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A college-wide community for everyone interested in AI, software, data, systems and the ideas shaping tomorrow.
A community for students across the college to explore AI, software, data, systems and emerging technology together.
Promote peer learning, practical AI engineering, career guidance, industry connections and accountable, faculty-guided project work.
A college-wide community where students from every branch and year learn together, build useful projects and grow into thoughtful technologists.
Learn by doing, share knowledge, include students at all skill levels, and work under faculty guidance.
The proposal lists three divisions: Technical, Events and Outreach & Marketing.
Two Chapter Heads and associates
Proposed: designs learning tracks and technical sessions, mentors project groups, reviews code and maintains shared notes and resources.
View membersTwo Chapter Heads and associates
Proposed: organises hackathons, workshops and competitions; coordinates speakers, venues, schedules, registrations and permissions.
View membersTwo Chapter Heads and associates
Proposed: manages social media and community communications, creates promotional materials, onboards members and promotes club activities.
View membersTalks, workshops and society sessions. Register directly on the CORTEX website.
Meet the people helping shape CORTEX and explore the interests they choose to share.
Featured: Manav TuliPresident
Technical articles, with questions and answers in the open.
A source-linked route from Git internals to agent architecture, with notes on measurement, safety and the limits of company-specific case studies.
Curated papers and engineering write-ups, linked to their original sources with our own summaries.
A technical guide to the parts that make up a coding agent, including its model, context, tools and control loop.
Why read it: Build a mental model of agent architecture before focusing on any one coding product.
Anthropic describes building Scion as its infrastructure needs changed. It reports about 2,500 code changes merged per day in May 2026 and more than 30,000 per day in September; this is a company-specific case study, not a general baseline.
Why read it: See how a team reasons about source control bottlenecks when its workload changes sharply.
Anthropic reports that its typical engineer merged 8× as much code per day in Q2 2026 as in 2024. The article cautions that lines of code measure quantity, not quality, so the figure is not a direct measure of productivity.
Why read it: A first-party account of how AI changes engineering work, with an explicit discussion of what its productivity measure can and cannot show.
Prerequisites: Basic familiarity with software engineering workflows.
Ordered stages, curated materials and personal progress tracking. Free to read; sign in to track your own progress.
A self-paced, source-linked path from Git internals to AI coding agents, ending with an optional read-only repository assistant challenge. Reading time is an estimate; one linked article is subscriber content.
Member-proposed problems, reviewed by the society. Express interest, form a team and ship something real.
Create a small assistant that answers questions about a public or synthetic Git repository and cites the exact file paths and line ranges behind each answer. A team can divide the work across research, interface design,…
CORTEX is a college-wide community for students interested in AI, software, data and technology. Students from every branch are welcome to learn; Community membership is a separate selective pathway with auditions. Prior technical experience is not required.