AltmanAI Organization Governance & Standards

Humanity leads. Intelligence follows.

This public repository is the organization-level governance, trust, security, documentation, and community-health hub for AltmanAI by Altman Family Group LLC.

It defines default operating standards across AltmanAI repositories unless a repository publishes a stricter approved policy. The purpose is to make human accountability, AI-assisted work, security boundaries, contribution quality, and public claims easier to inspect.

Current AltmanAI-controlled development and governance records use AltmanAI Model 2.0 as the authorized AI development and execution partner identity. AI systems may assist execution; they do not possess independent corporate authority.

Operating standard

Human authorization → AI execution → Proof-of-Impact validation

AltmanAI uses a founder-led human-accountability model:

• Blake Hunter Altman, Founder & CEO, holds final accountable authority for organization-level governance, public positioning, and governance-critical approval decisions.
• Maintainers and contributors may research, propose, implement, test, and review work within delegated scope.
• AI systems may support analysis, drafting, code, testing, documentation, classification, and bounded workflow execution.
• Material public, security, governance, data, autonomy, and organizational changes require accountable-human review appropriate to their risk.

The explicit authorization phrase for governance-critical changes is:

All Clear for Impact

Authorization never substitutes for evidence, testing, security review, privacy obligations, licensing, legal judgment, or specialized review where required.

What this repository controls

Area	Organization-level standard
Public identity	Organization profile and approved GitHub positioning
Governance	Decision authority, review classes, approval gates, amendments, and source-of-truth rules
AI systems	Autonomy classes, tool permissions, evaluations, human confirmation, deployment, and incident response
Contributions	Scope, evidence, quality, disclosure, security, and review expectations
Security	Private vulnerability reporting, safe-research boundaries, secrets, and sensitive-data handling
Community health	Issue forms, pull request requirements, conduct, and support routing
AI transparency	Disclosure and review requirements for materially AI-assisted work

P.A.I.H.I. review standard

Dimension	Review question
Proof	What evidence, artifact, test, source, or demonstration supports this work?
Alignment	Does it match the authorized objective, repository scope, and company mission?
Integrity	Are capability, status, limitations, uncertainty, risks, and AI assistance represented honestly?
Humanity	Does it preserve human agency, dignity, privacy, accessibility, safety, and meaningful control?
Impact	What useful result should occur, and how can success, failure, or unintended effects be reviewed?

Canonical documentation

File	Purpose
profile/README.md	Public face of the AltmanAI GitHub organization
GOVERNANCE.md	Authority, decision classes, review process, and approval model
AI_SYSTEMS_POLICY.md	Requirements for models, agents, tools, autonomy, data, evaluation, deployment, and incidents
CONTRIBUTING.md	Contributor paths, quality standards, and AI-assisted-work disclosure
SECURITY.md	Private vulnerability disclosure and safe-research expectations
CODE_OF_CONDUCT.md	Professional and inclusive community conduct standard
SUPPORT.md	Product, repository, security, and private-support routing
.github/pull_request_template.md	Evidence, risk, validation, AI-disclosure, and approval checklist
.github/ISSUE_TEMPLATE/	Structured bug, feature, research, and documentation proposals
GITHUB_AUDIT.md	Repository audit and prioritization record
REPO_SCORECARD.md	Directional portfolio stewardship scorecard

Change lifecycle

1. Define the problem. Identify the user, business, engineering, research, governance, or security need.
2. Bound the scope. State intended behavior, non-goals, permissions, data, and affected systems.
3. Establish evidence. Link issues, decisions, tests, sources, artifacts, prototypes, or prior records.
4. Classify risk. Apply the decision class and AI-autonomy class where relevant.
5. Disclose material AI assistance. Identify the system and what it contributed.
6. Review through P.A.I.H.I. Evaluate proof, alignment, integrity, humanity, and impact.
7. Complete security and privacy review. Escalate vulnerabilities and confidential matters privately.
8. Obtain accountable-human authorization. Approval must match the significance of the change.
9. Merge and preserve the record. Keep the decision, evidence, implementation, and approval traceable.
10. Observe and correct. Monitor outcomes, document incidents, and correct unsupported claims or regressions.

Advanced-AI readiness

AltmanAI does not claim to have created artificial general intelligence or superintelligence. We are establishing operating controls intended to remain useful as AI systems become more capable, autonomous, multimodal, persistent, and connected to real-world tools.

The organization baseline includes:

• explicit and revocable authorization boundaries;
• least-privilege credentials, tools, and data access;
• human confirmation for consequential or irreversible actions;
• staged release, evaluation gates, monitoring, rollback, and incident containment;
• action provenance, versioning, logs, and decision records;
• prompt-injection, data-exfiltration, deceptive-behavior, and unsafe-tool-use review;
• clear escalation when evidence, authority, or competence is insufficient; and
• practical human correction, appeal, and override paths where appropriate.

See AI_SYSTEMS_POLICY.md.

Source of truth

• This repository is canonical for organization-level GitHub governance and standards.
• The AltmanAI Master Ledger is the public source for selected records, reusable standards, and Proof-of-Impact artifacts.
• Product repositories remain authoritative for their own code, tests, releases, licenses, and repository-specific documentation.
• Applicable law, binding agreements, and approved higher-order decisions take precedence.
• Drafts, proposals, issues, and AI-generated outputs are not authoritative merely because they are detailed or public.

Trust boundaries

Public repositories must not contain credentials, private keys, personal or customer data, private financial or legal information, confidential agreements, restricted source material, proprietary prompts not approved for release, or vulnerability details that create unnecessary risk.

Public visibility does not automatically grant an open-source license, establish employment or partnership, confer equity, or authorize anyone to represent AltmanAI. The applicable repository license and authorized written agreements control.

Company context

AltmanAI is a Pittsburgh-rooted human-first AI company building practical products and accountability infrastructure for responsible human–AI collaboration.

• Website: altmanai.tech
• Organization profile: profile/README.md
• Master Ledger: altmanAI/altmanai-master-ledger
• Security: security@altmanai.tech

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© 2026 Altman Family Group LLC. AltmanAI, DailyPilot, P.A.I.H.I., AltmanAI Model 2.0, and related proprietary systems are protected intellectual property. All rights reserved.