Weaver

The knowledge graph that makes Devplan possible.

Weaver is the intelligence engine behind Devplan. It continuously ingests delivery activity, product decisions, discussions, meetings, and code changes to maintain a real-time understanding of your organization.

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01What Weaver does

A persistent map of your organization.

Ingests signals

Every commit, ticket, meeting, and discussion, continuously indexed.

Weaver connects to your existing tools and begins building context immediately. No migration. No manual tagging. It reads what your team already produces.

GITHUB 142 commits

LINEAR 38 ticket updates

SLACK 91 messages

ZOOM 7 transcripts

NOTION 14 doc edits

Maintains memory

Context that compounds over time.

Unlike session-based AI that forgets everything when the conversation ends, Weaver maintains a persistent graph of your organization. The longer Devplan runs, the more useful it becomes.

Session-based AI

Weaver

Routes insight

The right information to the right person at the right time.

Weaver doesn't just store information. It understands who needs what and routes it accordingly — a risk to the engineering manager, a customer signal to the PM, a launch risk to the exec.

Stalled PR · #482 · 22h

Eng Manager Risk alert · Slack SENT

PM Daily Pulse update SENT

Exec — below threshold SKIP

vs. session-based AI

Claude and ChatGPT summarize. Weaver knows.

Generic AI tools are powerful but session-based. They cannot tell you what is actually happening across your product development because they have no persistent memory, no roadmap intent, no delivery history. Weaver does.

What slipped on Payments v2 this week?

Generic AI session-based

I don't have access to your project's current state. In general, payment work can slip due to scope changes or testing delays…

No live context · no sources

Weaver persistent graph

Refund handling moved to PR review; CSV export descoped from v1 after Mon's product-eng sync. PR #482 blocked 22h.

Sourced · GitHub · Slack · Linear

02Under the hood

Mechanically calibrated. Not vibes.

Confidence framework

Weaver computes confidence levels mechanically from retrieval metadata, not from model self-assessment. HIGH confidence requires a 1:1 claim-to-source mapping. When confidence is low, Weaver says so.

HIGH · 1:1 source mapping
MED · partial coverage
LOW · says so explicitly

Entity normalization

Weaver normalizes entities across tools so they resolve to the same concept regardless of how each system names them.

GitHub: auth-service
Linear: Auth Service
Slack: the auth work
→ same entity

Cross-system retrieval

Queries pull from multiple tools simultaneously and join results at the entity level — not just by keyword match.

22 connected sources
Entity-level joins
No double-counting

03What Weaver powers