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This source-evidence page is currently authored and reviewed in English.

Alle Projekte

Die geschäftlichen Zusammenfassungen sind in dieser Sprache verfügbar. Produktabläufe und technische Belege werden auf Englisch gepflegt.

Produkt & Investition

LaunchpadOS

Produkturteil in ein wiederholbares Arbeitssystem überführen.

Eine folgenreiche Entscheidung ist über Dokumente verteilt. Ihre Annahmen, ihre verantwortliche Person und die Gründe für eine erneute Prüfung gehen verloren.

Produktverantwortliche, Gründer und interdisziplinäre Teams

Softwarewerkzeugkasten in aktiver Entwicklung

A product decision record
Decision
Advance, change or stop the proposed feature
Evidence
User need, technical constraints, economics
Uncertainty
Assumptions and dependencies to examine
Reopen when
A named assumption changes or evidence arrives
Decision logic and control flow

Explore the reasoning

Name the decision, accountable owner and credible alternatives—including keeping the current approach.

Engage now
A decision review connecting options, evidence, trade-offs and the next test to an accountable owner.
Inspect
Source toolkit under active development
Versioned skill files and product workflows with examples, rubrics and orchestration paths.
Still to validate
Skill inventory and structural depth are source scope, not proof of equal factual authority across every method or model.
Verify the applicable path-scoped licence and evidence rights, then expand independent method and output evaluation beyond the currently measured subset.

Quellen geprüft

The decision behind the system

What would make you change this product decision?

A product-management toolkit connecting skills, workflows, decision graphs and evidence. Make assumptions, dependencies and review triggers visible as a product moves from discovery to delivery.

LaunchpadOS structures reusable product judgement. TransformationOS explores organisational missions; E2A carries a consulting engagement from discovery to handover.

Reusable product workflows

Versioned skills and orchestration support discovery, strategy and delivery work through CLI, API and model-context interfaces.

Decision graphs

OPDG connects evidence, assumptions, dependencies, reversibility and review triggers so a decision can be revisited when conditions change.

Release-case reasoning

Configuration-bound Physical AI release cases expose missing evidence and human review gates. A structural verdict does not authorise deployment.

Read the complete system walkthrough
  1. Frame

    Name the decision, accountable owner and credible alternatives—including keeping the current approach.

  2. Connect

    Attach evidence, assumptions, dependencies and reversibility. Make missing information visible.

  3. Challenge

    Review the reasoning and relevant gates. Structural coherence does not establish factual correctness or permission to deploy.

  4. Decide

    Record the judgement, unresolved questions and the condition that should reopen the decision.

See all evidence and limits

Inspect the source, test conditions and operating limits in the technical record.

Technische Unterlagen und Evidenz

Brücke Business ↔ Technologie · Category operating system

Turn product judgement into an operating record without outsourcing authority to a model.

Makes full-lifecycle product judgement versioned, inspectable, and executable.

Dies ist eine Portfolio- und Quellinterpretation, keine Aussage über Kunden, Betrieb, Zertifizierung oder Ergebnisse.

  1. 01

    Geschäftlicher Druck

    Customer, portfolio, economic, delivery, and technical decisions are dispersed across documents and tools, so their original evidence and invalidation logic disappear.

  2. 02

    Produktentscheidung

    Define which product decisions matter, which evidence advances a gate, who owns the call, and what must cause the decision to reopen.

  3. 03

    Technischer Nachweis

    Versioned skills, the Operated Product Decision Graph, Release Case boundaries, CLI and MCP surfaces, workflow state, evaluations, and audit records.

  4. 04

    Evidenzrückfluss

    Changed assumptions, technical limits, release evidence, and field signals return to scope, economics, sequencing, and portfolio commitment.

Repository-/Laufzeitgrenze

Diese Seite interpretiert Quellen aus einem getrennten Venture-Repository. Quellcode dort bedeutet nicht, dass das Venture als Dienst in hyperion-consulting.io läuft.

Die KI-Verarbeitung von Besucher- und Kundendaten ist auf Mistral über den kontrollierten EU-Endpunkt beschränkt. Die vom Inhaber freigegebenen Pfade Helio, Suche und Product Council sind aktiviert. Ein getrenntes Redaktionsverfahren mit öffentlichen Quellen nutzt Anthropic mit kontrolliertem Mistral-Ersatz; es erhält keine Website-Anfragen, Kundendokumente oder Besuchergespräche. Deterministische Werkzeuge bleiben ohne Remote-KI verfügbar.

