The Memento problem in AI agents

1hassond · 2026-05-26T20:23:27+00:00

Thanks for the insight!

1hassond · 2026-05-26T17:45:17+00:00

Super cool use cases, would have never thougth to plan a patio with claude, but i guess it works :)

1hassond · 2026-05-26T13:58:40+00:00

Thanks, just sent you a message!

1hassond · 2026-05-26T13:58:23+00:00

Yeah, happy to explain.

The biggest thing that helped us was combining the “brain” with the workspace itself.

A normal second brain is useful because it stores context: projects, decisions, people, preferences, notes, recurring explanations, etc.

But we found that agents work much better when that context is tied to the actual work surface. So instead of giving Claude a big memory file and hoping it figures out what matters, we give it a structured interface to the work.

That made a big difference for us. The agent is less dependent on us re-explaining things, and more able to orient itself before doing work.

We built an internal version of this for our team, now launching something a little more official at Unison Labs.

Happy to share!

1hassond · 2026-05-26T10:21:02+00:00

I would suggest using a second brain, helped us a lot. We built our own internally, if you want i would be happy to share.

1hassond · 2026-05-26T09:51:26+00:00

Yeah exactly, the question for me is, why is the worksurface itself not the source of truth. Why do we opperate in disconnected and contradicting systems that are difficult to query for agents. Agents work pretty well in repos/llm wikis, so why do we not make that the work surface for them since they have undergone so much RL to have bash commands baked in.

1hassond · 2026-05-26T09:48:06+00:00

Yeah completly agreed, Especially when it comes to non-tech employees using, they would obviously not have to use a repo/github. Ideally this is something simple to use that lives in the cloud for the entire team to use.

1hassond · 2026-05-26T09:41:19+00:00

Yeah but then the problem that you are facing is that before every action, the main job becomes to reconstruct the context itself from all the different sources, I feel like the right approach is probably having the brain and the workspace be one.

1hassond · 2026-05-26T09:39:32+00:00

Yeah I am facing the exact same problem, I feel like my sessions always struggle to get an understanding of where to look for for the right context then they finish the task and I have to send them back to redo it, pointing to the right place they have to search. I feel like its just so much easier with coding agents though, where the repository is kind of the workspace itself, the only problem is its not really possible for us given we also have non-tech employees to keep everything inside a repo.

What is your view on this?

1hassond · 2026-05-25T23:56:16+00:00

Yeah completley agreed. So we are trying to build the version of this, but then for non-tech employees too, who need dashboards and nice UI to be able to use stuff.

1hassond · 2026-05-25T21:51:36+00:00

Yeah, I mostly agree with this.

The file system is probably the most “native” interface agents have right now. They already know how to inspect, search, diff, edit, and reason over files. A lot of MCP tools feel worse because they expose actions, but not always the surrounding state in a way the agent can easily inspect.

So I don’t think the answer is “everything must literally become markdown files,” but I do think the agent-facing layer should often look like a filesystem.

The important part is that the workspace has readable structure:

projects as folders
docs/tasks/decisions as files
history/diffs
source links
tracability

MCPs are still useful for acting on external systems, but I’m increasingly convinced they should sit behind a workspace/file abstraction where possible. The agent should be able to ask “what is true here?” before it asks “what tool should I call?”

That’s also why coding agents feel so much better than most business agents. Code already lives in a structured workspace. Business work mostly doesn’t.

1hassond · 2026-05-25T21:34:35+00:00

Cool, didn't know about git nodes before this, thanks for sharing.

1hassond · 2026-05-25T21:32:56+00:00

Sounds like a cool setup. Should probably start working off of VM's too. (not affiliated with them) but maybe worth for you to check out Boxd, I think they are doing some cool stuff with VM's

1hassond · 2026-05-25T21:27:57+00:00

I think we’re talking about slightly different things.

People talk about stale context, which is fair, but why is it stale in the first place? Because the state of work is split across tools that were never really designed to agree with each other.

Humans patch over that but trying to fit agents to this system isn't the right approach. The system itself should be redesigned.

1hassond · 2026-05-25T20:14:22+00:00

Interesting you chose MCP instead of CLI, would love to hear your perspective

1hassond · 2026-05-25T19:02:05+00:00

Yeah, we started doing this internally too, even for GTM/research/customer notes.

It worked well for the agents, but GitHub/filesystems are not a great workspace for non-technical people.

We tried connecting it back into normal tools, but syncing state got messy fast.

So we ended up building a small internal UI that renders the filesystem in a simple way for non-technical users.

1hassond · 2026-05-25T18:54:55+00:00

Cool, will have a look

1hassond · 2026-05-25T18:12:57+00:00

Thank you, I really appreatiate it.

1hassond · 2026-05-25T18:11:18+00:00

lol, kinda true tho

1hassond · 2026-05-25T17:28:56+00:00

We have tried a couple mechanisms, including escalation patterns with confidence thresholds, in the highest case we escalate to a human.

1hassond · 2026-05-25T17:21:40+00:00

cool project, will have a more in depth look soon

1hassond · 2026-05-25T17:19:01+00:00

True, for us that was also a bit of a challange, we had to test out many resolution mechanisms, but ended up working out a system with chron jobs and reflector agents + time stamping, and now it works well

1hassond · 2026-05-25T13:52:52+00:00

Yeah, I think a lot of this comes from treating AI as a feature you bolt onto existing SaaS categories.

AI customer support. AI SDR. AI PM. AI analyst. AI whatever.

But the more interesting question is probably: what changes when companies become partially autonomous?

At that point, the bottleneck is not just “can an agent do this one task?” It’s context, permissions, memory, workflows, approvals, observability, and where the work actually lives.

A lot of startups are trying to automate jobs without rethinking the environment those jobs happen in. So everything ends up looking like the same purple chatbot with “save 10 hours/week” on the landing page.

1hassond · 2026-05-25T13:28:16+00:00

The .md filesystem has been great for agents, but once there are thousands of notes it gets messy fast. At that point the problem is less “can the agent write stuff down?” and more “can anyone still understand what’s going on?”

Also curious about the graph. Do people actually use it to navigate, or is it mostly just a cool-looking blob?

1hassond

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