SCC Comets

Tess Rempel Mar, 6 2026 Artificial Intelligence

Token Budgets and Quotas: How to Stop LLM Cost Overruns Before They Happen

Token budgets and quotas are the only way to prevent runaway LLM costs. Learn how to set limits on token usage, apply graduated throttling, and avoid expensive mistakes before they happen.

Tess Rempel Mar, 5 2026 Artificial Intelligence

How Large Language Models Use Probabilities to Choose Words and Phrases

Large language models generate text by calculating the probability of each next word based on patterns learned from massive datasets. This article explains how they use probabilities, decoding strategies like top-p and temperature, and why they sometimes make mistakes - even when they sound convincing.

Tess Rempel Mar, 4 2026 Artificial Intelligence

How to Set Realistic Expectations for Vibe Coding on Enterprise Projects

Vibe coding isn't magic - it's a new way to build software using AI as a proactive team member. Learn how to set realistic expectations, write clear specs, and avoid common enterprise pitfalls that derail adoption.

Tess Rempel Mar, 3 2026 Artificial Intelligence

Why Tokenization Still Matters in the Age of Large Language Models

Tokenization remains critical in the age of large language models, impacting cost, accuracy, and efficiency. Learn why subword tokenization, vocabulary size, and domain-specific tuning still make or break LLM performance.

Tess Rempel Mar, 2 2026 Artificial Intelligence

Continuous Improvement Loops: How Feedback, Retraining, and Prompt Updates Keep AI Models Accurate

Continuous improvement loops keep AI models accurate by using real-world feedback, automated retraining, and prompt updates. Without them, models degrade quickly. Here’s how to build one that actually works.

Tess Rempel Mar, 1 2026 Artificial Intelligence

Abstention Policies for Generative AI: When the Model Should Say It Does Not Know

Generative AI often invents answers instead of admitting ignorance. Learn how abstention policies teach models to say 'I don't know'-and why that’s the key to trustworthy AI.

Tess Rempel Feb, 28 2026 Artificial Intelligence

Teaching with Vibe Coding: Learn Software Architecture by Inspecting AI-Generated Code

Learn software architecture by inspecting AI-generated code instead of writing it first. Vibe coding flips traditional programming education, helping students understand system design before syntax. Used by Google, Amazon, and top bootcamps.

Tess Rempel Feb, 27 2026 Artificial Intelligence

Data Collection and Cleaning for Large Language Model Pretraining at Web Scale

Training large language models requires cleaning hundreds of terabytes of web data. Discover how top teams filter, deduplicate, and curate data to boost performance - and why quality matters more than quantity.

Tess Rempel Feb, 26 2026 Artificial Intelligence

Media and Publishing with Generative AI: Headline Variants and Editorial Tools

Generative AI is transforming headlines and editorial workflows in media publishing by 2026, but success depends on human oversight, trust-based metrics, and fair compensation for content creators.

Tess Rempel Feb, 24 2026 Artificial Intelligence

Change Management for Vibe Coding: Training, Tools, and Incentives

Vibe coding transforms software development by replacing traditional coding with AI-driven conversation. This article breaks down the training, tools, and incentives needed to make it work in real teams - not just as a hack, but as a sustainable practice.

Tess Rempel Feb, 23 2026 Artificial Intelligence

Grounded Web Browsing for LLM Agents: How Search and Source Handling Power Real-World AI Tasks

Grounded web browsing lets AI agents search live websites to answer questions accurately. It's transforming customer support, e-commerce, and research by replacing guesswork with verified, real-time data.

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.