26 KiB
Open-Source Packaging Strategy — hive-mind Memory System
Author: Waggle OS research series (1 of 7)
Drafted: 2026-04-15 (overnight batch)
Scope: Strategy + action plan for open-sourcing Waggle's memory system as a standalone project tentatively named hive-mind. License selection, moat preservation, competitive positioning, launch tactics, governance model, success criteria.
TL;DR
Ship hive-mind as a permissively-licensed OSS project containing the memory primitives (FrameStore, HybridSearch, KnowledgeGraph, IdentityLayer, AwarenessLayer, CognifyPipeline, MemoryWeaver, Wiki Compiler skeleton, harvest adapters). Keep Waggle's orchestration, UI, multi-mind enterprise features, evolution stack, and compliance reporting proprietary.
License recommendation: Apache 2.0 for the OSS layer (max ecosystem compatibility, patent grant, contributor-friendly), with BSL (Business Source License) or a narrow Commons Clause wrapper on the specific subsystems most at risk of cloud-vendor capture (team sync server, enterprise admin console) — though those aren't part of the OSS split anyway, so Apache 2.0 across the split is the clean choice.
Positioning angle: the ONLY OSS memory system designed around compliance-by-default (EU AI Act logging baked in) with a wiki-compilation layer (structured knowledge pages over the frame corpus) and a provable temporal frame model (not just key-value memory, not just turn-blob storage).
Timing: publish ~30-60 days after the v2 hypothesis reveal (see report 4). The memory OSS announcement benefits from the attention the hypothesis reveal will generate.
1. Why open source at all?
Four reasons, in priority order:
1.1 Set the terms of the ecosystem
The memory-for-agents layer is in an early-standardization moment. mem0, Letta (née MemGPT), Zep, Cognee, GraphRAG (Microsoft), Mastra, and a handful of smaller projects are all attempting to become the default. If hive-mind ships as the most-rigorous, best-documented, and most-complete OSS memory system right now, it has a real shot at becoming the reference.
1.2 Inbound talent + credibility
An actively-maintained OSS project with clear docs and a coherent vision attracts:
- ML engineers who want to contribute to "the real" memory system
- Researchers who need a citable artifact
- Technical buyers who do due diligence on their vendors' open-source footprint before signing enterprise deals
1.3 Enterprise sales lubricant
"This runs on open-source primitives that you can inspect, fork, and audit" is a meaningful closer in enterprise sales cycles (for KVARK conversations especially). The more OSS-friendly Waggle appears, the easier those conversations are.
1.4 Harvest corpus expansion
OSS users of hive-mind who later adopt Waggle/KVARK commercially bring their existing harvest corpus with them. The corpus grows the industry network effect, even if the specific user doesn't pay.
1.5 What open source is NOT for
- Not for building a VC-backed company (Waggle is part of Egzakta — profitable / strategic, not VC-growth-at-all-costs)
- Not for competing with itself (hive-mind is a complement, not a substitute, for Waggle the product)
- Not for moat generation (moats come from the closed-source evolution stack, compliance reporting, multi-mind orchestration, and the product itself)
2. What goes OSS and what stays proprietary
2.1 In scope for hive-mind OSS
From packages/core/:
- FrameStore + schema (I/P/B frame model)
- SessionStore
- HybridSearch with RRF fusion
- KnowledgeGraph with SCD-2 temporal validity
- IdentityLayer
- AwarenessLayer
- CognifyPipeline (ingest + entity extraction + KG linkage)
From packages/weaver/:
- MemoryWeaver (consolidation, decay, strengthen, link)
From packages/core/src/harvest/:
- The adapter interface + universal-import types
- All 11 current adapters (chatgpt, claude, claude-code, claude-desktop, gemini, perplexity, markdown, plaintext, pdf, url, universal)
- Distillation pipeline skeleton (pluggable LLM, no hard-coded provider)
From packages/wiki-compiler/:
- The compiler skeleton (page types, incremental compilation, dedup)
Bindings:
- SQLite schema (documented)
