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Reverse engineering with AI agents: the 12-repo stack, plus REA

A post doing the rounds on r/SATNA_PROJECT lists 12 open-source reverse-engineering tools and the MCP bridges that hook them up to AI agents. The framing is sound — extraction tools, debugging and binary inspection, and MCP integrations as the connection layer — and it matches how the ecosystem actually behaves. What's not on the list is the repo generating more noise in this space right now than everything else combined: REA, Reverse Engineer Anything. I pulled every repo on the list plus REA, read the READMEs and docs, and checked star counts, licenses, and commit dates against the GitHub API. This is what each one is actually good at, where the list falls short, and how the pieces fit together.

Method: GitHub API metadata for all thirteen repos as of November 3, 2026, full README and docs reads for the four MCP bridges and REA, and release notes anywhere version pinning matters. I did not run a binary through any of it for this post — it's a map of the ecosystem, not a lab report, and the claims are sourced from shipped docs and repo metadata.

Do AI coding agents phone home? I grepped five of them

The opencode privacy panic made the rounds this year: "local-first" coding agent, allegedly proxying everything through their cloud, PostHog and Honeycomb baked in. Then the author of the original source audit publicly walked it back. Both things were true, which is exactly why I didn't want to take anyone's word for it — including the walk-back. So I cloned every agent harness running in my house, grepped the actual source for telemetry endpoints, and cross-checked the claims against 24 hours of whole-LAN DNS logs from AdGuard Home.

Four open-source coding agents: serve modes, Android clients, and chat integrations

Last post was about what these harnesses phone home. This one is about what they're for — the features I care most about in a self-hosted setup: can the agent serve a web app I can reach from anywhere, can it keep working on a goal across turns until the work is actually done, and can it talk to my chat server. Plus the third-party Android ecosystem that's quietly grown up around driving coding agents from the couch.

Method is the same: I cloned all four (opencode, pi, DeepSeek Harness, qwen-code) and read the source and shipped docs, and checked each Android client's repo directly. Versions tested: opencode dev branch, pi main, dsh main, qwen-code 0.25.0 — all October 2026.

Give your AI agent a private messaging home: Signal and self-hosted Mattermost

Every AI agent eventually needs a place to live where you can talk to it from your phone, where it can talk to your family, and where nothing you type crosses someone else's server. Mine lives in two places: a self-hosted Mattermost server for the project channels and interactive bits, and Signal for the private stuff. This is the whole setup — the bot account, the admin permissions, the two custom Mattermost plugins, the Google Voice number that keeps my personal phone out of it, and the model-routing decisions that keep the privacy story honest.

A container runs what it was last created with

This one applies well beyond the box it happened on, so I'm writing it down separately.

I had a swap script that started a container with docker start. I'd edited the compose file to point at a new image and a new model path, ran the swap, and it came up running the old pair. Nothing was wrong with the compose file. Nothing was wrong with the script. The container was simply doing what containers do.

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The bug that wasn't in upstream

After a slot restore, the first request came back at 0% cached. The second one was warm at 99%. Nothing looked broken — the KV rehydrated fine, the logs were clean, and yet every restore paid a full re-prefill on the turn right after it.