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Oleg Maslov
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docs/briefs/2026-04-25-launch-comms-templates.md
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# Launch Communication Templates — SOTA Claim Multi-Asset Suite
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**Date**: 2026-04-25 (autored 2026-04-24 late evening)
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**Status**: Ready-to-publish templates sa placeholder za actual benchmark numbers
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**PM**: claude-opus-4-7 (Cowork)
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**Trigger**: Phase 2 N=400 completion + PM-RATIFY-V6-N400-COMPLETE + SOTA result PASS
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**Placeholders to fill post-result**:
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- `[LOCOMO_SCORE]` — actual % achieved (target 91.6% baseline)
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- `[BASELINE_REF]` — Mem0 publication reference
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- `[H1_PVAL]` — Fisher one-sided p-value (target <0.10)
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- `[RETRIEVAL_PASS]` — % correct on retrieval cell
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- `[NO_CONTEXT_PASS]` — % correct on no-context cell
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- `[DELTA_PP]` — percentage point difference
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- `[SUBJECT_MODEL]` — Qwen 35B-A3B-Thinking (already known)
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- `[JUDGE_TRIO]` — Opus 4.7 + GPT-5.4 + MiniMax M2.7 (already known)
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- `[KAPPA_TRIO]` — 0.7878 conservative trio (already known)
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- `[COST_USD]` — actual N=400 spend
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- `[N400_DURATION]` — actual wall-clock
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---
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## Asset 1 — Technical Blog Post (publish on waggle-os.ai/blog or Medium)
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### Title options
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1. "Waggle hits SOTA on LoCoMo: how a sovereign Chinese-judge ensemble scored [LOCOMO_SCORE]% on memory benchmarks" (technical, headline-driven)
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2. "We built an AI memory layer that beats Mem0. Here's what it took." (narrative, founder voice)
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3. "How a 35B sovereign model outperformed cloud frontier models on long-context recall" (deep technical)
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**Recommend**: Option 2 for waggle-os.ai/blog, Option 1 for cross-post na arXiv/Hacker News pull
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### Outline (target 2,500-3,500 words)
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**Opening hook (300 words)**
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- Open with a concrete user moment ("Your AI forgets you exist between sessions. Every chat starts from zero.")
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- Pivot to thesis: "Memory is the real moat. Not training. Not parameters. Memory."
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- Reveal: "Today we're sharing benchmark results from our cognitive layer architecture — Waggle hit [LOCOMO_SCORE]% on the LoCoMo long-context memory benchmark, using a 35B-parameter sovereign model + bitemporal knowledge graph + audit-trail-grade retrieval."
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**Why memory matters (400 words)**
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- The "Groundhog Day problem" — current LLMs are stateless
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- Three current approaches: longer context windows (expensive, hits limits), RAG (works but generic), agent memory (Mem0, MemGPT, LangChain memory)
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- LoCoMo benchmark: 5-cell evaluation methodology (no-context / oracle-context / full-context / retrieval / agentic)
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- Industry baselines: Mem0 [BASELINE_REF]%, GPT-4 + RAG, Claude + native memory
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- What makes this hard: memories must persist, be retrievable, be auditable, be governed
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**Our architecture (700 words)**
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- **Local-first cognitive layer** — `.mind` file format on user's disk, not cloud
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- **Bitemporal knowledge graph** — every memory has VALID and RECORDED timestamps (audit-trail grade)
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- **MPEG-4 inspired I/P/B compression** — keyframes (I), update frames (P), bidirectional summary frames (B)
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- **EU AI Act Article 13 audit triggers** — every recall logged with provenance, replayable state
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- **Model-agnostic** — works with any LLM (Claude, GPT, Gemini, Qwen, local)
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- **MCP server protocol** — standard interop with Claude Code, Cursor, etc.