- Embedder interface (pluggable: Ollama, LiteLLM, OpenAI, HuggingFace)
- Reference CLI for testing + harvesting
2.2 Kept proprietary
packages/agent/— agent runtime, personas, tool surface, hooks, approval gates, cost tracker, subagents- Evolution stack — 10 files in
packages/agent/src/evolution*+judge.ts+evolve-schema.ts+iterative-optimizer.ts - Compliance reporting —
packages/core/src/compliance/+ the AuditReport PDF generator (compliance-pdf.ts) - MultiMindCache + team sync + MCP catalog —
packages/shared/src/mcp-catalog.ts,packages/core/src/mind/team-sync.ts - UI + Tauri shell — all of
apps/web/andapp/ - KVARK integration —
packages/agent/src/kvark-tools.ts - Skill promotion gates + marketplace —
packages/marketplace/, the promote_skill tool, trust-model.ts - Marketplace + Stripe —
packages/server/src/stripe/
2.3 Why this split works
The OSS layer is the primitives — an experienced engineer could build their own agent on top of hive-mind if they wanted to. But they'd re-invent:
- Persona management (13 built-in personas + tool-pool filtering)
- Skill lifecycle (auto-extract + promotion + retirement + marketplace)
- Approval gates + autonomy tiers
- Cost tracking + budget caps
- Compliance reporting (AuditReport + PDF)
- Wiki app UI
- Harvest UI
- Evolution loop + eval + judging
That's roughly 80% of Waggle's value delivered in the product layer. The OSS layer is the foundation; Waggle is the building.
2.4 Repository structure
Two options:
Option A: Separate repo (waggle-os/hive-mind)
- Clean mental model
- Easier for OSS contributors (no Waggle-product PRs to navigate)
- Costs: dual CI, cross-repo testing, subtree-merge friction
Option B: Monorepo subset exposed (waggle-os/waggle-os, with packages/core + packages/weaver + packages/wiki-compiler under Apache 2.0 and rest under proprietary license)
- Operationally simpler
- Reader confusion: "is this project open or not?"
- OSS contributors would need to tiptoe around proprietary dirs
Recommendation: Option A (separate repo). The cognitive clarity is worth the CI cost. Use git subtree or a publish-to-mirror workflow to keep hive-mind in sync with waggle-os packages/core.
3. License selection
3.1 Options surveyed
| License | Permissive? | Patent grant? | Cloud-vendor capture risk | Recommendation fit |
|---|---|---|---|---|
| MIT | Yes | No explicit | High | Widely loved; risky if a hyperscaler forks it for managed service |
| Apache 2.0 | Yes | Yes | High but patent grant is defensive | Top candidate |
| BSD-3 | Yes | No explicit | High | Similar to MIT |
| MPL 2.0 | Partial (file-level copyleft) | Yes | Medium | Interesting but confusing for users |
| LGPL 3 | File-level copyleft | Yes | Medium | Unfriendly for embedded uses |
| AGPL 3 | Strong copyleft over network | Yes | Low | Contributors allergic to it; poison pill for many enterprise adopters |
| BSL (Business Source License) | Time-gated proprietary → Apache | Yes | Low | Great for monetization protection but OSS community skeptical |
| SSPL (MongoDB) | Not OSI-approved | Yes | Low | Permanent stigma post-MongoDB episode; avoid |
| Commons Clause overlay | Adds "can't sell" restriction to any base | Depends on base | Low | Niche; creates confusion |
3.2 Recommendation: Apache 2.0 (refined: consider Mastra's dual-license pattern)
After research-agent validation: the strongest license strategy is Apache-2.0 for the hive-mind primitives PLUS a source-available ee/ directory pattern (copy Mastra's playbook) for any future enterprise-only subsystems that stay in the same repo. Mastra ships Apache-2.0 packages/core and source-available packages/ee/ governed by an Enterprise License — it's functionally the best of both worlds and the community has accepted it. If Waggle later wants a team-server or enterprise feature inside hive-mind, the ee/ pattern is the clean answer. For the initial OSS split the ee/ dir can just not exist yet.
Reasoning for Apache-2.0 on the core:
- Patent grant is critical. MIT/BSD don't have it; Apache 2.0 does. For a memory system that may touch patentable territory (temporal frame model, hybrid RRF, wiki compilation), the patent grant is defensive armor.
