borderless / FIELD_NOTES.md
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Document the demo flow, field notes, and trace sharing process.
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# Borderless Field Notes
## Why This Exists
Immigration research is high-stakes, fragmented, and exhausting. A person trying
to move for work, study, family, or safety often has to compare government pages,
embassy notes, point calculators, processing-time pages, blogs, and anecdotes.
Borderless is built for the moment before someone pays a lawyer: "What countries
are realistically worth researching for my profile?"
## Why A Small Model Fits
The hard part is not memorizing every immigration rule. Policies change too
often. A small model works well when it is used as a planner and synthesizer:
- It turns an everyday-language profile into a concrete research plan.
- It calls search and scraping tools for current official sources.
- It compares tradeoffs in plain language.
- It drives the globe so geography is part of the reasoning, not decoration.
This is a better fit than a larger model guessing from stale training data.
## What Changed After Prototype Testing
The first prototype was a pure chat with visible tool JSON and an editable system
prompt. It worked, but a new user had to know what to ask and judges had to read
through debugging details.
The award-ready version adds:
- A guided intake form that creates a complete research prompt.
- Demo personas for quick evaluation.
- A stricter research protocol focused on official sources.
- Source-quality labels in search results.
- Country-profile metadata for shortlist and globe grounding.
- Friendlier tool traces that explain progress without raw JSON noise.
- Globe loading and empty states so the visual panel is useful immediately.
- Local JSONL trace logging that can be shared as hackathon evidence.
## Responsible Use
Borderless is research support, not legal advice. The agent is instructed to cite
official sources for eligibility, documents, fees, timelines, and application
steps. When official data is missing or a tool fails, the answer should say what
needs verification instead of inventing details.
## Hackathon Award Fit
- Backyard AI: a practical tool for a real, specific life decision.
- Best Agent: multi-step tool use, source quality, partial synthesis, and globe
updates are all model-driven.
- Best Demo: the guided form plus globe shortlist creates an immediate visual
story.
- Sharing is Caring: JSONL traces can be published with the Space or linked in a
writeup.
- Field Notes: this report documents the product choices and constraints.