CTI is a statewide initiative to bring together tech companies, nonprofits and institutions of higher ed to design, develop, implement, and test programming, materials, pathways, and supports to prepare computer science students, particularly students from low-income, first-generation, URM backgrounds, to be competitive for opportunities in and to make significant contributions to the tech industry. CTI operates as an institute within CSU Monterey Bay and is supported by $10M in funding from the 2021 CA state budget.
External link for Computing Talent Initiative
Seaside, CA 93955, US
Computing Talent Initiative reposted this
I recently wrapped up my Micro-Internship with CodeDay & Computing Talent Initiative! During the program, I contributed to Dagster and built a new feature for Dagster+ users. I wrote a blog post sharing the problem, challenges, and implementation details. Check it out here.
A reflection from our team's Leslie Maxwell: As our team thinks about how to prepare students in this world of AI, we also are using AI a ton ourselves. It's a fascinating journey and I find myself experiencing a wide variety of emotions over the course of a day. Some of them are the more obvious ones — awe, amazement, frustration. Others are subtler. Fleeting thoughts that I really have to be paying attention to recognize. So, here are some of the nuanced feelings I notice: - Guilt. I often find myself compelled to say to my colleagues, "This is something Claude and I worked on." Even when I know I did the yeoman's work on it, I still wonder if I get to call it mine. It's a new kind of authorship that doesn't have a name yet. - Vulnerability. In human conversations, we tend to manage how we're perceived. We hedge. We sometimes imply we know more than we do. That instinct doesn't work well with AI. Being open and honest - asking the "dumb" questions, explicitly responding with "I don't know what that means, Claude" - makes the partnership dramatically better. That's ultimately freeing, but it took me a moment to get there. - Exposure. I can produce things faster now. That sounds like a pure win, but work that used to take weeks, with feedback gathered from my team along the way, can now be done in an afternoon. Sharing something that big feels more exposed. Like I'm offering more of myself at one time to their judgement. - Disorientation. Where I add value is shifting. Throughout most of my career, I've been tapped into for writing. Some of what I used to bring, AI brings now too. It doesn't mean I have nothing to offer, just that what I offer is shifting. My colleague, a software engineer with 20 years of experience, described going through a period of mourning. The thing he'd spent his career mastering is different now. I understood exactly what he meant. If I - a 45-year-old woman who is reasonably confident about herself as a professional - am grappling with these feelings, our students almost certainly are too. And unlike me, they may not have the experience or self-awareness to recognize what bubbles up, let alone navigate it. To that end, as we think about how to teach students to think with AI, we can’t lose sight of the need to help them navigate what it stirs up.
What makes human contribution valuable when AI can execute across every domain? One answer that keeps bubbling up: knowing which problem is actually worth solving. But how do you teach that? The traditional education model has the instructor define the problem and students learn to solve it — or more often, implement an already-identified solution. Whether it's the right problem rarely gets explored. With AI handling more of the implementation work, knowing how to find and frame the right problem becomes an increasingly important human contribution. So how do we shift from teaching students to implement solutions to helping them identify and define problems in the first place? Last week we ran one experiment. We wanted students to find a real problem in their own lives to eventually solve with AI. They were struggling, so we thought peer conversation might help. The catch: open-ended peer conversations often go nowhere — students don't know what to ask each other. So we built a simple AI-facilitated tool to give those conversations direction. Students paired up to explore each other's problem statements. The tool surfaced questions to expose hidden assumptions and push students to consider whether they were solving the right problem at all. Students chose when to click for guidance and when to keep going. The conversation stayed human-to-human throughout. Conversations that typically end in a few minutes often went 30+ minutes. More students than usual came back noticeably energized. Small sample, anecdotal — but a signal worth noting. The doubt we're sitting with: right now, students click for AI-generated follow-up questions when they get stuck. Through enough guided practice, will they learn to ask those questions themselves, or will they always need the prompt? (Our last post is linked in the comments.)
Is it possible, even likely, that with AI what people need to learn has fundamentally changed? Educators who are enthusiastic about AI are using it - but mostly to make existing courses better. We may be missing a bigger, more foundational question. The question isn't "what should CS teach now" or "how should business schools adapt." Those discipline-by-discipline answers seem to miss the point. We need to be thinking about, when AI can execute across every domain, what makes human contribution valuable? For 15 years, the Computing Talent Initiative team has designed and implemented programs connecting students from 60+ community colleges and regional publics to tech careers—learning as much from what didn't work as what did. Now, we're redesigning everything around two questions that students must answer with evidence: - What problems are now within my reach that I wouldn't have attempted before? - What would be worse about my solutions if I'd simply handed them to AI? Expanded capability + human value. We think you need both. And if discipline-specific responses are grounded in this understanding, they're more likely to be durable as AI keeps advancing. We don't have it figured out. We have bets we're testing and doubts we're sitting with. We plan to share both here, and would love to hear what others are trying.
