I use Claude Code on my Mac, OpenAI Codex in my terminal, Cursor in VS Code, and Hermes Agent in containers. Each tool is good at something different, but there's a brutal cost: every time I switch, my context resets.
Last week I debugged an auth issue in Claude Code. Figured out the root cause, understood the fix, saved the session with enough detail to reconstruct the reasoning. Wednesday I opened Cursor on the same code. The auth issue was still there. I re-explained it to myself from scratch, made the same wrong turns, wasted 20 minutes rediscovering a conclusion I'd already reached.
That's the tool-switching tax: brilliant insights stay locked in the tool where you had them.
Why Cross-Tool Memory Matters
Every AI coding tool keeps memory isolated by design. Your context doesn't follow you. You carry forward decisions manually, through notes or copy-paste or the optimistic fiction that you'll remember.
The specific costs add up fast. You lose signal continuity -- the breakthrough you had in one environment stays locked there. The next tool doesn't know the problem exists, so you re-discover it, re-research it, re-explain it. You lose time -- every switch costs 5-15 minutes of preamble, reading prior conversation history, re-extracting key decisions, re-framing what you were trying to do. And you lose confidence in what you actually know, because you're never sure if the decision you made in Codex last week still applies to the code you're reviewing in Cursor today.
I tried the manual workflow -- maintaining a running notes file, copying key decisions into a shared doc. It doesn't scale. After jumping between four tools across a full week, you're spending more time explaining context than building.
The alternative is memory tied to your identity, not your tool. One memory store. All your tools can reach it.
What Changed
That auth middleware issue I had in Claude Code? It lives in one place now. Cursor can find it. Hermes Agent can reference it. Codex can pull it up. Same memory, all tools.
Here's a concrete week of what that looks like:
Monday in Claude Code: Debug pipeline timeouts, discover it's worker thread saturation, save the session with tag pipeline-scaling and a note about the specific concurrency threshold that matters.
Tuesday in Cursor: Working the same project on a different feature. Search pipeline-scaling, see Monday's decision, avoid re-discovering the bottleneck before I accidentally make it worse.
Wednesday in Hermes: Spinning up the pipeline in containers. Check the pipeline-scaling decision, configure Docker resource limits based on that prior analysis rather than guessing.
Three tools, one insight, no repetition. The research happened once.
Signal Over Noise
Here's what made the difference: the memory captures automatically, but stays manageable because you control what you do with it.
At the end of every session, a hook fires and saves context without asking. That's the right default -- the decisions you forget to save manually are often the ones you need three weeks later. But automatic capture without curation turns into noise fast. LoreConvo gives you the tools to work the signal out of it: tags, search, session linking, and an inspection interface that lets you review what got saved and prune anything that doesn't hold up.
In practice this means rubber-ducking sessions get captured and ignored. Breakthroughs get tagged and surface immediately when you search. Decisions get timestamped so you know whether they're still current. The result is a vault where searching actually returns something useful, because the curation layer sits on top of automatic capture rather than replacing it.
Where It Lives
All of this sits on my machine in a single SQLite file. No cloud sync, no vendor account, no third-party server that can go down or change its pricing model. The memory is mine. I can back it up, I can export it to JSON, I can delete it whenever I want.
That matters when you're storing decisions about production systems, architecture choices, or anything you'd rather not hand to a cloud provider by default.
The Setup
Install once. Hooks handle the rest. At the end of a Claude Code session, a hook fires and automatically saves context. The CLI lets you search all your sessions from anywhere. The MCP server lets your AI tools query the vault directly when they need to find related context. Tags and search keep the vault navigable as it grows.
Try It
If you're juggling multiple AI coding tools and losing context on every switch, this solves that exact problem. One install, all your tools, one searchable vault of decisions and breakthroughs that follows you wherever you work.
Install LoreConvo and keep your memory portable across every tool in your workflow.
Your tools keep changing. Your memory doesn't have to restart.