This is the third of our real-matches case studies (the others cover a personal finance platform and a task manager). The product this time is a personal knowledge management tool with an AI memory layer — it captures your notes and articles and gives your AI assistants persistent memory of them. Real product, live discovery run; as always, the matches below are actual Reddit posts and comments, lightly trimmed, with no usernames and no links.
Two things make this run worth writing up: the best lead wasn't a post at all, and the best hunting ground wasn't the product's own category.
The setup
From the product's URL, ThreadSnoop drafted the profile and proposed 9 subreddits and 20 search terms— notably not just the PKM communities you'd guess (r/ObsidianMD and friends) but also the AI-assistant subreddits where people complain about their tools' memory. Since then: 1,332 matches, 73% via semantic search, and — this matters for what's below — 248 of them found in comments, not posts.
The lead that makes the case for comment monitoring
The single best match of the run, scored 8/10, was a comment — buried in a thread whose title mentions nothing the product does:
In a thread titled: “I just resubscribed… had to cancel Claude!”
Yeah Claude gaslighted me too last night, kept insisting it never had access to previous memories or notes or anything. I pushed back hard but Claude refused to acknowledge and kept saying it didn't have that ability, when I know it did. It was either lying, or there was an update that wiped its memory of its own memor—
Knowledge worker frustrated by broken AI memory; explicitly wishes for persistent cross-tool AI memory — exactly what this product solves, though no active search yet.
No post-only monitor sees this person. The thread is about subscription churn between chatbots; the pain — an AI that forgets your notes — lives three replies deep. ThreadSnoop sweeps comments as well as posts for exactly this reason, and in this run nearly one in five matches came from them.
The rest of the top of the queue
Looking for the best AI + Obsidian setup to build a long-term personal thinking partner
My goal is not just to chat with an AI or search through my notes. I want to build something closer to a persistent thinking partner that grows alongside me — I'd love to hear from people who have actually built something similar.
Knowledge worker actively seeking a persistent AI thinking partner integrated with their vault — strong ICP fit, currently exploring options.
What structure for an academic's PKM?
I started out by organizing things in simpler ways (back in the days of Evernote), then moved to Obsidian, and finally to an outliner tool, which I have used since the early beta versions. I am an academic working in the humanities… frustrated by ecosystem lock-in, looking for something Markdown-based that works with LLMs.
Academic actively considering switching tools, frustrated by lock-in and seeking Markdown-based PKM that works with LLMs — strong ICP fit and switching intent.
I don't mind introducing someone new to AI. I mind having to introduce Bob twice.
There have been many posts about ChatGPT forgetting context, but the specific pain point I'm experiencing feels slightly different. Imagine I tell my AI about Bob. Bob isn't famous — or maybe he is, but I know things about him that aren't on the internet. Next session, I'm introducing Bob again…
Knowledge worker experiencing real AI memory pain and asking how others handle it — high fit and severity, no buying signals yet.
What this run teaches
- Your best leads may live in someone else's community. The product is “a PKM tool,” but the highest-severity pain shows up in r/ChatGPT and r/ClaudeAI — people furious at their assistant's broken memory. Those threads never say “personal knowledge management”; they say “it forgot everything again.” Onboarding suggested those communities because it maps the problems, not the category.
- Comments are a fifth of the pipeline.248 of 1,332 matches were comment-level. The 8/10 above is the proof case: the thread topic and the buyer's pain can be completely different things.
- The reasoning stays honest about intent. Three of the four cards say some version of “not actively shopping.” That's the right brief for this market: show up, be genuinely useful about the memory problem, disclose what you built. Severity opens the door; a pitch-first reply would close it.
Run it on your product
If your customers' pain shows up in other tools' communities — and for most products it does — a category keyword list will never find them. Paste your URL and see where ThreadSnoop suggests looking; the first sweep shows you real threads before you've paid anything.
Frequently asked questions
Are these real Reddit posts and comments?
Yes — every match shown was found by ThreadSnoop's live discovery pipeline for a real customer product, with the pipeline's actual stored scores and reasoning. Quotes are lightly trimmed; usernames and links are deliberately omitted, and the product is described but not named.
Why does monitoring comments matter so much?
Because thread titles and buyer pain are often different things. In this run, 248 of 1,332 matches — including the single best lead — were comments, where someone describes their exact problem inside a discussion about something else. Post-only monitors structurally never see them.
How did ThreadSnoop know to watch AI-assistant subreddits for a PKM tool?
Onboarding maps the problems a product solves, not its category. For an AI-memory tool, the sharpest problem-talk ("my assistant forgot everything again") happens in the communities of the AI tools themselves — so those subreddits were suggested alongside the obvious PKM ones.
Find the leads hiding in other tools' communities
Join the waitlist, and once you're in, see where ThreadSnoop suggests looking — including the adjacent communities where your customers are already complaining.
Free during pre-launch — just your email to join, a product URL is optional.