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- Diagram: 4-layer stack (User → Tauri shell → React app → Cognitive substrate → Provider routing)
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**Methodology — how we benchmarked (600 words)**
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- N=400 LoCoMo-mini canonical fixture
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- 5 cells × 80 instances each
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- Subject model: [SUBJECT_MODEL] (sovereign, runs locally on H200 8-GPU node)
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- Judge ensemble: [JUDGE_TRIO] (US + US + CN jurisdictional diversity)
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- Pre-registered manifest v6 sa SHA-pinned protocol
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- κ inter-rater reliability: [KAPPA_TRIO] (substantial agreement, recalibrated for new trio)
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- Fisher one-sided primary hypothesis test: retrieval > no-context (p < 0.10)
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- Cost per run: [COST_USD], wall-clock [N400_DURATION] under concurrency=1
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- Full pre-registration: github.com/marolinik/waggle/manifest-v6 (link)
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**Results (500 words)**
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- Primary hypothesis H1 (retrieval > no-context): [VERDICT — PASS / FAIL]
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- Retrieval cell: [RETRIEVAL_PASS]% pass rate
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- No-context baseline: [NO_CONTEXT_PASS]%
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- Delta: [DELTA_PP] percentage points improvement
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- Fisher exact one-sided p-value: [H1_PVAL]
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- Per-cell breakdown table: oracle-context, full-context, agentic
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- Comparison vs Mem0 [BASELINE_REF]%: [+/- delta]
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- Caveat section: agentic cell weaker κ (0.6875 GPT×MiniMax pair), descriptive treatment for that subset
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- Honest acknowledgment of methodology limitations (sample size, judge ensemble jurisdictional diversity, etc.)
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**Why this matters strategically (400 words)**
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- For developers: stable API for memory primitive, MCP-native, model-agnostic
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- For enterprises: EU AI Act audit trail by default, GDPR-compliant local-first, data sovereignty
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- For researchers: open pre-registration, reproducible benchmarks, no proprietary judge ensemble required
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- The bigger thesis: cognitive layer that any LLM plugs into is the real moat. Not the model. The memory.
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**What's next (300 words)**
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- hive-mind OSS substrate releases today (Apache 2.0, github.com/marolinik/hive-mind)
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- Waggle desktop app: Free tier live, Pro $19/mo, Teams $49/seat/mo
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- KVARK enterprise sovereign deployment program: contact sales@egzakta.com
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- Coming: longer context evaluation, agentic episode memory, multilingual benchmarks
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- Ask: try Waggle, send feedback, file bugs, contribute to hive-mind
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**Closing CTA (100 words)**
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- Download Waggle: waggle-os.ai
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- Read full pre-registration: github.com/marolinik/waggle/manifest-v6
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- Follow: @waggle_os, Discord (link), Marko Marković on LinkedIn
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- Engineering hires: We're hiring (link)
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### Voice notes
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- Per `marko-markovic-style` skill: senior CxO + technical depth + Serbian-English bilingual sensibility
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- No marketing fluff; evidence-driven assertions
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- Acknowledge limitations openly (signals integrity)
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- Cite primary sources with arxiv links where applicable
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- Diagrams hand-drawn or schematic, not corporate vector art
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---
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## Asset 2 — LinkedIn Long-form (1,200-1,500 words)
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### Headline
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"We just hit SOTA on AI memory benchmarks. Here's the honest story behind [LOCOMO_SCORE]%."
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### Opening (founder voice)
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"For the past 6 months, my team and I have been quietly building something specific: a cognitive layer that gives AI agents real memory. Today's the day we share results.
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LoCoMo is the standard benchmark for long-context memory in LLMs. Mem0 — the current SOTA reference — scored [BASELINE_REF]%. We tested our architecture on the same N=400 fixture, with full pre-registration, and we hit [LOCOMO_SCORE]%."
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### Body (5-7 paragraphs)
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1. **The problem** — AI agents are amnesiacs. Context window grows but memory doesn't persist. Every session starts from zero. Real productivity needs continuity.
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2. **The architecture** — We built three things: hive-mind (open-source memory substrate), Waggle (consumer desktop app), KVARK (enterprise sovereign deployment). All share one cognitive layer.
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3. **The benchmark** — N=400 LoCoMo-mini, 5 cells (no-context / oracle / full-context / retrieval / agentic), subject model Qwen 35B-A3B running locally, judge ensemble Opus 4.7 + GPT-5.4 + MiniMax M2.7 sa κ=0.7878 substantial agreement, pre-registered manifest v6.
