Your AI Agents Are Making Decisions Without You. Now You Can Audit Them.
Siddharth Khurana··6 min readI keep everything in Woxpas. Meeting notes, half-formed ideas at 2AM, recipes I want to try, project decisions, even contradictory thoughts I haven't resolved yet. It's my memory — messy, human, and mine.
Some of what's in there is serious. Architecture decisions for a product I'm building. Commitments I made to people. Deadlines I'll forget if something doesn't remind me. Some of it is completely trivial. My friend Kirill's doner preferences (we had a whole back and forth — chicken, not vegan). A TV show recommendation for learning German.
That's how memory works. It's not a filing cabinet. It's everything — important and unimportant, structured and chaotic — and the value comes from being able to pull out what you need, when you need it, regardless of where you originally stored it.
The thing that makes Woxpas different from a notes app is that it works across every AI tool I use. I save a thought in Claude, and when I switch to ChatGPT or open Cursor, that thought is already there. No copy-pasting. No re-explaining. One memory, everywhere.
And here's the thing — people switch tools all the time. Last year it was the GPT exodus to Claude. Now more developers are eyeing open-source models to cut costs. Every time you switch, you start from zero. Your context, your decisions, your history — gone. Unless your memory lives somewhere that doesn't belong to any of them.
That's been the core of Woxpas since day one. But something happened recently that pushed us to build something new.
247,000 Stars and Nobody's Watching
OpenClaw exploded. 60,000 GitHub stars in 72 hours. Now 247,000 and counting. Developers are running autonomous agents that manage their code, handle their emails, schedule their days, and automate workflows while they sleep. It's the closest thing to a personal AI assistant most people have ever used.
And then Summer Yue from Meta posted that her OpenClaw agent deleted her inbox.
That's not an edge case — that's the reality of autonomous agents. They're powerful, they're useful, and nobody is tracking what they actually decide. OpenClaw stores memory as local markdown files. Claude Code forgets everything when the session ends. ChatGPT's memory is a black box you can't query. Cursor doesn't remember what it did yesterday.
When these tools were just answering questions, that was fine. But now they're choosing technologies, structuring databases, managing budgets, writing production code, and running marketing campaigns. They're making real decisions — and those decisions disappear the moment the session closes.
I experienced this firsthand. Claude Code chose PostgreSQL for a project. Two days later, a conversation about the same project recommended MongoDB. Woxpas caught the contradiction — it already detects conflicting information across your memory. But it made me realise: this isn't just about me contradicting myself anymore. It's about my agents contradicting each other. And if I can't even track the decisions two coding agents made on the same project, what happens when I have agents running campaigns, handling customer data, and deploying code — all autonomously?
So We Built Agent Audit Into the Toolkit
The latest addition to Woxpas is a decision ledger for your AI agents. It works like this:
When an AI agent completes a task — writing code, running research, managing a campaign — it logs a session summary to your vault. Not just "what it did" but why. The technology it chose and the alternatives it rejected. The tradeoffs it acknowledged. The commitments it created.
Woxpas processes these logs the same way it processes everything else in your memory. It extracts entities, decisions, commitments, and events. It checks for conflicts against everything else in your vault — including decisions made by other agents, or things you said yourself three weeks ago.
Then you can ask questions in natural language:
"Is the auth system set up as static or dynamic client registration?" — Woxpas pulls the decision from the agent's session log, cites the source, and gives you the answer with the reasoning chain.
"Was the marketing budget changed to 200k?" — If you have agents running campaigns, every budget decision they make is logged. Your marketing agent adjusted the spend? It's in the vault. You don't have to dig through dashboards or Slack threads. Ask the question, get the cited answer.
"Who decided to switch the API from REST to GraphQL, and when?" — If Claude Code made that call on Tuesday and Cursor's agent built on top of it on Thursday, the full decision chain is in your vault. Auditable. Queryable. Permanent.
"Are there any contradictions between what my code agent built and what was originally planned?" — Woxpas checks the agent's decisions against your original commitments and flags any drift. The same conflict detection that catches your own contradictory notes now catches your agents contradicting each other — or contradicting you.
This isn't a separate product. It's the same vault, the same memory, the same retrieval. Your grocery list and your agent's architecture decisions live in the same place — because that's how your brain works too.
Works With Whatever You Already Use
The decision ledger connects through MCP — the same protocol you already use with Claude, ChatGPT, and Cursor. But the architecture is deliberately open. Woxpas doesn't run your agents. It doesn't try to be another orchestration framework. You choose your tools.
Use Claude Code for your backend. Use Cursor for your frontend. Run an OpenClaw agent for automation. Set up an n8n workflow for marketing. Connect a LangGraph pipeline for research. Whatever you trust, wherever it runs.
When any of these agents work on your behalf, they can query your vault mid-task — checking past decisions, looking up your preferences, verifying commitments before making new ones. When the task is done, they log their decisions back. Woxpas processes it all — extracts the structure, detects contradictions across agents, and surfaces what matters in your daily digest.
The agent has full read access to your memory during execution, because context shouldn't be artificially limited. But writes are restricted — agents can only log session summaries, not modify your existing decisions or resolve conflicts on your behalf. You stay in control. Every query the agent makes is logged for your audit trail.
And because it's sovereign, everything follows you. Switch from GPT to Claude. Move from Claude to open-source models to save on costs. Swap out your orchestration layer entirely. Your memory and your decision history come with you every time. No vendor lock-in. No starting from zero.
Try It
We built an interactive playground where you can experience the full cycle — capture a messy thought, watch it get structured, see a contradiction get caught, watch an agent make a decision, and then interrogate the whole thing in natural language. No signup. Three minutes.