Computing Talent Initiative reposted this
My First Open-Source Contribution! 🎉 In November 2025, I made my very first open-source contribution, and it has been an incredibly rewarding experience. Through CTI – CodeDay Open Source Experience, I had the opportunity to contribute to the Open Energy Dashboard (OED) project while working alongside three amazing teammates and under the guidance of a supportive mentor. Our task focused on building and validating a test case that ensured accurate temperature unit conversions (Celsius ↔ Fahrenheit) and correct aggregation of 15-minute interval data into daily minimum and maximum values. Beyond the technical challenge, this experience gave me a real look into how data flows through a production-level codebase. I learned how to navigate design documents, trace helper functions across files, and truly understand existing systems instead of treating them as a black box. This milestone wouldn’t have been possible without the people who made it such a positive learning journey. Huge thanks to our mentor, Al D., for the mentorship and guidance, Computing Talent Initiative and CodeDay for creating this opportunity, and my three teammates (Tam Khanh Tran Pham, Wei Li, and Alngdi Mohsen) for their collaboration, support, and encouragement. Grateful for the learning, the community, and the confidence boost that came with my first open-source contribution! If you’d like to learn more about this experience and what I gained from it, I wrote an article sharing the full journey here 👇
Computing Talent Initiative reposted this
My First Open-Source Contribution 🎉 In November 2025, I completed my first open-source contribution, marking an important milestone in my learning journey. Through the CTI – CodeDay Open Source Experience, I had the opportunity to contribute to the Open Energy Dashboard (OED) project, where my team and I worked on improving automated testing for energy unit conversions. This experience allowed me to collaborate closely with my teammates Anthony Duenez Ramirez, Princeton Nguyen, and Nathan Espina, while receiving valuable guidance from our mentor, Daniel Bachhuber. Working within a real-world open-source codebase helped me better understand how large systems are structured, how testing ensures data accuracy, and how teamwork plays a critical role in successful software development. I am deeply grateful to Computing Talent Initiative and CodeDay for creating an environment that supports learning through hands-on contribution, as well as to our mentor and teammates for their constant support and encouragement. This project not only strengthened my technical skills but also boosted my confidence as a contributor to open-source software. If you’re interested in learning more about the technical challenges we tackled and what I gained from this experience, I wrote a detailed article sharing the full journey below. 👇
Computing Talent Initiative reposted this
I’m happy to share my experience working on my first open-source contribution to keyshade.io as part of the CTI x CodeDay micro-internship! During this program, my team and I focused on adding readable metrics to track daily usage. Using NestJS and TypeScript, we collect usage data in Redis cache throughout the day, then a cron job runs at midnight to save it to the database and clean up the cache. I’m grateful to my teammates Leonardo Garcia and Danny Abraham for the hard work and great collaboration. A special thank you to our mentor Ramiz Rahman for the invaluable guidance and to Computing Talent Initiative and CodeDay for this amazing opportunity.
Computing Talent Initiative reposted this
During the month of October, as part of the micro-internship provided by CodeDay and Computing Talent Initiative, I had the opportunity to contribute to an open-source project called Open Energy Dashboard, a web application designed for companies to monitor energy usage and sustainability. The attached blog below showcases the journey my team and I went through in implementing test cast CG17. Thank you again to CodeDay and Computing Talent Initiative for this open-source experience. #opensource #OpenEnergyDashboard #computingtalentinitiative #CTI #CodeDay
Computing Talent Initiative reposted this
𝗜'𝗺 [𝗶𝗻]! I’m thrilled to share that I’ll be joining LinkedIn as a Software Engineering Intern in Mountain View next summer! As AI continues to reshape the hiring landscape, I’m grateful for the chance to learn from the [𝗜𝗻] family and contribute to how we can best support and empower the global workforce through this evolving era. Looking back at the interview prep process, when I expected it to be 𝘰𝘷𝘦𝘳𝘸𝘩𝘦𝘭𝘮𝘪𝘯𝘨, I was surprisingly greeted by 𝘤𝘭𝘢𝘳𝘪𝘵𝘺, 𝘣𝘢𝘭𝘢𝘯𝘤𝘦, 𝘢𝘯𝘥 𝘢 𝘥𝘦𝘦𝘱 𝘴𝘦𝘯𝘴𝘦 𝘰𝘧 𝘱𝘶𝘳𝘱𝘰𝘴𝘦. Preparing for a company I truly admire helped me push through technical interview prep, rediscover the joy of problem-solving in Leetcode, reflect on my past experiences and assess how I’ve grown as into who I am today. Most importantly, I was surrounded by incredibly supportive people who made the journey meaningful. I’d like to extend my sincere gratitude to my recruiter Tamara Enriquez-Martone, for introducing this opportunity and guiding me along the way. And to the Minerva community, thank you to Shaghayegh M. Mohanad Abdelhakem Priscilla Boakye Temilola Olowolayemo Jonathan Powers, Ph.D. for your kindness, generosity, and time which have helped me tremendously in navigating the interview process. A huge thank you to Computing Talent Initiative, for the open-source projects I’ve been part of, and the amazing teams I worked with who strengthened my confidence and shaped how I think about engineering and teamwork. And thank you to all the friends who brought so much light and laughter despite this stressful time. I feel truly lucky to be surrounded by people who show that the hardest things become easier when you’re with the right people. I’m beyond excited to join LinkedIn this summer, learn from inspiring people, and keep growing. 💙 And to anyone currently on their own journey, I hope the right opportunity finds you soon! #LinkedIn #LinkedInLife #LinkedInterns
Computing Talent Initiative reposted this
October was a very eventful month for me. I wanted to announce that I just completed my first Micro-Internship! It has been a rollercoaster of emotions. And just like with roller coasters, I feel confident afterwards and want to go again. The only thing still bewildering to me is having made a PR for a new feature to the p5.js Web Editor, a website with ~200K monthly users! I wouldn't have imagined myself doing so when I started coding last year. This was my first real deep dive into an unfamiliar codebase. I learned so much! Specifically, how to: - Trace data flow through multiple modules - Design an extensible API with future contributors in mind - Work around Prettier's rules (the real boss fight 😭 ) Special thanks to Computing Talent Initiative and CodeDay for this opportunity. It was a blast and I can't wait to continue contributing to open source projects! For more details about my journey in implementing the feature, read my blog post. PR Link: https://lnkd.in/eEZzfHqF