Less noise.
Better questions.
Agentic AI is advancing faster than anyone can read. AGENTHESIS is an independent, open-source learning journal for those who want to understand how research works, which claims hold up, and where ideas connect—not merely collect headlines.
Follow the question
Start with a concrete problem, and explain the intuition before assuming readers know the terminology.
Read the experiment
Describe what was actually held constant: model, harness, tasks, budget, compute, metrics, and test conditions.
Separate fact from interpretation
Distinguish author-reported findings from our analysis, and give limitations room to change the conclusion.
Link the source
Every research note links directly to the primary paper, so readers can inspect the claims themselves.
Learn across boundaries
Prioritize agentic AI. Include broader AI and computer science only where the ideas offer unusual insight.
Correct openly
Research understanding evolves. Corrections and counterevidence belong in public version history, not behind closed doors.
Every idea can be challenged.
Research findings here are educational syntheses, not peer review or independent replication. Suggest a correction, discuss a paper, or contribute a new reading through the public repository.