AI-native product builder and system architect with a strong UX and customer-experience mindset.

I design and build systems across personal AI, conversational interfaces, customer experience, and digital ecosystems. My work often sits at the intersection of product logic, UX, architecture, and practical AI-native workflows.

• Personal AI and AI twin systems
• Owner-controlled personal information infrastructure
• Conversational products, services, and venues
• Customer experience AI systems
• UX-driven product and system architecture
• Digital ecosystems and platform thinking
• Practical AI-native product development

Over the years I have worked in many roles including founder, advisor, mentor, speaker, strategist, and product architect. What has stayed constant is that I enjoy building the most, especially when the result reaches real customers and improves their experience.

AI has made that role even more exciting. A lot of the old friction between idea, structure, documentation, prototyping, and execution can now be reduced dramatically. That makes multidisciplinary product and systems thinking more valuable than before.

My workflow often starts with voice-based thinking and brainstorming, frequently while walking outside, using ChatGPT to clarify product logic, user journeys, and structure.

From there I typically move quickly into:

• structured product documentation
• feature and UX logic
• early prototypes
• UI-first iteration
• repository-based refinement with coding tools

I like getting to the end-user experience early, then iterating outward from the product experience and inward toward the underlying system logic.

I use AI across the full product workflow, not only for coding.

Common tools and approaches include:

• ChatGPT for thinking, documentation, and structuring
• Lovable for rapid first prototypes and end-user experience iteration
• GitHub-based workflows
• Claude Code and Codex working within the same repository when useful
• OpenClaw for hands-on experimentation with agentic workflows, memory, and orchestration

I also run my own OpenClaw setup at home and have built my own related web and mobile apps around that environment.

My current open framework work is organized through peecos / PIOS 2.0 for personal-scale infrastructure and Entity Core / EIOS for entity-scale organizational memory.

PIOS is a Personal Intelligence Operating System framework for owner-controlled personal information infrastructure: preserved sources, canonical events, structured knowledge, retrieval surfaces, governance, and portable setup paths for agents and applications.

Entity Core is the organization-scale sibling initiative. EIOS, the Entity Information Operating System, defines how organizations can preserve originals, record events, maintain governed memory, and make operating context usable by people and AI agents.

• peecos organization: github.com/peecos
• PIOS 2.0 master documentation: peecos.org/pios/master
• PIOS framework repository: github.com/peecos/pios
• AWS template path: github.com/peecos/pios-core-aws-template
• Self-hosted VM path: github.com/peecos/pios-core-self-hosted
• Entity Core website: entitycore.org
• Entity Core GitHub organization: github.com/entity-core
• EIOS 1.0 specification: github.com/entity-core/eios

The public peecos repositories are the open framework and setup-template layer. My own private implementation and migration work remain separate.

• Builder portfolio: valto.github.io/portfolio
• Open framework work: peecos.org
• peecos GitHub organization: github.com/peecos
• Entity Core: entitycore.org
• Entity Core GitHub organization: github.com/entity-core
• Speaking and AI coaching: valtoai.com
• LinkedIn: linkedin.com/in/valto

Much of my work lives in private or organization-owned repositories, so this GitHub profile does not fully represent everything I have built or contributed to.

Because of that, I use my public portfolio to document selected work themes, case studies, and system thinking in a more visible way.

This profile is best understood as one part of a broader builder portfolio.

Systems where identity, knowledge, memory, and interaction come together in a more personal AI layer.

Owner-controlled information architecture for preserved sources, event logs, knowledge projections, agent retrieval, governance, and portable Core setup paths.

Organization-controlled memory architecture for preserved originals, event truth, governed context, and agent-ready entity operations.

Conversational layers that help products, services, and places explain themselves, answer questions, and learn from customer interaction.

Systems that turn customer interaction and feedback into insight, priorities, and better decisions.

Long-term work around connected products, services, data flows, and the wider structures around digital markets.

I'm especially interested in building AI-native products that:

• solve real problems for real customers
• make technology feel more natural, not more technical
• connect user experience, business logic, and system design clearly
• give people durable ownership and control over their own information context
• create stronger customer understanding and better market-facing value

If you're interested in product building, AI-native systems, speaking, advisory work, or collaboration:

• LinkedIn: linkedin.com/in/valto
• Website: valtoai.com
• Portfolio: valto.github.io/portfolio