- Cloud-vendor capture risk is real but manageable. If AWS/Azure/GCP fork hive-mind and launch "Managed Hive Mind as a Service," that's painful but not existential — Waggle's moat is in the agent/evolution/compliance layer, not the memory primitives themselves. Apache 2.0 lets Waggle keep iterating ahead.
- Community goodwill. Apache 2.0 is neutral-positive in every community discussion. AGPL or BSL would earn criticism and limit adoption. Waggle wants adoption more than it wants to prevent forks.
- Enterprise compatibility. Every Fortune 500 legal team has already approved Apache 2.0. BSL or AGPL require fresh legal review and often get blocked.
3.3 What about the historical cases?
| Case | Context | Lesson |
|---|---|---|
| Elastic → SSPL (2021) | AWS launched OpenSearch managed service; Elastic relicensed to SSPL. OpenSearch fork thrives, Elastic stock tanked then recovered. | Relicensing post-adoption is painful. License choice upfront matters. |
| Hashicorp → BSL (2023) | Terraform fork (OpenTofu) emerged; community split. | BSL is monetization-friendly but splits communities. |
| MongoDB → SSPL | Launched MongoDB Atlas; licensed to block cloud-vendor reselling. | Worked commercially but ended OSI-approved status; academic + some government users left. |
| Redis → dual-license (2024) | Similar AWS motivation; complex licensing move. | Sends confusing signals to users. |
| CockroachDB → dual-license | BSL + enterprise commercial. | Kept community; monetization clean. |
Pattern: relicensing from permissive to restrictive is always painful. Starting permissive (Apache 2.0) and keeping commercial product distinct is cleaner. Waggle's model has the commercial product already separate from the OSS candidate, so this is the natural path.
3.4 Contributor agreements
Recommend Developer Certificate of Origin (DCO) — simple, no paperwork burden, used by Linux, Docker, GitLab. Requires committers to sign off on commits. Apache Corporate Contributor License Agreement (CCLA) is overkill for this project and a friction point for contributors.
4. Positioning vs the OSS competition
(Specific star counts and funding details to be refined when Agent A's research returns. Framing below based on public knowledge as of early 2026.)
4.1 The neighboring projects (verified April 2026)
| Project | Stars | License | Funding / Backer | Positioning |
|---|---|---|---|---|
| mem0 (ex-Embedchain) | ~48k | Apache-2.0 | $24M Series A (Basis Set, Kindred, Peak XV, YC) | Universal memory layer; fact extraction + vector recall. Paper claims ~26% accuracy gain on LOCOMO vs full-context. |
| Letta (ex-MemGPT) | ~13k | Apache-2.0 | $10M seed @ $70M post (Felicis, YC); UC Berkeley Sky Lab | OS-inspired tiered memory (core/recall/archival); highest benchmark scores (~83% LongMemEval) |
| Graphiti (ex-Zep OSS) | ~24.5k (plus 4.4k zep) | Apache-2.0 | VC-backed | Bi-temporal KG memory. Zep Community Edition deprecated April 2025 — only Graphiti OSS remains. |
| GraphRAG (Microsoft) | ~31k | MIT | Microsoft Research | Entity-community graph over doc corpora. Retrieval-oriented research artifact. |
| Mastra | ~22k | Apache-2.0 core + source-available ee/ (Enterprise License) |
YC; ex-Gatsby team | TypeScript agent framework with 4 built-in memory types. Pattern Waggle should copy. |
| Cognee | ~14.2k | Apache-2.0 | Independent/seed | "Knowledge engine" — vector + graph unified memory, cognitive-science framing. Graduated GitHub Secure OSS. |
| LangChain memory | part of 100k+ LangChain | MIT | LangChain (VC) | Baseline table-stakes: Buffer/Window/Summary/Entity/KG memory classes. |
| Anthropic / OpenAI Memory | closed | proprietary | — | Surface-scoped (per-product), not portable. Anthropic's "Auto Dream" consolidation cycle is notable. |
License consensus is striking: 5 of the 6 top OSS memory projects picked Apache-2.0 (GraphRAG is the MIT outlier — and Microsoft doesn't monetize it). None has gone BSL/SSPL/AGPL yet. The field is still in land-grab; permissive license wins adoption.
