BRICS AI Economics

Mar, 22 2026

Autoscaling Large Language Model Services: Policies, Signals, and Costs

Emily Fies

Autoscaling LLM services requires specialized metrics like prefill queue size and slots_used - not CPU or GPU usage. Learn how to reduce costs by 30-60% while keeping latency low, and avoid the pitfalls that waste millions in cloud spend.

Mar, 20 2026

How Prompt Templates Reduce Waste in Large Language Model Usage

Emily Fies

Prompt templates cut LLM waste by 65-85% by reducing token use, energy, and processing time. Learn how structured prompts save money, lower emissions, and improve output - without changing your model.

Mar, 19 2026

Cost Savings from Compression: How LLM Efficiency Drives Real Business Value

Emily Fies

LLM compression cuts infrastructure costs by up to 80% through quantization, pruning, distillation, and prompt compression. Real companies are saving millions - here’s how to build your business case.

Mar, 18 2026

Versioning Contracts in Vibe-Coded APIs: Preventing Breaking Changes

Emily Fies

Learn how versioning contracts in Vibe-coded APIs prevent breaking changes using semantic versioning, automated OpenAPI specs, and a strict deprecation policy. A practical guide for teams building reliable APIs with AI-assisted development.

Mar, 17 2026

Security Basics for Non-Technical Builders Using Vibe Coding Platforms

Emily Fies

Non-technical builders using AI coding tools like Replit or GitHub Copilot need to understand basic security - or risk exposing secrets, data, and money. Learn the 4 must-do steps to protect your vibe-coded apps.

Mar, 16 2026

Latency Budgets for Interactive Large Language Model Applications

Emily Fies

Latency budgets determine whether your AI app feels responsive or frustrating. Learn how TTFT, batching, model size, and caching shape real-world performance for interactive LLM applications.

Mar, 15 2026

Rotary Position Embeddings and ALiBi: How Modern LLMs Handle Sequence Order

Emily Fies

Rotary Position Embeddings and ALiBi are two modern methods that help large language models understand word order without traditional positional encodings. Both improve long-context handling, scalability, and efficiency.

Mar, 14 2026

vLLM vs TGI: Which LLM Serving Framework Delivers More Power for Your API?

Emily Fies

vLLM and TGI are two leading frameworks for serving large language models. vLLM delivers higher throughput and memory efficiency, while TGI offers easier deployment and better observability. Choose based on your traffic, model size, and team workflow.

Mar, 12 2026

Parameter-Efficient Generative AI: LoRA, Adapters, and Prompt Tuning at Scale

Emily Fies

LoRA, adapters, and prompt tuning let you adapt massive AI models without retraining them fully. These methods cut costs by 90%+, making fine-tuning possible on consumer hardware. Learn how they work, how they compare, and which one to choose.

Mar, 10 2026

Cost Management for Large Language Models: Pricing Models and Token Budgets

Emily Fies

Learn how to manage LLM costs using token budgets, model cascading, and caching. Cut AI expenses by 30-50% without losing quality. Real pricing data and proven strategies for 2026.

Mar, 8 2026

NLP Pipelines vs End-to-End LLMs: When to Use Traditional Processing vs Prompting

Emily Fies

NLP pipelines offer speed and precision for structured tasks, while LLMs excel at complex reasoning. The best approach combines both: use pipelines for preprocessing and LLMs for nuanced understanding. This hybrid model cuts costs, improves accuracy, and meets regulatory needs.

Mar, 7 2026

Real-Time Multimodal Assistants Powered by Large Language Models: What They Can Do Today

Emily Fies

Real-time multimodal assistants use AI to process text, images, audio, and video together in under half a second. They're already improving customer service, healthcare, and education-but they're not perfect yet.

BRICS AI Economics

Autoscaling Large Language Model Services: Policies, Signals, and Costs

How Prompt Templates Reduce Waste in Large Language Model Usage

Cost Savings from Compression: How LLM Efficiency Drives Real Business Value

Versioning Contracts in Vibe-Coded APIs: Preventing Breaking Changes

Security Basics for Non-Technical Builders Using Vibe Coding Platforms

Latency Budgets for Interactive Large Language Model Applications

Rotary Position Embeddings and ALiBi: How Modern LLMs Handle Sequence Order

vLLM vs TGI: Which LLM Serving Framework Delivers More Power for Your API?

Parameter-Efficient Generative AI: LoRA, Adapters, and Prompt Tuning at Scale

Cost Management for Large Language Models: Pricing Models and Token Budgets

NLP Pipelines vs End-to-End LLMs: When to Use Traditional Processing vs Prompting

Real-Time Multimodal Assistants Powered by Large Language Models: What They Can Do Today

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Latest Courses

Cost Management for Large Language Models: Pricing Models and Token Budgets

Latency Budgets for Interactive Large Language Model Applications

How Synthetic Data Generation Protects Privacy in LLM Training

vLLM vs TGI: Which LLM Serving Framework Delivers More Power for Your API?

Parameter-Efficient Generative AI: LoRA, Adapters, and Prompt Tuning at Scale

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