code myself. Usually a few claude sessions at once, sometimes codex, one per feature or per revealed bug. I ran them in a split terminal for a few weeks, and quickly spotted two main problems. The first is that I couldn't easily tell which agent was stuck waiting on me and which was still working, so I'd cycle through sessions and checking on them. The second one: agents sharing a single branch step on each other. Two of them could be editing…
Jul 2026 · shikigami.dev
- 18
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…
Jul 2026 · oodle.ai
- 19MC
Hi HN, I'm Kaushik, and I built Rocketgraph. I believe that while other spaces have caught up to the AI wave, the observability space is still lagging behind, using the same tools and dashboards that we use to analyse logs from human-written code. But now the code is written and debugged by AI, so we need to rethink how we do observability where the observer itself is an AI. The problem that I run into is when an alert fires, I have to manually check the Grafana dashboards and write LogQL queries, which is pretty much like greping. But production usually breaks due to a schema mismatch, or a…
Jun 2026 · github.com
- 20LE
I started using Claude Code (claude --dangerously-skip-permissions) and Codex (codex --yolo) and realized I had no reliable way to know what they actually did. The agent's own output tells you a story, but it's the agent's story. logira records exec, file, and network events at the OS level via eBPF, scoped per run. Events are saved locally in JSONL and SQLite. It ships with default detection rules for credential access, persistence changes, suspicious exec patterns, and more. Observe-only – it never blocks. https://github.com/melonattacker/logira
Mar 2026 · github.com
- 21
- 22RC
The magic in AI coding assistants isn't the code -- it's the prompts. I studied the externally observable behavior of Claude Code and recreated it from scratch in Python with the exact same behaviors. It works with any model -- OpenAI, Gemini, Claude. What's surprising: 1. You can keep the core agent really simple, just 280 lines of Python. As long as it supports hooks, custom sub-agents and Model Context Protocol (MCP), then all the rest of the coding-assistant-specific behavior and tools can be factored out into a separate MCP server. 2. The magic is in the prompts (1200 lines of…
2025 · github.com
- 23
- 24
Ranked by how close each launch is in meaning, then by votes. Refine with a description →