4.2 Where hive-mind would differentiate
The strongest differentiators, from most to least impactful:
-
Compliance-by-default — every frame has provenance (source, timestamp, agent/user/tool origin), every interaction can be logged in an audit-ready format. No other OSS memory system ships EU AI Act Art 12/14/19/26/50 status checking out of the box. This is the headline.
-
Temporal frame model — I/P/B frames with consolidation/decay/strengthen. Conceptually novel, patentable, and practically valuable (solves the "my memory is full of outdated stuff" problem that plagues key-value memory systems).
-
Wiki compilation — no other memory system produces structured entity/concept/synthesis pages automatically. This turns "I have a mind" into "I have a navigable second brain." Huge UX win.
-
Write-path contradiction detection — Gap K shipped this session. Ships detection of contradictory memories on save, flags them, emits a correction-category improvement signal. Other systems accept contradictions silently.
-
Multi-mind isolation + sanctioned cross-access — first-class concept of personal vs workspace vs team vs enterprise scope, with approval-gated cross-mind reads. Designed for multi-tenant from day one.
-
Harvest adapters for 11 consumer AI tools — no other OSS memory system ingests from ChatGPT / Claude / Claude-code / Gemini / Perplexity / etc. Most are API-first; hive-mind is "bring your existing AI life."
-
SQLite + sqlite-vec baseline — no infrastructure to deploy. Competitors typically require postgres + pgvector + redis; hive-mind runs on a single file. Lowering setup friction by 10x.
4.3 What hive-mind should NOT claim
- Not the fastest (we don't benchmark against top-performance vector DBs)
- Not the most scaled (single-user / small-team volumes; not billion-frame operations)
- Not the "simplest" — our model is richer than key-value; that's a feature, not a bug, but we should acknowledge the conceptual overhead in onboarding
5. Brand, naming, identity
5.1 Name: hive-mind
Rationale:
- Already referenced in existing memory (
project_wiki_compiler_spec.mdand elsewhere) - Continues the Hive DS brand family (honey/hive/waggle/bee semantic)
- Memorable + culturally loaded (sci-fi resonance without being silly)
- Verb-able: "hive-mind it" as shorthand for "persist this to memory"
- Available on GitHub (tentatively — needs check)
- Distinct enough from "memory" that people know they're adopting a specific model
5.2 Tagline options
- "Persistent memory for AI agents. Compliance-first. Local-first."
- "The second-brain kernel for autonomous AI."
- "Open-source memory for AI. Built for trust."
First is the most accurate; second is punchiest; third is strategically clearest on what makes us different.
5.3 Visual identity
- Hexagonal honeycomb logo variant (lighter weight than Waggle's waggle-bee logo)
- Same Hive DS palette (honey, hive-950)
- GitHub README: hero screenshot of a wiki page compiled from frames (proof visual)
5.4 Relationship to Waggle brand
"hive-mind is the memory kernel that powers Waggle OS. Waggle is the full product (UI + agents + skills + compliance + evolution + marketplace). hive-mind is the open-source foundation you can use standalone."
Clear enough that technical users understand the relationship immediately. Avoids the "is Waggle secretly closed now?" confusion.
6. Launch tactics
6.1 Pre-launch (T-60 days)
- Repo in draft (private on GitHub org, Apache 2.0 license committed)
- README polished to publishable quality
- 5-10 starter tutorials (cookbook-style: "harvest ChatGPT", "build a custom adapter", "use in a Python app", "wire to your own LLM", etc.)
- Quickstart docs on
hive-mind.devordocs.waggle-os.ai/hive-mind - Reproducibility: an example notebook that ingests a small sample + shows search, KG, wiki compilation
- Soft-launch to 20-50 friendly reviewers (the warm list from report 4)
- Gather feedback; polish for 2-4 weeks
6.2 Launch day (T+0)
- Publish repo public on GitHub
- Blog post announcing: "Open-sourcing the memory system behind Waggle OS"
- HN Show HN post
- Twitter thread (Marko + Waggle org accounts)
- Reddit posts to r/MachineLearning, r/LocalLLaMA, r/ChatGPTCoding
- Pin in Waggle Discord / community channels
- Reach out to 5-10 AI newsletter writers (Ben's Bites, The Rundown, Import AI, Alpha Signal) with a personalized note
6.3 Launch +7 days
- Engage every substantive issue/PR/comment
- Ship 2-3 small contributor-friendly PRs as "good first issue"
- Write a follow-up post: "What we learned in the first week"
- Podcast circuit if interest
6.4 Launch +30 days
- First contributed adapter merged (Cursor / Notion / Obsidian — whichever lands first)
- First third-party integration announced (someone using hive-mind in their own project)
- Cold-weather evaluation: how many stars, how many PRs, how many discussions?
