Education Hub for Generative AI

Education Hub for Generative AI2026-05-18T06:29:14+00:00https://ehga.org/Susannah Greenwoodhttps://ehga.org/author/susannah-greenwood/Constrained Decoding for LLMs: Mastering JSON, Regex, and Schema Control

Learn how constrained decoding guarantees JSON, regex, and schema compliance in LLMs. Explore performance trade-offs, model comparisons, and implementation tools for structured generation.

2026-05-18T06:29:14+00:002026-05-18T06:29:14+00:00AI & Machine LearningSusannah Greenwoodhttps://ehga.org/author/susannah-greenwood/Vibe Coding Glossary: Essential Terms for AI-Assisted Development

Explore the essential terms of vibe coding, the AI-assisted development method transforming software creation. Learn key concepts, tools, and risks to master this new workflow.

2026-05-17T06:07:04+00:002026-05-17T06:07:04+00:00AI & Machine LearningSusannah Greenwoodhttps://ehga.org/author/susannah-greenwood/Security Telemetry for LLMs: Logging Prompts, Outputs, and Tool Usage

Discover how to implement effective security telemetry for Large Language Models. Learn to log prompts, validate outputs, and monitor tool usage to prevent data leaks and adversarial attacks.

2026-05-16T06:32:20+00:002026-05-16T06:32:20+00:00AI & Machine LearningSusannah Greenwoodhttps://ehga.org/author/susannah-greenwood/Cursor vs Replit for Teams: Shared Context, Reviews, and Collaboration Workflows

Compare Cursor and Replit for team collaboration. We analyze shared context, code review workflows, and security to help you choose the right tool for your development needs.

2026-05-15T06:24:23+00:002026-05-15T06:24:23+00:00AI & Machine LearningSusannah Greenwoodhttps://ehga.org/author/susannah-greenwood/Building Internal Marketplaces for Vibe-Coded Components: Governance, Safety, and Scale

Explore how internal marketplaces solve governance challenges for vibe-coded components. Learn about AI-driven development, security frameworks, and scaling strategies for enterprise adoption.

2026-05-14T06:20:50+00:002026-05-14T06:20:50+00:00AI & Machine LearningSusannah Greenwoodhttps://ehga.org/author/susannah-greenwood/Why You Don't Need to Read Every Line of AI Code in Vibe Coding

Explore why understanding every line of AI-generated code isn't the goal in vibe coding. Learn how this new paradigm shifts focus from syntax to intent, boosts speed, and requires strategic review.

2026-05-13T06:29:20+00:002026-05-13T06:29:20+00:00AI & Machine LearningSusannah Greenwoodhttps://ehga.org/author/susannah-greenwood/How Sampling Choices Influence LLM Accuracy: Controlling Hallucinations

Explore how LLM sampling choices like temperature, top-k, and nucleus sampling directly influence hallucination rates. Learn practical strategies to boost accuracy without retraining models.

2026-05-12T06:45:23+00:002026-05-12T06:45:23+00:00AI & Machine LearningSusannah Greenwoodhttps://ehga.org/author/susannah-greenwood/Red Teaming LLMs at Scale: Automated Adversarial Testing Guide

Learn how to scale LLM security with automated red teaming. Discover why manual testing falls short, explore key vulnerability categories, and see how hybrid approaches improve AI safety.

2026-05-11T06:12:26+00:002026-05-11T06:12:26+00:00AI & Machine LearningSusannah Greenwoodhttps://ehga.org/author/susannah-greenwood/Building Content Moderation Pipelines for LLMs: A 2026 Security Guide

Learn how to build secure content moderation pipelines for LLMs using hybrid architectures, policy-as-prompt strategies, and human-in-the-loop validation to prevent security risks and ensure compliance.

2026-05-10T05:53:10+00:002026-05-10T05:53:10+00:00AI & Machine LearningSusannah Greenwoodhttps://ehga.org/author/susannah-greenwood/Building Content Moderation Pipelines for LLMs: A Practical Guide to Security and Safety

Learn how to build secure content moderation pipelines for LLMs using hybrid architectures, policy-as-prompt strategies, and human-in-the-loop validation to prevent security risks.

2026-05-10T05:53:10+00:002026-05-10T05:53:10+00:00AI & Machine LearningSusannah Greenwoodhttps://ehga.org/author/susannah-greenwood/Risk-Based App Categories: Prototypes, Internal Tools, and External Products

Learn how to classify apps into prototypes, internal tools, and external products to optimize security budgets. Discover risk-based strategies, common pitfalls, and implementation tips for modern governance.

2026-05-09T06:28:39+00:002026-05-09T06:28:39+00:00Cloud Architecture & DevOpsSusannah Greenwoodhttps://ehga.org/author/susannah-greenwood/LLM Inference Observability: Tracking Token Metrics, Queues, and Tail Latency

Master LLM inference observability by tracking token metrics, queue dynamics, and tail latency. Learn why requests-per-second fails and how to optimize GPU utilization for faster, cheaper AI responses.

