BRICS AI Economics

BRICS AI Economics

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Mar, 31 2026

Teacher Selection for LLM Distillation: How to Match Skills and Domains

Emily Fies
0
Learn how to select the right teacher model for LLM distillation by matching skills and domains. Covers essential criteria, timing strategies, and emerging collaborative approaches.
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Mar, 30 2026

State Diagrams and Orchestrators for Complex LLM Agent Pipelines

Emily Fies
1
Learn how to build stable LLM agent systems using state diagrams and orchestrators. Covers architectural patterns, frameworks like LangGraph, and practical implementation strategies.
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Mar, 29 2026

Risk-Based App Categories: Prototypes, Internal Tools, and External Products

Emily Fies
1
Stop wasting budget on low-risk code. Learn how to classify software into prototypes, internal tools, and external products to optimize security efforts.
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Mar, 28 2026

How to Budget for Vibe Coding Platforms: Licenses, Models, and Cloud Costs Explained

Emily Fies
3
Navigate unpredictable vibe coding platform costs with clear strategies for licenses, AI model pricing, and cloud expenses. Learn to budget effectively in 2026.
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Mar, 27 2026

Robustness and Generalization Tests for Large Language Model Reliability

Emily Fies
3
Learn essential robustness testing methods for LLMs beyond standard benchmarks, including adversarial stress tests, OOD validation, and real-world deployment readiness.
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Mar, 25 2026

Diverse Teams in Generative AI Development: Reducing Bias through Inclusion

Emily Fies
0
Explore how diverse teams in Generative AI Development reduce algorithmic bias. Learn practical steps, regulatory requirements, and the business case for inclusion in AI ethics.
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Mar, 24 2026

Prompting as Programming: How Natural Language Became the Interface for LLMs

Emily Fies
5
Prompting has replaced coding for many tasks, turning natural language into the new programming interface for LLMs. Learn how system prompts, Chain of Thought, and generated knowledge are reshaping how we interact with AI.
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Mar, 23 2026

Grounding Prompts in Generative AI: How Retrieval-Augmented Generation Cites Sources to Stop Hallucinations

Emily Fies
0
Grounding prompts with Retrieval-Augmented Generation stops AI hallucinations by forcing responses to cite real data. Learn how RAG works, where it excels, and why it's the only reliable way to use AI in business.
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Mar, 22 2026

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

Emily Fies
7
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.
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Mar, 20 2026

How Prompt Templates Reduce Waste in Large Language Model Usage

Emily Fies
0
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.
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Mar, 19 2026

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

Emily Fies
6
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.
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Mar, 18 2026

Versioning Contracts in Vibe-Coded APIs: Preventing Breaking Changes

Emily Fies
9
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.

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