I thought markdown memory would be enough for agents. It turned into prompt debt.

I thought markdown memory would be enough for agents for a while. back in my OpenClaw setup, the agent memory was basically markdown files. readable, editable, easy to back up, no weird vendor lock-in. honestly it felt like the correct boring answer. then it grew to 80+ md files and somewhere past 5 million characters. and technically, yeah, it was all still "there." but every run started to feel like: "please scan this giant pile of notes and somehow guess which parts still matter." that was the part that kept biting me. storage was solved. memory was not. the annoying thing about flat text memory is that it works beautifully for one scale, then quietly turns into prompt debt. project facts, old bugs, decisions, people, preferences, half-dead plans... they all sit there as chunks waiting to be reread like they have equal weight. the thing that finally clicked for me, weirdly enough in the shower lol, was that I didn't want a better notebook. I wanted the agent to render the relevant part of its memory for the current task. so I ended up moving toward graph memory: each memory as a node, relationships stored as edges, and retrieval as "what part of this map should light up right now?" instead of "dump the top 10 similar notes into context." not saying markdown is bad. I still like it as an archive/export format. I just don't think long-term agent memory can stay purely text-shaped once it gets big enough.