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4. **The result** — [LOCOMO_SCORE]%, primary hypothesis [PASS/FAIL] sa Fisher p=[H1_PVAL]. Honest caveat: agentic cell weaker κ, treated descriptively.
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5. **Why it matters** — Memory is the moat. Models commoditize, memory differentiates. Local-first means data sovereignty. EU AI Act audit triggers built-in.
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6. **What changes today** — hive-mind OSS goes live, Waggle desktop app launches, KVARK enterprise pilot program opens.
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7. **The ask** — Try it. Break it. Send feedback. We hire engineers who care about this kind of work.
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### CTA
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"Waggle Free tier: waggle-os.ai — no credit card.
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hive-mind on GitHub: github.com/marolinik/hive-mind
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Hiring: jobs.egzakta.com
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DM me with bugs."
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### Voice
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- First-person Marko, executive but technical
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- One narrative, no bullet-list overload
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- Honest tone, not "we're disrupting AI" hype
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- 1-2 emojis max (if any), professional register
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---
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## Asset 3 — Twitter / X Thread (10-12 tweets)
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### Tweet 1 (hook)
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"Mem0 is the SOTA reference for AI memory benchmarks at [BASELINE_REF]% on LoCoMo.
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We just hit [LOCOMO_SCORE]%.
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Here's what changed and why it matters 🧵"
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### Tweet 2
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"Memory is the real moat in AI. Not training. Not parameters.
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Models commoditize. Memory differentiates."
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### Tweet 3
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"The architecture: cognitive layer that any LLM plugs into.
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- hive-mind: OSS memory substrate (today)
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- Waggle: consumer desktop app (today)
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- KVARK: enterprise sovereign (next)"
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### Tweet 4
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"Local-first. Bitemporal knowledge graph. MPEG-4 inspired memory compression. EU AI Act audit triggers by default. Model-agnostic."
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### Tweet 5
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"Benchmark: N=400 LoCoMo-mini, 5 cells, pre-registered manifest v6.
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Subject: Qwen 35B-A3B (sovereign, local).
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Judges: Opus 4.7 + GPT-5.4 + MiniMax M2.7. κ=0.7878."
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### Tweet 6
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"Result: [LOCOMO_SCORE]%, primary hypothesis [PASS/FAIL] (Fisher p=[H1_PVAL]).
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Retrieval cell: [RETRIEVAL_PASS]%.
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No-context: [NO_CONTEXT_PASS]%.
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Delta: [DELTA_PP]pp."
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### Tweet 7
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"Methodology pre-reg: github.com/marolinik/waggle/manifest-v6
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Honest caveat: agentic cell weaker κ. Treated descriptively. We're not hiding anything."
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### Tweet 8
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"What's live today:
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→ hive-mind OSS (Apache 2.0): github.com/marolinik/hive-mind
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→ Waggle desktop: waggle-os.ai
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→ Free tier, no credit card"
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### Tweet 9
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"Why this matters strategically:
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For devs: MCP-native memory primitive, model-agnostic.
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For enterprises: GDPR + EU AI Act compliant by default.
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For researchers: reproducible, pre-registered, open."
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### Tweet 10
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"We're hiring engineers who think memory architecture is the next 10x lever.
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jobs.egzakta.com"
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### Tweet 11 (close)
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"Long-form: [LINK to blog post]
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Try Waggle: waggle-os.ai
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Star hive-mind: github.com/marolinik/hive-mind
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@-mention prominent ML researchers / orgs you'd want feedback from (DAIR, Anthropic researchers, EU AI Act enforcement bodies, etc.)"
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### Tweet 12 (community)
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"Discord: [LINK]
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Bugs: github.com/marolinik/waggle/issues
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Email: hello@waggle-os.ai
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Building this in the open. Come build with us."
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---
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## Asset 4 — hive-mind OSS Announcement (GitHub README + Release Notes)
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### README.md (top section)
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```markdown
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# hive-mind
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> Local-first cognitive substrate for AI agents.
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> Bitemporal knowledge graph + MPEG-4 inspired memory compression + EU AI Act audit triggers.
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> Apache 2.0 licensed. Zero cloud dependencies.
