Built to solve a problem
I hit every day.
3ngram exists because I got tired of watching AI tools forget what they promised to do next.
Sebastian Gade
I build software for a living. I use Claude Code, ChatGPT, and Cursor daily, often in parallel across ten worktrees. The models are brilliant at reasoning. They remember facts and preferences across sessions. But the commitment I made at 9 a.m. to ship a feature by Friday? Gone by lunch. No tool tracked it. No tool surfaced it when I got pulled into something else.
That gap, between remembering and following through, is what 3ngram was built to close. I wanted a single memory layer that works across every AI tool I use, gives memories structure (commitments carry deadlines, blockers track resolution, decisions accumulate rationale), and holds me accountable when things slip.
3ngram is a one-person company based in Copenhagen, Denmark. I build it, I use it, and I ship updates based on what actually makes the workflow better.
Make AI follow through.
Every AI tool on the market can remember. Native memory in Claude, ChatGPT, and Gemini stores facts and preferences. Third-party memory layers add retrieval and embeddings. None of them track whether you actually did the thing you said you would do.
3ngram adds the missing layer: structured memory with accountability. Commitments have deadlines. Blockers have resolution states. Decisions carry rationale. When something slips, you get nudged. When you switch tools, your context follows. One protocol (MCP), one memory layer, every AI client.
Memory that follows through.
Connect via MCP. Keep your tools. Add the layer they are missing.