Product & investment intelligence
LaunchpadOS
Turn product judgement into a repeatable working system.
A consequential decision is spread across documents. Its assumptions, owner and reasons for reopening it are getting lost.
Product leaders, founders and multidisciplinary teams
Source toolkit under active development
- 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
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.
Source reviewed
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
Frame
Name the decision, accountable owner and credible alternatives—including keeping the current approach.
Connect
Attach evidence, assumptions, dependencies and reversibility. Make missing information visible.
Challenge
Review the reasoning and relevant gates. Structural coherence does not establish factual correctness or permission to deploy.
Decide
Record the judgement, unresolved questions and the condition that should reopen the decision.
Inspect the source, test conditions and operating limits in the technical record.
Explore the technical record and evidence
Business ↔ technology bridge · 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.
This is a portfolio and source interpretation—not a customer, deployment, certification, or outcome claim.
- 01
Business pressure
Customer, portfolio, economic, delivery, and technical decisions are dispersed across documents and tools, so their original evidence and invalidation logic disappear.
- 02
Product decision
Define which product decisions matter, which evidence advances a gate, who owns the call, and what must cause the decision to reopen.
- 03
Technical record
Versioned skills, the Operated Product Decision Graph, Release Case boundaries, CLI and MCP surfaces, workflow state, evaluations, and audit records.
- 04
Evidence return
Changed assumptions, technical limits, release evidence, and field signals return to scope, economics, sequencing, and portfolio commitment.
Repository/runtime boundary
This page interprets source from a separate venture repository. Source presence does not make the venture a service running inside hyperion-consulting.io.
Visitor and client-data AI processing is restricted to Mistral through the governed EU endpoint. Owner-authorized Helio, Search and Product Council paths are enabled. A separate public-source editorial lane uses Anthropic with governed Mistral backup; it receives no website enquiries, client documents or visitor conversations. Deterministic tools remain available when remote AI is unavailable.
Source evidence
What the source actually establishes
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.
- Maturity
- Source toolkit under active development
- Evidence review
- Source snapshot through
Architecture and product decisions
- 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.
Inspectable evidence
- 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.
Claim boundary
- 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 evidence is not client, deployment, certification, or outcome evidence.
Tech Stack
Built With
Named technologies identify repository dependencies or adapter surfaces; they do not assert a live integration or deployment.
- 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.
Work with Hyperion
Bring one product decision
A decision review connecting options, evidence, trade-offs and the next test to an accountable owner.
Bring a short description of your situation, constraints and decision. We agree the scope, responsibilities and quote before work begins.
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 MissionSource 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