# Research

Canonical page: https://antern.co/research/

## Summary

Teaching without research becomes repetition.

AI changes too quickly for static slides. Antern research combines first principles, historical context, academic papers, industry validation, open-source implementations, production constraints, experiments, and feedback from real users and businesses.

The research principle is: research keeps teaching alive.

## Research Stack

The curriculum is updated from multiple kinds of evidence:

- Observe reality
- Study history
- Read papers
- Build systems

Research starts with what is breaking in the real world: participants, companies, agents, hiring, deployment, cost, latency, and user behavior.

## Research Flywheel

Research becomes curriculum only after it survives the loop:

1. Observe reality
2. Study history
3. Read research
4. Build
5. Test
6. Teach
7. Revise

The loop turns raw information into teaching: observe reality, study history, read research, build systems, test assumptions, teach, and revise.

## Paper Club

Participants are trained to read papers critically, not reverently.

Paper reading is not a prestige ritual. It is a way to learn research taste: what mattered, what failed, what changed, and what can be rebuilt.

Paper Club follows this pattern:

- Read
- Critique
- Reproduce
- Present

## Evidence Sources

Research includes papers, code, failures, and real workflows.

Evidence sources include foundational research papers, survey papers, open-source implementations, engineering blogs, benchmarks and eval reports, production incidents, participant build failures, and enterprise workflow constraints.

## What We Avoid

Research-driven teaching is the opposite of recycling.

Antern avoids stale slides, treating papers as scripture, teaching tools without constraints, ignoring production failures, chasing hype without understanding what changed, and confusing confident AI output with research judgment.