Vision
Vision
The Runnable Paper Needs an Identity Report
Paper2Agent, published in Nature in September, turns research papers into AI agents you can run. Hand over your data and the method executes, with no rebuilding it from prose. The authors want papers to carry an "agent availability" section saying whether a runnable version exists.
A PDF never had to promise anything like that. A running method has versions, can drift from what was published, and goes offline. Right now, Paper2Agent's tests decide what counts as the same method. Museums that conserve software-based art have been arguing about that, and about endings, for decades.
The Runnable Paper Needs an Identity Report
Paper2Agent, published in Nature in September, turns research papers into AI agents you can run. Hand over your data and the method executes, with no rebuilding it from prose. The authors want papers to carry an "agent availability" section saying whether a runnable version exists.
A PDF never had to promise anything like that. A running method has versions, can drift from what was published, and goes offline. Right now, Paper2Agent's tests decide what counts as the same method. Museums that conserve software-based art have been arguing about that, and about endings, for decades.
Paired Features
What It Would Take for an Agent to Be Yours
Since 1998, when a web page and its reader disagree about fonts, the browser has sided with the reader. On October 22, the W3C wrote that allegiance down for AI agents: a user agent serves its user over its maker and over everyone else. You could check a browser by watching the screen. An agent earns its keep because you aren't watching. So if it switched sides, where would you look to find out?
The Interviewer Worked for the Firm
A job-interview bot owes the applicant none of the loyalty the W3C asks of user agents. The employer buys it and writes its questions. Yet in a new, not-yet-reviewed experiment covering about 67,000 call-center applications in the Philippines, applicants interviewed by the AI got more offers, started more often and stayed longer. The reason lies in what recruiters got to know, and it suggests a test for any go-between a firm deploys.
In Conversation With a Game Master Who Told Her AI Never to Pull Punches
CONTINUE READINGShort Take
The PROBE study set ten AI coding agents loose on twenty open-source projects. It compared their bug reports with the 2,457 bugs the projects' volunteer maintainers fixed over eighteen months. Reviewers judged 85% of the agents' reports to be real bugs. Even so, the best agent caught only about a fifth of what maintainers fixed, and the agents' findings resembled one another more than they resembled the humans'.
Maintainers' choices are lopsided because their users are. Someone complained, or a feature visibly broke. That lopsidedness tells you who depends on the software. As agent reports fill the same queues, one shared machine sense of what's worth fixing could outweigh it simply by arriving in greater volume.
Further Reading
