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Resources / Working knowledge

Build the review practice, not just the report.

Practical material for teams turning scattered technical evidence into decisions they can explain.

Content system

Four questions guide everything we publish.

The library follows the same reasoning path as the product: establish truth, understand consequence, constrain AI, and improve engineering practice.

Architectural truth

How provenance, identity, relationships, history, and gaps create a reliable system model.

Security consequence

How findings become paths, blast radius, ownership, and actionable decisions.

Bounded AI systems

How agents, model providers, tools, context, retention, and cost remain governable.

Engineering practice

How to introduce continuous review without disrupting the way teams build and ship.

Guided paths

Start with your role and the decision in front of you.

Choose a working path through architecture truth, structural risk, agent boundaries, and implementation practice. Each path ends with an outcome your team can apply.

Choose your review question

A path through the library, not another content pile.

Library

Start with the decision in front of you.

Filter by format or search by the question your team needs to answer.

Guide

AI agent boundaries

A practical model for provenance, tools, human approval, telemetry, and cost controls.

AI architectsOpen
Field note

Architecture intelligence vs scanners

Understand where detection products stop and where cross-source architecture context begins, without forcing a replacement decision.

AppSec teamsOpen
Guide

Benchmark an AI security review

Evaluate evidence coverage, citation validity, replayability, isolation, decision quality, and measured cost instead of grading polished prose.

Security leadersOpen
Reference

Continuous review checklist

A practical operating rhythm for source freshness, coverage, review gates, remediation, and architecture memory.

Engineering teamsOpen
Guide

Evidence-backed architecture

Build an architectural model where every material relationship can explain its source, confidence, and history.

Security architectsOpen
Guide

Evidence-first content playbook

Plan searchable articles, technical field notes, LinkedIn points of view, X threads, and visual explainers from one truthful content system.

Founders and content teamsOpen
Interactive

Explore a living review

Use the guided product environment to inspect evidence, agent artifacts, architecture, and measured cost.

Evaluation teamsOpen
Guide

Governed model routing

Assign explicit model roles while keeping evidence access, retention, cost, and action authority consistent across providers.

AI platform teamsOpen
Guide

MCP as an evidence gateway

Design MCP around scoped evidence submission and typed actions rather than ambient repository or shell access.

Platform engineersOpen
Reference

MCP evidence gateway

See how approved tools submit tenant-scoped evidence without turning repository text into instructions.

Platform teamsOpen
Guide

Publish trust claims with evidence

Connect privacy and security language to implemented controls, known boundaries, upstream tools, and honest release gates.

Security and legal teamsOpen
Field note

The security context engine

Connect isolated findings to ownership, exposure, reachable paths, and system consequence.

Security engineersOpen
Field note

Trust boundaries and blast radius

Trace how identity, delivery, data, and runtime relationships change the consequence of a security weakness.

Threat modelersOpen
Reference

Veriom brand system

Use the shared identity, colour, type, card, motion, voice, imagery, accessibility, and implementation rules behind every public surface.

Design and product teamsOpen

Bring the next architecture decision into focus.

Show us the sources, constraints, and review question. We will map a safe evaluation path before you connect production systems.

Talk through your system