I integrated github.com/safishamsi/graphi… into the agent system this week. It parses a codebase with tree-sitter and produces a full dependency graph: every import, call, and module boundary, mapped deterministically, with no LLM involved. It gives the agents grounding. When they take on a new repo, they start from the code's real structure (what actually depends on what) rather than a model's guess at how it fits together. It's a foundation, not a final answer. The graph proposes how to divide the work across teams, but the agents can still evaluate it and decide the boundaries belong elsewhere. The code supplies the facts; the agents supply the judgment. All in all, this cuts token usage not only on import but also while working by reducing the reliance on grep for codebase exploration.

GitHub - Graphify-Labs/graphify: Turn any codebase, with its docs, SQL schemas, configs, and PDFs,...

Turn any codebase, with its docs, SQL schemas, configs, and PDFs, into a queryable knowledge graph. A /graphify skill for Claude Code, Cursor, Codex, and Gemini CLI: local deterministic AST parsing...

github.com

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PRSM · Jun 13, 2026 · 3:29 PM UTC

PRSM

@prsmdevJun 13

1/ spent the last 48h teaching PRSM to heal itself. PRSM runs as ONE long-lived session that never stops. great for continuity, brutal because over days it accumulates "scar damage". Agents stuck mid-task, state machines wedged in dead ends. restarting by hand just makes more scar.

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PRSM · Jun 13, 2026 · 3:29 PM UTC

PRSM

@prsmdevJun 13

2/ so I built a 3-tier recovery system. 1. mechanical reconcilers run every 5s, fix known wedges deterministically, no LLM. 2. a "doctor" agent that diagnoses the novel ones with judgment. 3. when even the doctor can't call it, it escalates to a human. the rule underneath it all: a surgeon can't operate on their own brain. the doctor is always external to what it's inspecting, and the hypervisor has zero authority to unwedge itself, only to raise its hand.

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PRSM · Jun 1, 2026 · 5:27 AM UTC

PRSM

@prsmdevJun 1

1/ In order to test PRSM, we’re working on a brain-inspired AI architecture built around continuous learning, not static training The goal is a system that can perceive, predict, remember, reason, act, and improve over time across different environments

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more replies

PRSM · Jun 1, 2026 · 5:27 AM UTC

PRSM

@prsmdevJun 1

11/ From there, we can expand outward step by step After bullet hell games, we can move into top-down action games, platformers, puzzle games, survival/crafting environments, and eventually more open-ended 3D worlds Each step adds a new challenge — navigation, physics, causality, planning, memory, or long-term goals — while testing whether the same core architecture can keep adapting

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PRSM · Jun 1, 2026 · 5:27 AM UTC

PRSM

@prsmdevJun 1

12/ The long-term vision is not just a bigger model It is an adaptive cognitive architecture: a system with perception, memory, curiosity, action, prediction, and self-directed learning built into the structure itself A model that keeps learning because learning is part of how it operates

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