Full-stack product development
Python services, a custom web interface, persistent data, and native app surfaces, developed together around actual workflows.
A personal platform for learning, research, and putting ideas to work.
well.education connects study tools, source-linked reporting, and AI orchestration in one workspace. A project built through the work of using it, questioning it, and making it better.
Explore the projectThe interesting part starts after you have the information.
You still have to make sense of it. Find the connection. Practice the difficult part. Decide what deserves your attention and turn a decision into work you can follow.
Originally called Brain, this project began as a way to coordinate AI agents across software projects. It has grown into a personal environment for studying, reading, researching, and building, with shared infrastructure underneath.
well.education is its public identity: a place to see the system, understand its design, and follow the thinking behind the work.
Learning systems / Research workflows / Knowledge connections / Agent orchestration
Different tools. A common thread:
make the work easier to understand.
Course guides, question banks, and review tools bring the material and the work of learning it into the same place. Learn mode gives immediate feedback; saved attempts make it possible to revisit where understanding broke down.
Implemented across LSAT preparation, Spanish, and university coursework, with concept-level review and authored study materials.
Explore the learning systemNews Unfiltered brings source-linked reporting into a deliberate reading experience. The pipeline separates collection, editorial preparation, and publication, with original sources kept close to the resulting summaries.
AI-assisted writing is subject to editorial checks. Reporting, interpretation, and uncertainty remain distinct so readers can inspect the basis of a claim.
Read News UnfilteredThe world, read from
more than one side.
The Neural workspace organizes entities, relationships, notes, and evidence into explorable maps. A relationship is more useful when you can see where it came from and return to the supporting material.
Graph views, entity profiles, and evidence records give research a structure that can be revisited as new information arrives.
Explore the knowledge architectureProjects define where work happens. Agents define how it runs. Tasks carry the instructions, and streamed events show what happened along the way.
The web control plane and local worker divide coordination from execution. Task records, live logs, cancellation, and recorded outcomes make long-running work inspectable.
Explore the orchestration modelThe interface is only the visible part. Behind it are task queues, persistent state, model runtimes, and a clear separation between public work and private activity.
Study · research · knowledge · projects
FastAPI · SQLite · task state · event streams
Project-aware execution, local inference,
and service integrations.
Attempts, notes, evidence, task outcomes,
and published artifacts.
A project like this is an exercise in connecting systems and taking responsibility for what happens between them.
Read the project case studyPython services, a custom web interface, persistent data, and native app surfaces, developed together around actual workflows.
Agent execution, local model runtimes, streaming responses, and tool access connected to the surrounding application.
Source attribution, saved learning attempts, and inspectable run histories make the output something you can return to and question.
Deployments, authentication, worker boundaries, and regression checks are part of the product’s design and ongoing maintenance.
Explore the work. Follow the reasoning.
Start a conversation about what comes next.