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[](LICENSE)
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[](https://waggle-os.ai/blog/sota)
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**hive-mind** powers Waggle, the desktop AI workspace, but it's a standalone library you can use directly. MCP server included.
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## What it does
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- Persists agent context as `.mind` files on user's disk (no cloud)
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- Bitemporal: every memory has VALID and RECORDED timestamps
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- Compresses memory like MPEG-4 video (I/P/B frames)
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- Provides MCP protocol server for any compatible client (Claude Code, Cursor, custom)
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- 11 harvest adapters (Claude, GPT, Gemini, Qwen, local Ollama, Anthropic API, OpenAI API, Together, OpenRouter, MiniMax, Zhipu)
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- Wiki compiler: turns memory graph into navigable knowledge base
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- EU AI Act Article 13 audit triggers built-in
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## Benchmark
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LoCoMo (long-context memory): **[LOCOMO_SCORE]%** vs Mem0 [BASELINE_REF]%.
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Pre-registration: [manifest v6](./benchmarks/preregistration/manifest-v6-preregistration.md)
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Methodology: [BENCHMARK.md](./BENCHMARK.md)
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## Quickstart
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[install + basic usage]
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## Architecture
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[diagram]
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## License
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Apache 2.0. See [LICENSE](LICENSE).
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```
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### Release notes (v0.1.0 — first public release)
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```markdown
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# v0.1.0 — Public release
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This is the first public release of hive-mind, the cognitive substrate that powers Waggle.
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## What's in this release
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- Core memory primitives: store, retrieve, query, audit
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- Bitemporal knowledge graph engine
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- MPEG-4 inspired memory compression (I/P/B frames)
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- MCP server protocol implementation
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- 11 harvest adapters
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- Wiki compiler
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- EU AI Act audit trigger framework
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- Local-first persistence (.mind file format spec)
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## Benchmarks
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- LoCoMo: [LOCOMO_SCORE]% (vs Mem0 [BASELINE_REF]% reference)
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- Methodology: pre-registered manifest v6
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- Audit trail: every recall logged with provenance
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## What's not in this release
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- Cloud sync (intentionally — local-first)
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- Multi-user collaboration (Pro tier in Waggle)
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- Skills marketplace (Waggle-only feature)
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## Coming next
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- Multilingual benchmark coverage
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- Agentic episode memory
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- Web extension harvest adapter
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Built by Egzakta Group. Marko Marković and team.
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License: Apache 2.0.
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```
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---
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## Asset 5 — Waitlist Email (subscriber broadcast)
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### Subject line options
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1. "We hit SOTA on AI memory. Waggle is live."
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2. "Waggle launched. Here's your early access link."
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3. "[LOCOMO_SCORE]% on LoCoMo. Waggle is finally public."
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### Body
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```
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Hey [FIRST_NAME],
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Six months ago you signed up to hear when Waggle was ready.
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Today's the day.
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We hit [LOCOMO_SCORE]% on LoCoMo — the standard AI memory benchmark — beating Mem0's [BASELINE_REF]% reference. Full methodology + pre-registration here: [BLOG_LINK].
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|
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Three things you can do right now:
|
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|
||||
1. Download Waggle Free tier (no credit card): waggle-os.ai
|
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2. Star hive-mind on GitHub (the OSS substrate): github.com/marolinik/hive-mind
|
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3. Reply to this email with feedback. I read every message.
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|
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If you signed up because you wanted memory that persists across AI conversations — that's exactly what's live today. Local-first. Privacy-first. Model-agnostic.
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Pro tier ($19/mo) and Teams ($49/seat) include extras. Free is fully functional.
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Thanks for waiting.
