Net AI Value pricing that stakes fees on measurable gains
Methodologies
17 methodologies.
Every one verified.
Named, defensible IP. Seventeen ways we make AI shipping repeatable.
FLAGSHIP AI-Act-aligned Karpathy-6 is designed to support AI Act Article 9 risk-management obligations. It materially reduces audit risk by surfacing fabrications, misattributions, and omissions before outputs reach a client.
Karpathy-6 Adversarial Verification
A six-failure-mode adversarial pipeline that verifies LLM-generated analytical outputs against source evidence before they reach a client.
Read the flagship method →
Foundations
Methodology
Outcome NAV
Methodology
Net AI Value
The financial framework for measuring AI return on investment honestly
Methodology
Service Awareness
CSDM-grounded service modelling that traces every AI initiative from business outcome down to infrastructure CI.
Methodology
Workshop-to-Design Audit
A 15-tier pipeline that transforms workshop transcripts into verified requirements, solution design, and traceable work decomposition.
Verification & Audit
Methodology
Implementation Verification
A post-execution gate that confirms code, scripts, and configuration built from a plan are correct, complete, and faithful to the specification.
Methodology
LLM-as-a-Judge
A structured model-selection methodology that evaluates candidates on the specific outputs your use case requires
Methodology
Regulated Encoder
A deterministic, pure-function rule encoder that enforces regulatory boundaries on AI outputs without LLM reasoning
Methodology
AI-Act-in-a-Box
A structured regulator workshop that maps your AI portfolio against EU AI Act risk tiers and produces a traceable compliance posture register.
AI-Native Architecture
Methodology
Radial Agent Architecture
A multi-agent topology pattern that places one orchestrator at the centre and deploys parallel specialist sub-agents at the periphery, preserving context isolation by design.
Methodology
CSDM v5 Accelerator
A structured, gate-governed methodology that bootstraps a production-grade ServiceNow Common Service Data Model in weeks, not quarters.
Methodology
Pearl's Third Rung
Causal AI reasoning that answers what would have happened
Methodology
Task Length Barrier
The empirical finding that agent output quality degrades beyond a coherence threshold
Practice & Adoption
Methodology
Cognitive Village
The human-in-the-loop posture for AI-augmented teams
Methodology
Apprenticeship Model
The AI-fluent workforce uplift methodology that builds human capability alongside AI capability
Methodology
Emergent Intent
The design pattern for AI-driven systems whose purpose is discovered through operation, not specified in advance
Methodology
Technical Debt Paradox
AI accelerates code velocity and technical debt simultaneously
Put the methodology to work
Stream D — Evaluation & Verification applies Karpathy-6 and the regulated encoder to your existing analytical outputs. Bring the document; we surface what requires correction.