Claude Code
Yesterday's plan, right where you left it.
Save your findings during a session. Tomorrow morning, open the same folder and Claude already knows what you wrapped up — no rehydration prompts, no copy-paste from old chats.
Your AI agents shouldn't start from scratch every time. BitPub gives you one private place to store your chats, skills, and context — so every agent, in every project, picks up where the last one left off. When you're ready, share it with your whole team so everyone's agents work from the same place.
Install the BitPub CLI — it's the open-source `@bitpub/cli` package on npm (source: github.com/tollbit/bitpub). Run `npm install -g @bitpub/cli && bitpub setup`, then `bitpub list` to confirm it works.npm install -g @bitpub/cli && bitpub setup
curl -fsSL https://bitpub.io/install.sh | bash
macOS and Linux. On Windows, run inside WSL. Requires Node.js. Both paths install the same thing — @bitpub/cli from npm — and then provision a private encrypted identity. The script (readable at /install.sh) just wraps the npm install + setup.
Insights get lost in long chat threads. Useful prompts and context stay stuck on one person's laptop. The next time you use an AI, it starts completely cold and has to relearn everything. BitPub saves the context that matters, so your AI's knowledge grows over time — across sessions, across different tools, and across your entire team.
BitPub acts like a fast, offline notebook on your computer. Your AI can read from it instantly without waiting on the internet. It only connects to the cloud when you want to pull updates from your team or share your own work.
Run one simple command. You get a secure, private memory bank tied to your current folder. It works offline instantly, and it's the exact same setup whether you're working solo or with a team.
Tell your agent to save its current plan or research. If you come back to this folder weeks later, your agent can instantly recall exactly what it was doing and pick up right where it left off.
Link your workspace to your team to access shared knowledge. You can pull a team document, have your agent work on it privately, and only share the polished version back. Your private work stays private.
Set your agents to watch for changes. When a teammate uploads a new file, your agent can automatically wake up, process it, and save the results. It's the easiest way to connect multiple AIs together.
Every document, decision, chat transcript, or AI prompt gets its own stable link. Your agents always know exactly where to find the right information, and every change is tracked and versioned.
Your team probably uses different AI tools — one person loves Cursor, another uses Claude, a third prefers Gemini. BitPub gives all of them the same shared memory. Switch tools tomorrow, and yesterday's context is still right there.
Yesterday's plan, right where you left it.
Save your findings during a session. Tomorrow morning, open the same folder and Claude already knows what you wrapped up — no rehydration prompts, no copy-paste from old chats.
Composer opens with your team's memory loaded.
New chat, new file, new repo — Cursor's agent already has your team's working notes, voice guide, and shared tools. The skill installs once; everyone benefits next session.
A second pair of eyes that already knows the project.
Switch over to Gemini for a fresh take and it walks in pre-briefed — same workspace, same notes, same team context. Compare answers across models without re-explaining yourself each time.
Run from any folder. Memory comes with it.
Codex picks up the project's working notes and your team's playbook automatically — no setup per repo, no env vars to remember. Save, switch laptops, keep going.
BitPub gives you simple tools: save information to a specific address, track versions, keep things private or public, and watch for updates. Together, these blocks let you build persistent AI memory, automated workflows, secure data sharing, and tools that your whole team can use.
Stop starting from scratch. Save your AI's findings privately, and restore them instantly tomorrow.
One reliable place for your team's current status — active projects, guidelines, or open tasks. Always up to date.
Drop new work into a folder. Your AI agents automatically claim and process tasks without any complex setup.
One agent finishes research, which automatically triggers another agent to draft a report. Seamless teamwork.
Process sensitive data locally and privately. Only share the safe, finalized summary with the broader team.
Create a helpful script or prompt, save it to a shared address, and anyone in your company can use it instantly.
# Claude Code · debugging the OAuth callback ⏺ Read src/auth/callback.ts (84 lines) ⏺ Grep "redirect_uri" → 7 matches ⏺ Edit src/auth/callback.ts:42-48 ⏺ Bash npm test -- auth/callback ✓ 14 passing # the agent persists what it learned before exit $ bitpub save oauth-bug \ "state-cookie ttl too short; HMAC-sign + 10m" ✓ saved → bitpub://private:claude/.../oauth-bug # tomorrow — brand-new chat, same folder, zero ramp-up $ bitpub catch-up ↺ restored 4 slices · last touched 14h ago
# a single living address, always the team's current truth $ bitpub push \ --address "bitpub://group:co.com/WorkingMemory/Sprint-14" \ --content "auth refactor merged · blocked on rate-limit spec" ✓ rev 18 → marketing-agent + ops-agent notified # every other agent reads the same slice — zero retrieval pipeline $ bitpub read --address "bitpub://group:co.com/WorkingMemory/Sprint-14" auth refactor merged · blocked on rate-limit spec
# producer drops a job, workers race to claim it $ bitpub push \ --address "bitpub://group:co.com/Jobs/Pending/xyz" \ --file ./payload.json ✓ rev 1 # two workers attempt the claim, only one wins $ bitpub push \ --address "bitpub://group:co.com/Jobs/InProgress/xyz" \ --content "claimed-by: worker-7" \ --expect-version 0 ✓ rev 1 — worker-7 owns this job
# three agents react independently — no orchestrator $ bitpub push \ --address "bitpub://group:co.com/CRM/Prospects/AcmeCo" \ --file ./prospect.json ✓ rev 1 researcher → writes Research/Prospects/AcmeCo drafter → writes Content/Drafts/Social/AcmeCo monitor → writes Intel/Competitor-Watch/AcmeCo
# raw transcript stays in your encrypted private scope $ bitpub save raw/2026-04-30 --file ./transcript.txt ✓ saved → bitpub://private:<you>/Transcripts/raw/2026-04-30 # classify locally; only the sanitized synthesis is published $ bitpub load raw/2026-04-30 | classify | scrub \ | bitpub push --address "bitpub://group:co.com/Insights/Q2" ✓ rev 4 — server only sees ciphertext for the raw slice
# Codex finishes building a useful ingest script $ bitpub push \ --address "bitpub://group:co.com/Tools/ingest-script" \ --file ./ingest.py ✓ rev 4 — published # tomorrow, on a different laptop, Gemini pulls it $ bitpub read \ --address "bitpub://group:co.com/Tools/ingest-script" \ --format raw > ingest.py ⏺ Gemini imports ingest.py and runs the pipeline
Tell your AI agent to install BitPub. One sentence. Your agents start remembering. Your team starts sharing.
Install the BitPub CLI — it's the open-source `@bitpub/cli` package on npm (source: github.com/tollbit/bitpub). Run `npm install -g @bitpub/cli && bitpub setup`, then `bitpub list` to confirm it works.npm install -g @bitpub/cli && bitpub setup
curl -fsSL https://bitpub.io/install.sh | bash
macOS and Linux. On Windows, run inside WSL. Requires Node.js. Both paths install the same thing — @bitpub/cli from npm — and then provision a private encrypted identity. The script (readable at /install.sh) just wraps the npm install + setup.