Add v5.0 announcement documentation drafts

Documentation:
- v5-reddit-post.md: v5.0-specific post focusing on hybrid search breakthrough
- v5-reddit-FINAL-DRAFT.md: General claude-mem post with timeline examples
- v5-reddit-post-story.md: Architecture evolution narrative
- v5-reddit-post-draft.md: Early draft with search examples
- v5-linkedin-post.md: Professional LinkedIn announcement
- reddit-posts.md: Research and reference materials

These are working drafts for community announcements.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

context/v5-reddit-post-story.md

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+# Your Claude forgets everything after /clear. Mine doesn't.
+
+You know the cycle.
+
+/init to learn your codebase. Takes a few minutes. Claude reads everything, understands your architecture, builds context.
+
+You work for a while. Context window fills up. You try /compact to compress the conversation—but you can't recall specific moments later, and the compressed format is more verbose than useful.
+
+Eventually you hit /clear.
+
+Everything's gone.
+
+Next session: Claude reads CLAUDE.md again. Does the research again. Re-learns your codebase again.
+
+Tokens cost money. 
+
+Research takes time. 
+
+Low context windows cause quality issues. 
+
+Claude forgets.
+
+This cycle is killing productivity.
+
+## Designing instant memory recall that survives /clear
+
+I spent months building persistent memory for Claude Code. Not summaries. Not compressed conversations. Actual persistent memory—capture everything Claude does, process it with AI, make it instantly recallable across sessions.
+
+/clear doesn't delete anything. The memory persists.
+
+Early on I tried all kinds of vector stores, MCPs, memory tools. I was using ChromaDB for vector search.
+
+The documents were big massive things. Great performance in a RAG sense—semantic matching worked. But it would use up context too quickly.
+
+Either I was doing it wrong, or vector databases are just limited in what they can do.
+
+That's how I ended up with the hybrid approach.
+
+## Watching memories get saved live
+
+The entire idea behind "temporal context" came to me as I watched memories being captured in real-time.
+
+I could see that most memories were duplicate knowledge. Your codebase architecture doesn't fundamentally change every session.
+
+But many memories were **changes**. Bugfixes. Refactors. Decisions.
+
+And here's the thing: if you don't have the date and time associated with it, if you don't know it's the "newest" change, then your information is stale.
+
+And if your information is stale, Claude has to go researching.
+
+Researching is the token-heavy work I'm trying to minimize.
+
+## Building v4.0 with timelines in mind
+
+When I was designing claude-mem 4.0 to be a plugin architecture compatible with Claude Code 2.0, I decided to focus on the SQLite database and observation formatting first.
+
+The semantic chunking was architected by design so it could be brought into ChromaDB later for the best possible results.
+
+But then using the super-fast SQLite index to sort results by date, so you could search for "change" or "bugfix" and see a timeline.
+
+Newest first. So you know what's current.
+
+## Bringing ChromaDB back
+
+Then I brought ChromaDB back to compare with FTS5 searching.
+
+Chroma returned very relevant results with vector relations. FTS5 just doesn't work as well for semantic matching.
+
+And it was fast. Really fast.
+
+That's when the custom timeline feature clicked.
+
+## The "instant replay" idea
+
+My thought was: what if you ask Claude to work on a task from 3 days ago, 4 weeks ago?
+
+Now you have an "instant replay" of everything that was done around whatever you're searching for.
+
+Natural language search finds the anchor point. Timeline reconstructs the context around that moment. Claude's head is in the game, immediately.
+
+## The paradox
+
+Here's what actually happened.
+
+Claude-mem's startup context got so good that Claude rarely even uses the search tools anymore.
+
+The last 50 observations at session start is usually enough for whatever I'm working on. /clear doesn't reset anything—next session starts exactly where you left off.
+
+But I just built out contextualization-on-demand for v5.0. When you need to recall something specific from weeks ago, the "context timeline" instantly gets Claude's head in the game for that exact task.
+
+No /init. No research phase. No re-learning.
+
+Just: start session, Claude knows your codebase, you work.
+
+Development becomes pleasant instead of repetitive. Token-efficient instead of wasteful. Focused instead of constantly re-explaining.
+
+---
+
+**Repo**: https://github.com/thedotmack/claude-mem
+
+v5.0 just shipped. Python optional but recommended for semantic search. Falls back to keyword search if you don't have it.
+
+Does the "how to work on this task" problem resonate with anyone else?