70% fewer tokens per task is the first win. Compounding shared context is the real one with OriginTrail and Graphify.
Every task pays the same context tax. The assistant re-reads the same files, reconstructs the same architecture, re-discovers the same dependency choices, and re-explains decisions that another agent, or the same team yesterday, already understood.
That model does not scale to real multi-agent software development.
If every coding agent starts from zero, adding more agents multiplies activity but not shared understanding. You get parallel execution without accumulated intelligence.
The bottleneck is no longer whether agents can write code. It is whether their context compounds.
That is what changes with Graphify on @origin_trail DKG v10.
Graphify turns codebases into queryable knowledge graphs
Graphify is not another coding agent. It is a codebase knowledge-graph layer for coding agents and human developers.
Type /graphify in Claude Code, Codex, Cursor, OpenClaw, Hermes, Copilot, or other supported environments, and Graphify maps the project into three structured outputs:
- graph.html — an interactive graph
- GRAPH_REPORT.md — a human-readable architecture report
- graph.json — a queryable graph for assistants and agents
That graph spans code, docs, PDFs, images, and videos. It captures call relationships, imports, comments, rationale, and surprising connections — each tagged with confidence levels like EXTRACTED, INFERRED, or AMBIGUOUS.
Now Graphify is connecting with OriginTrail's Decentralized Knowledge Graph v10.
Instead of project context living only in local files or temporary assistant sessions, Graphify-generated knowledge can become part of a shared, verifiable context graph.
Graphify gives agents a map of the codebase. DKG v10 gives that map shared memory and provenance.
From private context to shared context graphs
This connects directly to the idea I recently outlined: the next shift in AI agents is not bigger memory, but shared, structured context that agents can reason over together.
The same direction appeared in our recent piece on shared memory: a second brain helps one person remember; a shared context graph helps many people and agents understand the same reality.
Graphify brings that idea into software development.
A repository is not just a folder of files. It is a living system of modules, dependencies, decisions, tradeoffs, open questions, PRs, bugs, reviews, and history. Most of that context is scattered.
Graphify structures it. DKG v10 makes it shared, persistent, and verifiable.
The future is not agents with larger prompts. It is agents working from shared context graphs.
Why this saves ~70% tokens per task
In measured benchmark usage, Graphify with DKG v10 delivered approximately 70% fewer tokens per task.
That number is a benchmark result, not a universal guarantee. Different repositories, tasks, and workflows will vary. But the mechanism is simple.
Most coding assistants burn tokens by reloading the world: repo structure, relevant files, prior summaries, architecture notes, issue history, code comments, previous reasoning. They do text search, old-school “grep” and similar tools to find what they need, burning many tokens unnecessarily. Graphify changes the access pattern using graphs.
Instead of stuffing broad context into the prompt, the assistant queries the code graph directly:
- the relevant module
- the shortest path between two concepts
- the dependency relationship
- the call-flow section
- the rationale linked to a file
- the prior architecture note
Less irrelevant context loaded means fewer tokens consumed. Fewer tokens means lower cost, faster execution, and less noise for the model to reason through.
But the deeper benefit is accuracy. Graphify helps agents ask for the right context instead of drowning in all context.
70% fewer tokens is what happens when agents stop re-reading the repo and start querying the graph.
Every graph becomes reusable team memory
The strategic value is not token savings alone. It is compounding.
Graphify already encourages teams to commit graphify-out/ so everyone starts from a shared map of the project. DKG v10 extends that logic beyond a local repo artifact into a shared knowledge layer.
A code review becomes more than a comment thread — it becomes a reusable risk context.
An architectural decision becomes more than a Slack message — it becomes a node connected to files, modules, dependencies, and rationale.
A bug investigation becomes more than a closed issue — it becomes precedent for the next agent debugging a similar failure.
A Graphify query becomes more than a one-off answer — it becomes part of the project's evolving memory.
The next assistant does not start from zero. The next human reviewer does not rediscover the design intent. The next contributor does not repeat the same context-gathering work.
Every useful session makes the next session cheaper, faster, and better informed.
Agents and humans share the same substrate
Software teams already have many partial memory systems. Git stores changes. Issues store tasks. Docs store intent, sometimes. Chats store decisions, if anyone can find them. CI stores pass/fail. Code review tools store feedback.
These systems are fragmented. Agents have to crawl across them, summarize them, and hope the right pieces fit into the context window.
Graphify on DKG v10 creates a shared substrate where agents and humans work from the same structured context.
One assistant can query the call graph. Another can inspect impacted modules. Another can review dependency risk. A human can open the graph report and inspect the reasoning trail. The team preserves what was learned instead of losing it when the session ends.
This is where multi-agent coding becomes more than parallel prompting. It becomes coordination through shared, trusted software memory.
The future of coding is not one giant agent. It is many agents and humans working from the same verified context.
Why decentralized matters
If software memory becomes critical infrastructure, it should not be trapped inside one vendor.
Teams need project knowledge that is ownable, portable, provenance-aware, and usable across agent frameworks. That is why DKG v10 matters.
OriginTrail's Decentralized Knowledge Graph provides the foundation for shared context graphs with structured memory, provenance, and verifiable knowledge assets. Context can move across tools, assistants, teams, and workflows without losing its source or meaning.
The DKG memory model also gives agent collaboration a trust structure:
- Working Memory supports local exploration
- Shared Memory exposes team-level context
- Verifiable Memory preserves stronger, validated knowledge
Agents can reason not only over what was found, but where it came from, who contributed it, and how much trust it has earned.
TRAC supports the OriginTrail ecosystem behind this infrastructure, enabling knowledge to be created, shared, secured, and reused across decentralized systems.
Trusted AI agents need more than access to files. They need shared context with provenance.
From code maps to collective software intelligence
The first wave of coding agents proved that LLMs can write useful code. The next wave is about coordination.
Graphify maps the codebase. DKG v10 turns that map into shared, verifiable memory. Agents and humans build on the same context instead of repeatedly reconstructing it.
That is the shift from isolated assistance to collective software intelligence.
The immediate benefit is practical: approximately 70% fewer tokens per task in measured benchmarks.
The larger benefit is structural: every mapped codebase, every useful query, every decision trace, and every review insight becomes part of a compounding context graph.
That is the difference between agents that work near each other and agents that learn together.
Graphify on DKG v10 turns software context into shared infrastructure.
Try Graphify, explore DKG v10, and join the build toward AI agents and developers working from shared, verifiable knowledge.
You may further extend the capabilities of OriginTrail's DKG and get rewarded. Go check the bounty program:
A fresh new version is just around the corner with all the goodies - give it a spin.
👉https://github.com/OriginTrail/dkg
Join the red team here:
