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What is newly possible with ZAO's full tooling stack as of 2026-05-30 (live Bonfire graph recall via /delve, ZOE orchestrator Gap 1+2, Supabase public/private CRM, 190-endpoint Bonfires API with typed intake, Hermes, cross-bot relay): what NEW capabilities/workflows are unlocked, what's the highest-leverage next build, and how does it compare to other 2026 AI-agent-stack builders. Tier DEEP.
tier
DEEP
775 - What ZAO's Agent Stack Can Do Now (2026-05-30)
Goal: Inventory the new capabilities unlocked after this session's work (live graph recall, orchestrator Gaps 1+2, Supabase CRM, typed Bonfire intake), name the single highest-leverage next build, and position the stack honestly against the 2026 agent-stack field.
Key Decisions (recommendations first)
#
Decision
Why
1
Highest-leverage next build: a typed-triple ingestion path (use the live /knowledge_graph/add_triples + typed /entity + /edge + /ontology/ingest endpoints) for meetings + CRM, instead of prose episodes.
The Bonfires kernel (doc 771) AND the 2026 field consensus both reward deterministic typed extraction over LLM prose extraction. The API already exposes it (doc 771 findings). This is the one move that puts ZAO at the frontier on knowledge quality, not par.
2
Spread recall (/delve) beyond ZOE DMs to /meeting, Hermes, and the CRM.
Recall just went live but ONLY in ZOE's private concierge turn (PR #744). The same recall() graph context would sharpen meeting recaps, Hermes fix-context, and CRM dedupe. Cheap to extend - the function exists.
3
Agent-fed CRM from Gmail/GCal (MCPs already connected) is now buildable end-to-end.
CRM tables + bot write API + ZOE crm_op shipped (doc 772). The missing piece is the extract->dedupe->upsert loop from email/calendar - the exact "AI chief of staff" pattern Lindy/Dex sell. ZAO has the substrate; competitors mostly do post-hoc enrichment.
4
Use Gap 2 multi-agent dispatch for native research fan-out inside ZOE.
The GATEWAY + 8-worker dispatch landed (doc 759). ZOE can now run /zao-research-style parallel investigation itself instead of Zaal driving it from a terminal.
5
Do NOT build a bespoke memory engine. Ride Bonfires (graph) + the recall/mirror wiring.
Mem0/Zep have billions-scale temporal-reasoning proof; ZAO can't out-engineer that. The win is the typed-intake + CRM coupling on top, not the memory core.
What is newly possible (that wasn't before this session)
Graph-grounded ZOE answers, live. ZOE now runs a /delve query against the Bonfire graph before each DM and injects hits as <bonfire_recall> context. Proven live: a "zabal gamez" query returned 5 graph hits in the journal. Before: recall was dead (wrong endpoint), ZOE answered only from repo Read + memory blocks.
Typed knowledge ingestion (not just prose). The live API exposes /knowledge_graph/add_triples, /api/kg/add-triplet, typed /entity + /edge, /ontology/{ingest,match,gaps}, and the procedural /agents/{id}/stack/*. ZAO can write structured facts, not just prose episodes that the backend has to re-extract.
Agent-fed CRM. Supabase crm_contacts + crm_interactions (public/private RLS), a /network public feed, a /crm admin dashboard, and a ZOE crm_op write path (doc 772). ZOE can log "met X, talked about Y" straight into the CRM from a Telegram message.
Multi-agent dispatch under one gateway. Gap 1 (decompose.ts) + Gap 2 (8 worker subagents via the Agent/Task tool, GATEWAY pattern) landed. ZOE owns the task graph and can fan work out to workers - the supervisor topology that is 2026 best practice.
Autonomous code-fix loop (Hermes) + cross-bot relay were already live; they now compose with recall + CRM (e.g. a fix PR can be graph-grounded; a relay can log its outcome to CRM).
Ahead on integration depth (native structured write + graph), behind on breadth of connectors.
Long-term operator continuity
/delve per turn + Letta-style blocks
Mem0/Zep production-proven
Behind on proof, the wiring is sound.
One-paragraph read: ZAO's stack is a 2026-current hybrid - Mem0-style selective memory + LangGraph-style supervisor orchestration + Lindy-style CRM coupling, on a GLiNER-based extraction substrate that is cheaper than full GraphRAG. It is ahead on knowledge-engineering + CRM coupling, par on orchestration governance, behind on benchmarked temporal-reasoning depth. The differentiator to press is deterministic typed knowledge tied to a structured CRM and a real community - not the memory core, which the field has already mass-produced.
Zep: 63.8% LongMemEval (~15 pts over vector-only).
LangGraph: 33,343 stars, ~34.5M PyPI downloads/mo, ~2.4x faster than CrewAI on research tasks (46.8s vs 111s p50).
CrewAI: 44,600+ stars, 10M+ agent runs/mo, ~23% more token-efficient than LangGraph, 3x overhead on simple flows.
LazyGraphRAG (Microsoft): ~0.1% of full-GraphRAG indexing cost, 700x cheaper queries at equal accuracy. FastGraphRAG: 6x cheaper. Youtu-GraphRAG (ICLR 2026): 33.6% lower token cost + 16.62% higher accuracy vs SOTA.
Mastra: $22M Series A (Feb 2026), pivoted from LLM-routed .network() to supervisor after hitting 5 walls (memory propagation, routing fragility, observability, nesting, concurrency).
ZAO live: Bonfires API = 190 endpoints; ZAO bonfire = 283 chunks; /delve "What is ZAO?" = 51 episodes; recall proven live (5 hits on "zabal gamez").
Also See
Doc 759 - the orchestrator gap analysis + GATEWAY decision (17-Q grill)