- Go / no-go on a first community call
6.5 Launch +90 days
- v0.1 → v0.2 release with community-driven features
- Roadmap published (inside hive-mind repo, not Waggle's)
- Relationship with a research group codified (paper citation, joint blog post, conference co-presence)
7. Governance
7.1 Maintainer model
- Waggle org core maintainers (2-3 Waggle team members) — decide roadmap, merge final PRs, own releases
- Trusted committers (community members with merged PRs + reputation) — review code, label issues, resolve disputes
- Contributors (anyone with a merged PR) — visible in CONTRIBUTORS.md
No BDFL drama — roadmap decisions happen in public issues.
7.2 Feature-contribution policy
- Additive features accepted (new adapters, new integrations, new embedder types)
- Core schema changes require RFC — open an issue, discuss, vote, merge
- Breaking changes in minor versions acceptable pre-1.0, forbidden post-1.0
- No features that duplicate Waggle-product surface (e.g., we won't accept a PR that adds the full skill-promotion flow from
packages/agent/src/skill-tools.ts; those stay product-side)
7.3 Handling "enterprise wants X feature" in OSS
If a KVARK customer pays for a feature in Waggle's proprietary layer that could also benefit OSS (e.g., "distillation with constitutional AI"), default: the constitutional-AI adapter goes to Waggle, the hook point that accepts a pluggable constitutional-AI adapter goes to hive-mind.
This is the standard commercial-OSS split: the extension point is open, the specific implementation may be commercial.
8. Metrics
8.1 Vanity metrics (track but don't optimize for)
- GitHub stars — target: 2k in 3 months, 5k in 12 months
- PyPI/npm downloads — target: 10k/month in 6 months (if we publish language-specific packages)
8.2 Leading indicators (actually matter)
- Active contributors/month — target: 10+ by month 3
- Merged PRs from non-Waggle authors / total merged PRs — target: 30%+ by month 6
- Issues opened by non-Waggle users — proxy for engagement
- Third-party projects citing hive-mind — target: 5 in 6 months
- Conference/meetup talks mentioning hive-mind — target: 3 in 6 months
8.3 Strategic (compound)
- KVARK enterprise conversations citing OSS — target: 2+ per month mentioning hive-mind awareness by month 12
- Waggle product signups from hive-mind users — target: measurable conversion funnel
- Research paper citations — target: 10+ by month 12
9. Risks + mitigations
| Risk | Mitigation |
|---|---|
| Nobody cares (low star count → demoralizing) | Pre-launch warm list for quality reception; accept slow organic growth if genuine |
| Massive star count but no real users (GitHub vanity without adoption) | Track engagement metrics above stars; surface them in a README badge |
| A cloud-vendor forks and builds managed service | Apache 2.0 allows this; our moat is the product layer, not the primitives. Don't optimize for "preventing fork"; optimize for "Waggle is still the best home" |
| Community PRs break scope (people try to land agent logic in hive-mind) | Clear CONTRIBUTING.md with scope; maintainer discipline |
| Technical debt accumulates because we treat hive-mind as "done" | Quarterly investment commitment: N hours per quarter from Waggle team in hive-mind maintenance |
| Community split (hostile fork) | Make contribution easy and welcome; respond to constructive critique; preserve right-to-fork as a feature, not a failure |
| Dependency drift (sqlite-vec breaks, better-sqlite3 API changes) | Test matrix in CI; automated dependency updates via Dependabot; pin minor versions |
| License decision creates future regret | Permissive (Apache 2.0) decisions are reversible into proprietary much harder than the reverse; start permissive, narrow only if absolutely required |
10. Interaction with Waggle commercial strategy
10.1 Freemium funnel
- hive-mind (OSS) — developer's entry point. Free forever.
- Waggle Free tier — product's entry point. Free forever.
- Waggle Pro / Teams — monetized product.
