AI Layer
Research Intelligence Stack
A record of the models and tools that sit inside the research workflow and what each one is actually used for. It changes as the work changes.
Primary synthesis engine — literature analysis, research drafts, code architecture, and complex reasoning across all active projects
claude.ai↗In-editor code assistance across the full platform build — component generation, refactoring, and API design
github.com↗Early-stage drafting, ideation, and structured reasoning for complex research problems and communication frameworks
chatgpt.com↗Citation extraction, systematic literature review, and deep research grounding across academic sources and primary documents
elicit.com↗Primary citation and reference library across all research projects — annotation, bibliography generation, and source tracking
zotero.org↗Real-time social media data curation, event monitoring, and field-level signal extraction for active research interventions
grok.com↗The pattern here is: model does the repetitive or computationally intensive part — surface a source, draft a synthesis, generate a code block — and a human decides whether the output holds up, what it means, and whether it goes anywhere. No finding published on this platform leaves AI as the last checkpoint.
This stack is updated as the workflow evolves. Lab AI tools — tools built in-house — are documented separately.