Quellcode-Evidenz

Was der Quellcode tatsächlich belegt

A versioned product-management toolkit combining skills, orchestration, decision graphs, evaluation, APIs and MCP surfaces. The current source adds evidence-linked product decisions and configuration-bound Physical AI release cases; generated judgement still needs accountable review.

Der detaillierte technische Stand wird auf Englisch gepflegt.

Reifegrad
Source toolkit under active development
Evidenzprüfung
Quellstand bis

Produkt- und Architekturentscheidungen

  • Compile reusable product practices into explicit skills, rubrics, and workflow stages.
  • Keep artefact generation, quality evaluation, memory, and trust records as separate concerns.
  • Treat Physical AI release readiness as an assurance verdict with human gates, not an automated deployment permission.

Prüfbare Evidenz

  • Versioned skill files and product workflows with examples, rubrics and orchestration paths.
  • Python CLI, API and MCP surfaces with workflow, evidence, audit and quality-test suites.
  • OPDG decision graphs linking evidence, assumptions, dependencies, reversibility and review triggers, plus bounded release-case fixtures.

Aussagegrenze

  • Skill inventory and structural depth are source scope, not proof of equal factual authority across every method or model.
  • Platform and tool surfaces require path-specific configuration and verification; source presence does not establish identical behavior or external-system access.
  • Software and method licences are path-scoped; evidence and trademark terms remain separate. Structural coherence does not establish factual correctness, deployment permission or legal conformity.

Repository-Evidenz ist kein Nachweis für Kunden, Betrieb, Zertifizierung oder Ergebnisse.

Tech Stack

Built With

Genannte Technologien kennzeichnen Repository-Abhängigkeiten oder Adapteroberflächen; sie belegen keine aktive Integration oder Bereitstellung.

Backend
Python 3.12+, FastAPI, Click CLI, Redis caching, Pydantic v2, litellm multi-provider abstraction
AI / LLM
Provider-adapter and routing source for Anthropic, OpenAI, Mistral and local-model paths, plus retrieval components; model availability and behaviour depend on configuration and current provider terms
Frontend
React 18, Vite, Tailwind CSS, skill browser UI, brief input, output panel, history panel
Integrations
Notion (pages), Linear (issues), Jira (tickets), GitHub (releases), Figma (specs), Miro (boards), Slack (digests), Confluence (wikis)
Infrastructure
Docker Compose (5 services), Kubernetes Helm, AWS ECS Fargate, GCP Cloud Run, nginx reverse proxy, API key scoping
Quality & Evaluation
Pytest structural skill audit, selected rubric and evaluation fixtures, benchmark harnesses, and property-based tests; factual method authority requires separate source assurance
Evaluation & access

Evaluation

Get Started with LaunchpadOS

Contact me to evaluate where LaunchpadOS can support your product practice, what still requires human product leadership, and which integrations would need separate verification.

Request a Demo

Inspect the dated skill inventory, virtual-role and workflow source, and the innovation pipeline implementation. The demo separates what is present in source from what is configured, tested and ready for accountable use.

Contact Sales

Mit Hyperion arbeiten

Eine Produktentscheidung einbringen

Eine Entscheidungsprüfung, die Optionen, Belege, Abwägungen und den nächsten Test mit einer verantwortlichen Person verbindet.

Bringen Sie eine kurze Beschreibung Ihrer Situation, Rahmenbedingungen und Entscheidung mit. Umfang, Verantwortlichkeiten und Angebot werden vor Arbeitsbeginn vereinbart.

Physical AI Product Leadership Mission

Use the toolkit inside an accountable product mission.

Hyperion can use selected LaunchpadOS source patterns while leading one evidence-backed product milestone. The commercial mandate remains the Physical AI Product Leadership Mission; LaunchpadOS is supporting R&D, not a fourth offer or a promise of autonomous delivery.

Explore the Product Leadership Mission

Source toolkit under active development

A product decision you can hand over.

For a technical founder

Structure a customer/problem brief, compare alternatives and record the assumptions behind an MVP or industrial pilot. Hyperion selects and reviews the relevant workflows; the founder owns business commitments.

For an existing product team

Organise approved field evidence, draft requirements and prepare a product-to-engineering handoff. Keep sources, open assumptions, decision owners and the next experiment attached to the record.

Prompt roles provide perspectives and workflow stages. They do not supply engineers or independently accountable employees. The current LaunchpadOS–TransformationOS handoff is local file exchange, not a unified production service.

Explore the Product Team Design Canvas