Oxynote

For a long time, the most reliable documentation at my company was the Slack chat I had with myself. How it got that way starts with dashboards. We had a lot of them: Grafana, Sentry, for some reason a bit of Datadog, and a few custom self-hosted HTML pages with charts on them. On top of that, I was encouraged to run my own health checks for the deployments I owned (why that could not live in Grafana or anything like it, nobody could tell me). Those deployments were services pulling financial market data over websockets. Under heavy volume they leaked memory and got OOM killed. There was a bug in there somewhere that we were chasing and could not find for a while, and in the meantime every kill meant missed events, and missed events meant running backfill scripts by hand. None of our dashboards showed any of that. So: cron, curl against each service's status endpoint, and the result posted to me privately on Slack. Not convenient at all.

Then there was everything else. Internal wikis still describing deployment procedures for trial products that had ended. Secret vaults. Server management commands and curl requests. None of it lived in one place, and access was its own problem: each of these had a different owner who could grant it, so a lot of my time went into finding out who that was and then finding them. Since we talked on Slack, that is where I asked for all of it, and that is where people answered, sometimes with plain credentials (the horror). To not lose any of it, I forwarded those messages to the chat with myself, which is how that chat became my source of truth for a long time: links to the specific Grafana dashboards that mattered out of the many we had, example curl requests against other teams' services so I could match their responses when integrating (neither the requests nor the responses were documented anywhere), and server IPs with notes on what was deployed where.

Naturally, I did try to fix it. I wrote Notion docs and linked the Grafana charts from them, and for a while that was fine. Then they drifted apart. One doc explained the labels on our ingestion-rate chart, market, region and so on, but new labels kept being added, nobody documented them, half were not even used in the chart, and each one cost Prometheus another time series. Keeping a doc and a chart in sync meant links on both sides, in Notion and in Grafana, which was more work than I wanted, plus switching browser tabs just to check that the explanation and the chart still meant the same thing. And that was only observability. Beyond it, admin actions were specific curl requests, and feature flags lived in a service disconnected from everything else. All of it deserved a proper review flow, like on GitHub, with diffs that work for text, metric charts and other visual structures. Instead it had none.

David (@davseby), who started Oxynote with me (@swithek), was the one who had to work through a system and its documents the first time he was on call, at a different company. He had years of Grafana and internal docs behind him and expected it to be routine. What he got was Datadog, which he had never used, and a wildly different Notion structure. Then, on that first shift, the services that enrich image metadata failed. Search over user uploads turned inaccurate, and from there it cascaded through the product. Monitors fired, but none of them linked anywhere or said which service had started failing, which made for a nerve-racking night of tying things together by hand. The metric showing one service overloaded and unresponsive existed the whole time. Datadog's UI is convoluted, though, and nothing explained what any chart tracked, so David never found it. An AI agent connected to Datadog's MCP server did.

What both of us wanted was the graph, the explanation, the command and the flag on one page, edited together, reviewed like code, and readable by a tired person at night or by an agent. Every tool we had was built to be great at one of those things and to never look sideways at the others. That gap is what Oxynote is for. It starts with the pieces we needed most: live Notion-like docs, metric charts, review flows, and Stripe-like split docs for real-time systems. The other pieces of the puzzle are coming.