Every meeting tool now offers to “summarize this call for you.” I’ve tried a few of them. And every time, I get back the same thing: a tidy, generic recap that reads like it was written by someone who wandered into the room halfway through and had no idea who anyone was or why the conversation mattered.
That’s the part nobody talks about. A summary isn’t the same as understanding. The built-in AI on your calls can tell you what was said. It can’t tell you that the thing the other person mentioned in passing is actually the third time they’ve raised it, or that it connects to a deadline two weeks out, or that it’s the exact follow-up you promised someone else last month. It has no memory of your world. So you still end up doing the real work: re-reading the transcript, pulling out the action items, deciding where each one belongs.
Earlier this summer I started building something to fix that for myself, and the difference in the output has genuinely surprised me.
The problem isn’t transcription, it’s context
The raw capability of turning speech into text is basically solved. You can get a clean transcript of almost any call or meeting now. That’s the easy 80%. The hard 20%, the part that actually saves you time, is everything that happens after the transcript exists.
What I wanted was an assistant that already knows my projects, the people I work with, and the open threads I’m tracking, and reads each conversation through that lens. Not “here are five bullet points,” but “here’s what mattered, here’s how it connects to what you’re already working on, and here’s the thing you said you’d do that you’ll absolutely forget by tomorrow.”
The mental model I kept coming back to: I don’t want a stenographer. I want a sharp assistant who was in the room, knows the backstory, and hands me a note afterward that’s already half-actionable.
What it actually does differently
The system takes a call transcript and, instead of producing a standalone summary, processes it against everything else it knows about what I’m working on. The notes that come out are connected to the relevant project. Action items get pulled out and filed where they’ll actually resurface. A passing comment that ties back to an earlier conversation gets flagged as exactly that. And for some calls it no longer needs a recording handed to it: it can join a video call directly (Google Meet, so far) and capture the audio itself.
The outcome is the part I care about. I’m not opening a transcript and a to-do list and a project folder and manually stitching them together anymore. The note arrives already knowing where it belongs. That’s the whole game: closing the gap between “a thing was discussed” and “the right next step is captured and won’t get dropped.”
There’s a nice side benefit I didn’t expect: it’s intentionally opt-in, call by call. It’s not silently vacuuming up every conversation in the background. When I want notes on a specific call, I turn it on for that one. That constraint actually made the tool feel more trustworthy to me, not less: it’s a deliberate “sit in on this one,” not ambient surveillance of my whole life.
Why this keeps coming up in my work
I build automation systems, and the most common request I hear, in one form or another, is some version of “help me stop dropping things.” People don’t actually want more dashboards or more notifications. They want the small, reliable stuff handled (the follow-up that got promised, the detail that mattered, the thread that went quiet) so their attention is free for the work only they can do.
A notetaker that understands context instead of just transcribing is a small example of a much bigger idea: software that knows enough about your situation to be genuinely useful, rather than generically capable. That’s the line I keep chasing. Generic is cheap and everywhere now. Useful is still rare.
I’m still refining this one, starting to test it against real calls and tuning where things get filed. But even early, it’s already changed how I feel walking out of a conversation. The mental “okay, don’t forget to write that down” tax is mostly gone.
Want something like this?
If you’ve got a workflow where things slip through the cracks (notes, follow-ups, handoffs, the stuff that lives in your head until it doesn’t) that’s exactly the kind of problem I like to solve. I build context-aware AI assistants and automation around the way you actually work, not the way a generic tool assumes you do. Take a look at what I do at /ai-assistant, or just get in touch and tell me what keeps falling through.