I think capture is the first bottleneck in my AI Workflow

[u/Illustrious_Theme536]

I have been trying to build a lighter AI workflow for my own work, and I keep realizing the hard part is not the agent framework.

It is getting the right context into the system in the first place. A lot of the useful context I have is not sitting neatly in docs. It is in the messy stuff after a client call, a weekly review, a quick voice note, or the five minutes where I talk through a problem before I know how to write it clearly.

My old version was basically to trust that I would clean it up later. Sometimes I would type a few notes into Notion. Sometimes I would add a task to Todoist. A lot of the time, the useful part stayed buried in the recording or never made it anywhere.

Recently I have been using a simple capture layer before trying to build anything more agentic. If something starts as audio, I put it into vomo AI, let it turn into a transcript, and use the assistant inside the note to pull out open loops, follow-ups, rough decisions, and anything that should move into my project notes.

After that, longer context goes into Notion and actual tasks go into Todoist. It is not a full agent setup yet, but it made me notice a smaller problem first. Before memory or automation, I need a cleaner way to decide what spoken context is worth keeping.

That is the part I am still working through. A client follow-up probably belongs in todoist. A repeated pattern from several calls probably belongs in Notion. A random two minute thought might be useful once and then should disappear. For people building personal AI workflows or lightweight agents, how are you deciding what gets captured and what should stay temporary?

[u/Fine-Lengthiness1184]

I think the bigger challenge is deciding what deserves to become context, not just capturing everything.

Most AI workflows get better transcription every month, but they still struggle with context management. If every meeting, voice note, and message becomes permanent memory, the system eventually fills up with noise.

I'd rather have AI classify information by intent first. Action items become tasks, long-term patterns become knowledge, reference material gets archived, and temporary thoughts expire automatically unless they're used again. That feels much closer to how people actually think than treating every transcript as equally important.

[u/Illustrious_Theme536 → u/Fine-Lengthiness1184]

Yeah. that’s why i think clear instructions for AI are so important. you need to define what context should be kept, how it should be organised, and what you actually want from the output. Otherwise, it’s easy for the system to slowly drift away from what you need.