BRICS AI Economics

Feb, 21 2026

Constrained Decoding for LLMs: How JSON, Regex, and Schema Control Improve Output Reliability

Emily Fies

Constrained decoding ensures large language models generate valid JSON, regex-matching, and schema-compliant outputs by blocking invalid tokens during generation. It reduces errors to near zero but slows generation slightly and works best with smaller models.

Feb, 20 2026

Security Vulnerabilities and Risk Management in AI-Generated Code

Emily Fies

AI-generated code is now writing half of all software, but it’s introducing critical security flaws like SQL injection, hardcoded credentials, and XSS. Learn how to detect and prevent these risks before they breach your systems.

Feb, 18 2026

Vibe Coding for Operations Teams: Automate Workflows and Build Internal Dashboards with AI

Emily Fies

Vibe coding lets operations teams build automations and dashboards using plain English instead of complex tools. AI writes the code, deploys it, and keeps it running-no developer needed.

Feb, 17 2026

Prompt Chaining for Multi-File Refactors in Version-Controlled Repositories

Emily Fies

Prompt chaining turns complex multi-file code refactors into safe, step-by-step workflows. Learn how to use it with LangChain, Autogen, and version control to cut errors by 70% and save weeks of manual work.

Feb, 14 2026

Liability Considerations for Generative AI: Vendor, User, and Platform Responsibilities

Emily Fies

In 2026, liability for generative AI is no longer theoretical. Vendors, platforms, and users all face legal risks when AI generates harmful, false, or infringing content. Learn how state laws and court rulings are reshaping responsibility.

Feb, 13 2026

Video Understanding with Generative AI: Captioning, Summaries, and Scene Analysis

Emily Fies

Generative AI now understands video like never before - generating captions, summaries, and scene analysis with 89%+ accuracy. Learn how it works, where it fails, and who’s using it in 2026.

Feb, 11 2026

Generative AI in Business Operations: High-Impact Use Cases and Implementation Patterns

Emily Fies

Generative AI is transforming business operations by automating complex tasks like customer service, document generation, and supply chain planning. Learn the top use cases, implementation patterns, and real-world results from companies like BMW, Commerzbank, and Citi.

Feb, 6 2026

Secure Authentication Patterns for Vibe-Coded Backends: Avoid Common AI Security Pitfalls

Emily Fies

Learn how to secure backend systems built with AI tools like GitHub Copilot. Discover common vulnerabilities in vibe-coded auth code and proven patterns for OAuth, JWT, RBAC, and more. Avoid 63% more authorization bypass risks with expert tips and real-world examples.

Feb, 5 2026

Open-Source LLM Licensing: What You Must Know to Avoid Legal Risks

Emily Fies

Understanding legal and licensing requirements for open-source LLMs is crucial to avoid costly lawsuits. This guide covers common licenses, compliance steps, real-world risks, and how to navigate them safely.

Feb, 4 2026

Stepwise Prompting with Feedback Loops: A Practical Guide to Iterative Code Generation

Emily Fies

Stepwise prompting with feedback loops helps developers generate accurate code by breaking tasks into smaller steps and validating each part. Learn how this method reduces errors by 63% and integrates with tools like GitHub Copilot. Practical examples and best practices included.

Feb, 3 2026

Version Control with AI: Managing AI-Generated Commits and Diffs

Emily Fies

As of 2026, managing AI-generated commits and diffs requires new workflows. Teams using AI without version control adjustments face higher errors, security risks, and technical debt. Learn how to audit, review, and track AI code properly with Git and modern tools.

Feb, 2 2026

How Curriculum and Data Mixtures Speed Up Large Language Model Scaling

Emily Fies

Smart data ordering and mixtures can boost LLM performance by up to 15% without larger models. Learn how curriculum learning works, what mixtures to use, and whether it’s worth the effort for your team.

BRICS AI Economics

Constrained Decoding for LLMs: How JSON, Regex, and Schema Control Improve Output Reliability

Security Vulnerabilities and Risk Management in AI-Generated Code

Vibe Coding for Operations Teams: Automate Workflows and Build Internal Dashboards with AI

Prompt Chaining for Multi-File Refactors in Version-Controlled Repositories

Liability Considerations for Generative AI: Vendor, User, and Platform Responsibilities

Video Understanding with Generative AI: Captioning, Summaries, and Scene Analysis

Generative AI in Business Operations: High-Impact Use Cases and Implementation Patterns

Secure Authentication Patterns for Vibe-Coded Backends: Avoid Common AI Security Pitfalls

Open-Source LLM Licensing: What You Must Know to Avoid Legal Risks

Stepwise Prompting with Feedback Loops: A Practical Guide to Iterative Code Generation

Version Control with AI: Managing AI-Generated Commits and Diffs

How Curriculum and Data Mixtures Speed Up Large Language Model Scaling

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Latest Courses

Vibe Coding for Operations Teams: Automate Workflows and Build Internal Dashboards with AI

Security Vulnerabilities and Risk Management in AI-Generated Code

Measuring Data Quality for LLM Training: Model-Based and Heuristic Filters

Open-Source LLM Licensing: What You Must Know to Avoid Legal Risks

Video Understanding with Generative AI: Captioning, Summaries, and Scene Analysis

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