潮记 Review: Can AI Note-Taking Finally Fix Messy Meeting Notes?

Why I Started Testing 潮记 for AI Note-Taking

I spend a lot of time in meetings and research calls, and most of my notes end up as messy bullet points that I never revisit. When I came across 潮记 (also labeled as tidenote or Beanly in different places), the pitch was straightforward: let AI capture the content and turn it into structured summaries. I wanted to see if it actually saved time or just added another app to manage.

Over about two weeks, I used 潮记 during regular work calls, a couple of online lectures, and one longer research interview. Here's what stood out.

What Worked Better Than Expected

The summary output was genuinely useful for meetings. After a 45-minute call, 潮记 produced a condensed version that pulled out the key decisions and action items without much filler. I didn't have to re-read my raw notes to figure out what mattered. That alone saved me maybe 10–15 minutes per meeting, which adds up over a week.

The capture speed felt fast enough for real-time use. During a live lecture, I could let the app run and focus on listening rather than typing. When I checked the notes afterward, the structure was reasonably clean — topics grouped under headings, not just a wall of text. It wasn't perfect, but it was better than what I'd have written manually while half-distracted.

Organization was decent for short sessions. Notes from individual calls or classes were easy to find and scan. The app seems to assume each session is a distinct unit, which matches how most people actually take notes — one meeting, one class, one interview at a time.

Where It Got Messy

Longer content didn't summarize as cleanly. During a 90-minute research interview with a lot of back-and-forth, the summary missed some nuance. It captured the main points but flattened the disagreements and conditional statements into something more definitive than what was actually said. I had to go back to the raw transcript to correct two claims that the summary oversimplified.

The naming is also confusing. 潮记, tidenote, and Beanly all appear in different contexts — the app store listing, the website, the onboarding screens. I wasn't always sure which name referred to the same product or whether there were feature differences between them. It's a small thing, but it made it harder to find documentation or community discussions when I ran into questions.

Editing the AI output inside the app felt limited. I could tweak wording, but reorganizing sections or merging points from different notes wasn't straightforward. For anything beyond light edits, I ended up copying text into a separate document anyway.

Realistic Scenarios Where It Helps (And Where It Doesn't)

• Weekly team meetings: Good fit. 潮记 handles routine, structured conversations well. The summaries are accurate enough for tracking decisions and next steps.
• Lectures or presentations: Works reasonably well if the speaker is clear and organized. Heavy jargon or fast-paced sections sometimes get muddled in the output.
• Research interviews: Partially useful. You get a decent starting summary, but expect to manually review anything that involves nuance, disagreement, or conditional reasoning.
• Brainstorming or open-ended discussions: Less reliable. The app tends to impose structure where there isn't much, which can make messy creative sessions look more decided than they actually were.

Tradeoffs and Fit

潮记 trades manual control for speed. If you value having notes exactly the way you'd write them, the AI-generated structure will sometimes feel off. But if your priority is not missing key points while staying engaged in the conversation, it does that job well enough.

The app also assumes you're working in relatively standard Chinese-language or bilingual contexts. I tested it mostly in Mandarin meetings, and it handled those fine. A mixed English-Mandarin call produced some awkward phrasing in the summary — not unusable, but not smooth either. I'd be cautious about relying on it for heavily multilingual settings without checking the output carefully.

Compared to just recording and transcribing manually, 潮记 saves time on the summarization step. Compared to more established tools like Otter or Notion AI, it's less polished in editing and integrations but feels lighter and faster to start using. If you don't need deep workflow connections and just want summaries quickly, that simplicity might actually be an advantage.

Final Take

潮记 does the core thing it promises — turning long spoken content into shorter, organized notes — reasonably well for routine meetings and lectures. It's not a replacement for careful manual notes when accuracy matters a lot, and the editing experience needs improvement. But for day-to-day calls where you just want to remember what happened without re-reading everything, it's a practical tool that saves real time. I'm still using it for weekly meetings, though I've stopped relying on it for anything I need to quote precisely.