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|
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— Marko
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Founder, Waggle / Egzakta Group
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|
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P.S. We're hiring engineers who care about cognitive architecture. jobs.egzakta.com
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```
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---
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## Asset 6 — Press Kit One-Pager (PDF + web)
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### Layout (1 page, two columns)
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||||
|
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**Left column (40%)**
|
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- Waggle logo (vector + raster)
|
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- Tagline: "AI Agents That Remember"
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- Founded: 2025, Egzakta Group
|
||||
- HQ: Belgrade, Serbia (international footprint)
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- Stack: Tauri 2.0 + React 19 + local-first cognitive layer
|
||||
- Funding: Bootstrapped (Egzakta cash flow)
|
||||
|
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**Right column (60%)**
|
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- 1-paragraph elevator pitch:
|
||||
"Waggle is a desktop AI workspace where agents remember your context, connect to your tools, and improve with every interaction. Built on hive-mind, an open-source cognitive substrate with bitemporal knowledge graph, audit-trail-grade memory provenance, and EU AI Act compliance by default. Local-first. Privacy-first. Model-agnostic."
|
||||
|
||||
- 3 key facts:
|
||||
- **Benchmark**: [LOCOMO_SCORE]% on LoCoMo (vs Mem0 [BASELINE_REF]%)
|
||||
- **Architecture**: Local-first cognitive layer + 23 native AI apps + 13 persona system
|
||||
- **Pricing**: Free / $19 Pro / $49/seat Teams + KVARK enterprise
|
||||
|
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- Press contact: press@waggle-os.ai
|
||||
- Media kit (logos, screenshots, founder photo): waggle-os.ai/press
|
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### Visual
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- 1 hero screenshot Waggle desktop sa Cockpit + Memory + Graph windows
|
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- 1 hero screenshot honeycomb visualization
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||||
- Quote box: Marko Marković quote pull from blog post or LinkedIn
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||||
---
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|
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## Pre-publish checklist
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||||
|
||||
Before pulling trigger on any asset:
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||||
|
||||
1. **Numbers verified** — every `[PLACEHOLDER]` filled with actual benchmark output
|
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2. **Marko personally reviewed** every asset (no auto-publish)
|
||||
3. **Legal review** za bilo kakve compliance claims (EU AI Act, GDPR mentions)
|
||||
4. **Embargo timing** — synchronize: blog post + LinkedIn + Twitter thread + GitHub release within 30 min window
|
||||
5. **Email broadcast** sent 24h after public posts (give organic momentum first)
|
||||
6. **Analytics** — track UTM sources per asset (`?utm_source=blog`, `?utm_source=linkedin`, etc.)
|
||||
|
||||
---
|
||||
|
||||
## Distribution sequence
|
||||
|
||||
**Hour 0** (e.g., 2026-04-26 09:00 CET):
|
||||
- GitHub: hive-mind v0.1.0 release published
|
||||
- Blog: technical post live
|
||||
- LinkedIn: long-form post by Marko
|
||||
- Twitter: thread posted
|
||||
|
||||
**Hour +30 min**:
|
||||
- Hacker News: submit blog post (Marko or community)
|
||||
- Reddit: r/LocalLLaMA, r/MachineLearning (community submission preferred)
|
||||
- Discord: Anthropic Discord, MCP community Discord
|
||||
|
||||
**Hour +24h**:
|
||||
- Waitlist email broadcast
|
||||
|
||||
**Hour +48h**:
|
||||
- Newsletter outreach (TLDR AI, Ben's Bites, AI Tidbits — submit to editors)
|
||||
- Reach out to specific researchers / VCs / enterprise contacts
|
||||
|
||||
**Week +1**:
|
||||
- Podcast outreach (Latent Space, MLOps Podcast, etc.)
|
||||
- Conference proposal submissions (NeurIPS workshops, EMNLP, etc.)
|
||||
|
||||
---
|
||||
|
||||
## Risk register
|
||||
|
||||
- **Numbers don't match expected** — if [LOCOMO_SCORE] < [BASELINE_REF], pivot from "we hit SOTA" framing to "honest evaluation methodology + how we plan to improve". DO NOT publish overstated claims.
|
||||
- **Press misinterprets** — provide pre-briefed FAQ document for journalists
|
||||
- **GitHub repo not ready** — verify hive-mind extraction completed before announcement (per `project_locked_decisions` H-34 5-10 day extraction window)
|
||||
- **Stripe checkout fails on launch day** — test cards verified day-of, support inbox monitored 24h post-launch
|
||||
- **Server overload** — Vercel auto-scales; plan for 100x baseline traffic spike in first 6h
|
||||
Reference in New Issue
Block a user