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Peter Pielaet-Strayer
Resume
Projects

Work across structure, environment, and systems.

Selected work grouped by category labels. Each project keeps the same center: clarity, environment, and systems that support reflection and decision-making.
PMBaseline — slide 1 of 3
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Self-Regulation ProductMVP in DevelopmentNext.js + Supabase

/today → check-in → mode → next move → reflect → history

PMBaseline

A working MVP that helps people choose the right next move based on their actual state—not an idealized version of themselves. Built around a canonical loop of check-in, interpretation, right-sized action, and reflection.

What it demonstrates

  • Designing a self-regulation loop that connects state awareness, interpretation, action, and reflection
  • Building a working full-stack MVP with Next.js, Supabase, authentication, stored results, and history
  • Making human-centered product decisions by stabilizing the core non-AI loop before adding bounded AI
  • Translating a messy human problem into a structured product experience
MentorHub preview
Student Support PrototypeAmeriCorps-InspiredAI Support Layers

Mentor contact & support workflows

MentorHub

An AmeriCorps-inspired student-support prototype exploring how mentors and program staff could maintain better contact, organize learner needs, and use AI support layers to improve follow-through.

What it demonstrates

  • Student support and mentor follow-through workflows
  • Program operations and dashboard concepting
  • AI support layers for coaches and program staff
Open World Learning Lab / LOCUS preview
Education R&D VentureAdaptive Learning SystemsAI-Native Prototyping

World → inquiry → structured journey → evidence → reflection → continuity

Open World Learning Lab / LOCUS

An independent education R&D venture exploring how questions, places, projects, sources, and lived experience can become cumulative learning. Current work includes LOCUS Core and Journey Studio, with a working First Landing vertical slice and generalized creator/learner workflows.

What it demonstrates

  • Designing a learning-system architecture grounded in retrieval, scaffolding, reflection, transfer, and evidence
  • Translating a long-horizon education thesis into working learner and creator prototypes
  • Designing AI boundaries around learner agency, provenance, inspectability, and human judgment
  • Building place-based and open-world learning workflows across Creator, Learner, Orchestrator, and Reviewer roles
  • Using AI-native product development with explicit contracts, bounded model behavior, testing, and prototype honesty
Wine With Pete preview
Experience & Environment Design

Atmosphere, ritual, facilitation

Wine With Pete

A facilitation and experience-design project using gathering, ritual, and conversation to create environments for reflection and meaningful dialogue.

What it demonstrates

  • Designing learning through environment and atmosphere
  • Structuring open-ended experiences without over-controlling them
  • Using facilitation and context to shape engagement