SCC Comets

Tess Rempel Feb, 22 2026 Artificial Intelligence

Proof-of-Concept Machine Learning Apps Built with Vibe Coding

Vibe coding lets anyone build machine learning apps in hours, not weeks. No coding experience needed. Learn how real people are using AI tools like Cursor and Lovable to create functional prototypes - and what you need to know to avoid the pitfalls.

Tess Rempel Feb, 21 2026 Artificial Intelligence

Data Classification Rules for Vibe Coding Inputs and Outputs

Data classification in vibe coding ensures AI-generated code handles sensitive data safely. Without clear rules for Critical, High, Medium, and Low data, companies risk leaks of PII, API keys, and service credentials. Learn how to enforce security at every step.

Tess Rempel Feb, 20 2026 Artificial Intelligence

Talent Markets in the Vibe Coding Era: Skills Employers Actually Reward

In the vibe coding era, employers reward developers who think like conductors, not typists. Learn the top five skills that actually get you hired - and what’s fading fast in AI-assisted development by 2026.

Tess Rempel Feb, 19 2026 Artificial Intelligence

Y Combinator Startups and Vibe Coding: What 91% AI-Generated Codebases Really Mean

Y Combinator's Winter 2025 startups showed 91% AI-generated codebases using vibe coding-a trend that’s fast, risky, and unsustainable without human oversight. Here’s what actually works-and what’s about to break.

Tess Rempel Feb, 18 2026 Artificial Intelligence

Architectural Considerations and Technical Decision-Making in AI-Assisted Development

AI is transforming how architects and developers make critical design decisions, from optimizing building layouts to detecting software antipatterns. Learn how generative design, BIM integration, and parametric modeling are reshaping both physical and digital architecture.

Tess Rempel Feb, 17 2026 Software Architecture

How to Build a Coding Center of Excellence: Charter, Staffing, and Real Goals

A Coding Center of Excellence isn’t about enforcing rules - it’s about giving teams tools, templates, and consistency to ship faster and break less. Learn how to build one with the right charter, staffing, and measurable goals.

Tess Rempel Feb, 16 2026 Artificial Intelligence

Measuring Code Quality in AI-Heavy Repos: Beyond Lines of Code

Traditional code quality metrics like lines of code are broken in AI-heavy repos. Learn what actually matters: code churn, review depth, and developer experience.

Tess Rempel Feb, 15 2026 Artificial Intelligence

Practical Applications of Generative AI Across Industries and Business Functions in 2025

Generative AI is transforming healthcare, finance, manufacturing, and customer service in 2025 with real-world results-cutting costs, speeding up workflows, and improving accuracy. Learn how top companies are using it-and where it still falls short.

Tess Rempel Feb, 14 2026 Software Architecture

Team Size Compression: How Smaller Teams Deliver More Without Burning Out

Smaller teams can deliver more by cutting waste, not people. Learn how compressing your team to 60% of its size boosts speed, reduces burnout, and unlocks real productivity.

Tess Rempel Feb, 13 2026 Artificial Intelligence

Evaluating Internal Deliberation Costs in Reasoning Large Language Models

Reasoning large language models deliver superior accuracy on complex tasks-but at a steep computational cost. Learn how deliberation expenses stack up, where they pay off, and how top companies are cutting waste without losing performance.

Tess Rempel Feb, 12 2026 Artificial Intelligence

Prompt Costs in Generative AI: How to Reduce Tokens Without Losing Context

Learn how to cut generative AI prompt costs by reducing tokens without losing quality. Real strategies, real savings, and what works today-based on enterprise data from 2024.

Tess Rempel Feb, 10 2026 Artificial Intelligence

How Prompt Templates Reduce Waste in Large Language Model Usage

Prompt templates cut LLM waste by 65-85% by reducing token usage, energy consumption, and processing time. Learn how structured inputs save money, improve accuracy, and lower carbon emissions in AI workflows.