Investor or project evaluator
Evaluate AI projects through evidence
To evaluate an AI project, connect each claimed capability to an artifact, a test and the conditions under which it was exercised. MAIOS can support continuity in evaluation through sources and project state; economic judgments and decisions remain with the evaluator.
Draft generated by Codex on . Human review remains pending.
From a demo to the next piece of evidence
A demo shows behaviour in one case. Ask what was actually executed, which dependencies made it possible and what happens when a condition changes. A useful milestone also identifies missing evidence and the decision it will enable.
One claimed capability, one case to examine
If a project claims to maintain context, ask it to resume an activity after its source is corrected. Observe what it preserves, which choices it reconsiders and how it makes the new condition visible. The result helps distinguish a described function, a function actually exercised and the possibility of transferring it to another environment.
Which investigation is needed now?
You can request a focused technical test, clarify a dependency or examine the work required for delivery. Comparisons and benchmarks need explicit data and method. This brief organizes available evidence and open questions without assigning automatic scores.
Product, research and resources
In evaluation, distinguish available versions, research direction and the work needed to realize it. People, corpora, compute and infrastructure can support a development trajectory; each step requires its own evidence. The research and vision page describes the D-ND direction and its relationship with current kernels, providing a basis for relevant questions and milestones.
AI project evidence brief
Use it for one capability or milestone, keeping observations and hypotheses separate.
Thesis and user
Which problem does the project address, and who should use it?
Artifact
Which code, document or result can you inspect?
Evidence
Which behaviour was exercised, and using which method?
Dependencies
Which models, data, access, operating costs and people are needed?
Limits and recovery
Under which conditions does the behaviour fail or require intervention?
Milestone
Which next piece of evidence would change your assessment?
kernel_chat 1.0.0
Start with MAIOS
To work with sources in ChatGPT, open the kernel_chat installation. If evaluation lives in a repository, the builder path introduces Project Kernel.
MAIOS, kernel_chat and MAIOS Project Kernel are independent projects. ChatGPT is an OpenAI product. Publication on ChatGPT Sites does not imply OpenAI endorsement or certification.