Fable, Sol, and Terra: what really changed for builders
A dated radar of new AI portfolios and a method for choosing by task, risk, cost per outcome, evals, and verifiability.
FORGE Knowledge
Executive reading to understand why it matters. Technical depth to check how it works — always with authorship, review and sources.
Reading trails
Filter by your goal. The category of each card shows the specific subject.
14 articles across all reading tracks.
A dated radar of new AI portfolios and a method for choosing by task, risk, cost per outcome, evals, and verifiability.
How to use AI to prepare better experiments without promoting a synthetic persona, click, prototype, or opinion into market evidence.
A six-phase path to turn building speed into evidence of a problem, product, operation, and a real exchange of value.
How to separate executor, checker, reviewer and approver to use AI in evaluation without creating circular authority or fictitious independence.
A practical grammar to link claims to subject, property, mechanism, evidence, verifier, validity and limit of inference.
A method for grading agent authority by effect, reversibility, sensitivity and uncertainty — without confusing capacity with permission.
How to separate specification, contract, test, coverage and eval so that each green supports only the decision it actually verified.
A practical contract to measure AI pilots by accepted outcomes, quality, flow, total cost, and risk — not by tokens or artifacts.
A technical guide for organizing intent, policy, execution, verification, evidence, and feedback around AI agents.
AI does not transform an organization alone: it enhances clarity, flow and learning — or accelerates ambiguities, queues and rework.
JARVIS's journey to FORGE and the six changes that transformed AI memory, decisions, and execution into a verifiable system.
AI can perform more work without receiving accountability: clear roles, boundaries, verifiers, and evidence preserve accountability.
Models change quickly; reliable results depend on context, tools, policies, verification, evidence and learning.
AI amplifies execution, but purpose, learning, judgment and accountability depend on how we redesign work.
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