The ai literacy course just teaches distrust. an nsf-funded project called openseccoder, out oct 3,…
the ai literacy course just teaches distrust. an nsf-funded project called openseccoder, out oct 3, trains students to spot security flaws in ai-generated code with eight hands-on labs.
the first skill taught is now verification.
Context
Verified dates: UT San Antonio announced the project on Sep 23, 2026 (UTSA News). Nishant Vishwamitra leads a $500,000 National Science Foundation project; OpenSecCoder is a free online learning platform where students practice finding and fixing security problems in AI-generated code, and the project will also develop eight hands-on labs, three course modules and annual workshops.
AFCEA's Signal Media covered it on Oct 2, 2026, and a Basil Puglisi analysis (Oct 3) places it among three AI literacy products, citing the Sep 23 announcement.
The NSF funding, OpenSecCoder and the eight hands-on labs match UTSA. The announcement date is Sep 23, not Oct 3; Oct 2 and Oct 3 are the coverage dates. The labs are described as planned deliverables of the project, so the post's present tense is not confirmed. 'The first skill taught is now verification' is the author's opinion, in line with the project's stated aim of spotting security flaws in AI-generated code.
Related work
- Texas Public Radio: new funding supports AI safety research and training at UT San Antonio ↗Sep 27, 2026.
- George Mason University: a hands-on curriculum for handling AI ↗Sep 21, 2026; another NSF-funded agentic AI security education project.
- T-SPAN: new funding supports AI safety research and training at UT San Antonio ↗Sep 27, 2026.
Watch next
- Check whether the eight labs are released yet on the OpenSecCoder platform.
Sources
Provenance
The note above is reproduced unedited from the original post, first published on Threads on 11 October 2026 at 17:32 IST. Sources are the papers and datasets the note draws on.
View the original post ↗Embed this note
More notes
The air is now being asked to keep its own ledger
the air is now being asked to keep its own ledger: ecmwf’s aifs compo becomes the first ai model to forecast atmospheric composition globally every three hours, cleanair simulates 365 days of pm2.5 over china in ten seconds, and a unified framework maps six pollutants at one kilometer across the whole country. the air now files its own composition report.
read the note →The current is now being asked to draw its own map
the current is now being asked to draw its own map: china’s langya 2.0 predicts six ocean phenomena including internal waves and mesoscale eddies, a deep net called wenhai resolves eddies globally with air sea flux formulas built in, and scripps infers surface currents from the way temperature patterns deform in satellite images. the ocean now files its own circulation report.
read the note →The soil is now being asked to report its own carbon
the soil is now being asked to report its own carbon: a nix color sensor paired with generative data augmentation predicts soil organic carbon without a lab, random forest drives 74 percent of soil health mapping studies, and sentinel 2 tracks five year carbon change across france and italy from 922 samples. the dirt now files its own carbon account.
read the note →