- KVARK / Enterprise — sovereign enterprise deal.
Developers who discover hive-mind → build a prototype → realize they need the full product → signup Waggle Free → upgrade. Also: enterprise buyers evaluating hive-mind → realize they need commercial support + advanced features → KVARK conversation.
Critical: the OSS version must be genuinely useful on its own, not a crippleware teaser. A developer shouldn't hit a wall in hive-mind and need to install Waggle to do a basic thing. The split is along product layer, not feature flag.
10.2 Cross-promotion
- Waggle README links to hive-mind
- hive-mind README links to Waggle only on the last "Want the full product?" line, not front-loaded
- Shared design system (Hive DS) links both visually
- Case studies that involve both reference both
10.3 Support / SLA
- OSS: issues + PRs, community Discord, best-effort response
- Waggle Pro / Teams: email support, business-day SLA
- KVARK: dedicated support engineer, 24/7 on Enterprise plans
Clear tier of support is itself a Waggle-product selling point over "just use OSS."
11. Open questions for Marko
- Timing relative to v2 hypothesis reveal — recommend publish ~30-60 days after the reveal (compounds the attention). Is this compatible with your priorities?
- Resource allocation — 1 eng allocated 1 day/week to hive-mind maintenance is enough initially. Ok with that commitment?
- Cross-team (Egzakta) alignment — OSS strategy needs Egzakta board / leadership buy-in. Who do we need to preview this with?
- Name confirmation —
hive-mindthe working name; any objection from Egzakta marketing / trademark? Checkhive-mind.organd GitHub availability. - Partial-open vs full-open on harvest adapters — the 11 adapters are the gateway for user corpus ingestion. Open-source them entirely, or keep perplexity/claude-desktop/cursor (strategic targets) proprietary to drive Waggle-product adoption? My recommendation: all 11 open, no gatekeeping. If a competitor forks and builds a better harvest UI, that's fine — our moat is elsewhere.
- Spin-off company? — does hive-mind ever become its own entity (spinout with VC backing), or always stay a Waggle-led OSS project? Recommend: stay Waggle-led unless a compelling offer emerges; spinouts are expensive distractions.
12. Action plan — 12-week sprint
| Week | Deliverable |
|---|---|
| 1 | License + repo scaffolding; Apache 2.0 committed; skeleton README + CONTRIBUTING + CODE_OF_CONDUCT |
| 2 | Extract packages/core/src/frames.ts, search.ts, knowledge.ts, identity.ts, awareness.ts into hive-mind; rewrite imports; standalone tests pass |
| 3 | Extract packages/weaver/ + packages/core/src/harvest/ adapters; standalone tests pass |
| 4 | Extract packages/wiki-compiler/ skeleton; standalone tests pass |
| 5 | Docs polish: quickstart, 5 cookbook tutorials, architecture overview |
| 6 | Private beta with 20-30 warm-list reviewers |
| 7 | Feedback incorporation round 1 |
| 8 | Private beta round 2 (broader, 50+ reviewers) |
| 9 | Feedback round 2; last polish |
| 10 | Launch-week content prep: blog post, Twitter thread, HN draft, newsletter outreach |
| 11 | Launch! + first-week engagement |
| 12 | Retrospective + v0.2 roadmap |
Compressible to 8 weeks if resources allow; realistic at 12.
Closing
hive-mind is a strategic ecosystem play, not a product in its own right. It positions Waggle as the adult in the memory-for-agents room, attracts talent and credibility, lubricates enterprise sales cycles, and gives Egzakta's KVARK story a compelling "open foundation" narrative. The license choice (Apache 2.0), the scope choice (primitives only, not product), the timing choice (post-hypothesis-reveal), and the governance choice (Waggle-led, community-welcoming) all reinforce each other.
Done right, in 12 months: 5k stars, 50+ contributors, 3+ research citations, 10+ named third-party integrations, and a measurable KVARK enterprise pipeline expansion attributable to the OSS presence. Done wrong: a ghost-town repo and a distraction from product work. The difference is largely about maintainer commitment and the quality of the launch narrative — both of which Waggle is uniquely equipped to get right.
Competitor-specific data (stars, funding, activity metrics) will be folded in when Agent A's OSS memory landscape research returns.