2026-05-08T06:03:49+00:002026-05-08T06:03:49+00:00AI & Machine LearningSusannah Greenwoodhttps://ehga.org/author/susannah-greenwood/Legal and Regulatory Compliance for LLM Data Processing: A 2026 Guide

Navigate the complex world of LLM data privacy in 2026. This guide covers the EU AI Act, US state laws, and technical controls needed to avoid massive fines and ensure secure AI deployment.

2026-05-07T06:04:33+00:002026-05-07T06:04:33+00:00AI & Machine LearningSusannah Greenwoodhttps://ehga.org/author/susannah-greenwood/Cutting Generative AI Training Energy: A Guide to Sparsity, Pruning, and Low-Rank Methods

Discover how sparsity, pruning, and low-rank methods can cut generative AI training energy by up to 80% without losing accuracy. Learn practical implementation steps for TensorFlow and PyTorch.

2026-05-06T06:06:35+00:002026-05-06T06:06:35+00:00AI & Machine LearningSusannah Greenwoodhttps://ehga.org/author/susannah-greenwood/Sales Enablement Using LLMs: Battlecards, Objection Handling, and Summaries

Discover how Large Language Models (LLMs) revolutionize sales enablement by creating dynamic battlecards, automating objection handling, and generating smart conversational summaries to boost rep efficiency.

2026-05-05T06:43:16+00:002026-05-05T06:43:16+00:00AI & Machine LearningSusannah Greenwoodhttps://ehga.org/author/susannah-greenwood/Customer Journey Personalization Using Generative AI: Real-Time Segmentation and Content

Discover how generative AI transforms customer journeys through real-time segmentation and dynamic content. Learn implementation strategies, technical requirements, and how to balance personalization with privacy.

2026-05-04T06:23:37+00:002026-05-04T06:23:37+00:00AI & Machine LearningSusannah Greenwoodhttps://ehga.org/author/susannah-greenwood/Data Privacy for Generative AI: Minimization, Retention, and Anonymization Strategy

Master data privacy for Generative AI with actionable strategies on minimization, retention, and anonymization. Learn how to stay compliant with 2026 regulations while enabling safe AI innovation.

2026-05-03T05:53:02+00:002026-05-03T05:53:02+00:00AI & Machine LearningSusannah Greenwoodhttps://ehga.org/author/susannah-greenwood/How Prompt Templates Reduce Waste in Large Language Model Usage

Discover how prompt templates cut LLM waste by up to 85%. Learn about token optimization, energy savings, and tools like LangChain to reduce AI costs and carbon footprint.

2026-05-02T05:55:56+00:002026-05-02T05:55:56+00:00AI & Machine LearningSusannah Greenwoodhttps://ehga.org/author/susannah-greenwood/Generative AI Audits: Independent Assessments, Certifications, and Compliance

Independent AI audits verify compliance with laws like the EU AI Act and NIST RMF. Learn how to prepare for assessments, choose certified auditors, and implement continuous monitoring for generative AI systems.

2026-05-01T06:11:00+00:002026-05-01T06:11:00+00:00AI & Machine LearningSusannah Greenwoodhttps://ehga.org/author/susannah-greenwood/Backlog Hygiene for Vibe Coding: Managing Defects, Debt, and Enhancements

Master backlog hygiene for vibe coding. Learn how to handle AI-generated technical debt, defects, and enhancements using micro-issues for faster delivery.

2026-04-30T06:19:07+00:002026-04-30T06:19:07+00:00AI & Machine LearningSusannah Greenwoodhttps://ehga.org/author/susannah-greenwood/Safety-Aware Prompting: How to Prevent Sensitive Data Leaks in GenAI

Learn how to use safety-aware prompting to prevent data leaks and prompt injections in Generative AI. Practical habits and technical strategies for secure LLM use.

2026-04-29T06:14:50+00:002026-04-29T06:14:50+00:00AI & Machine LearningSusannah Greenwoodhttps://ehga.org/author/susannah-greenwood/From Figma to Function: A Guide to Vibe Coding for Designers

Learn how vibe coding uses AI and Figma's MCP to turn design mockups into functional code, bridging the gap between designers and developers for rapid prototyping.

2026-04-28T05:53:22+00:002026-04-28T05:53:22+00:00AI & Machine LearningSusannah Greenwoodhttps://ehga.org/author/susannah-greenwood/How to Extend Vibe Coding with Agent Plugins and Tools

Learn how to extend vibe coding capabilities using agent plugins and tools like Cursor and Cline to move from simple AI prompts to production-ready apps.

2026-04-27T06:10:27+00:002026-04-27T06:10:27+00:00AI & Machine LearningSusannah Greenwoodhttps://ehga.org/author/susannah-greenwood/Mastering Long-Form Generation with LLMs: Structure, Coherence, and Fact-Checking

Learn how to master long-form generation with LLMs. This guide covers structural skeletons, maintaining coherence, and using RAG for rigorous fact-checking.

2026-04-26T05:56:22+00:002026-04-26T05:56:22+00:00AI & Machine LearningSusannah Greenwoodhttps://ehga.org/author/susannah-greenwood/How to Handle Multilingual Data in LLM Pretraining Pipelines

Learn how to optimize multilingual LLM pretraining by balancing token allocation, using English as a pivot, and implementing model-based data filtering.

2026-04-25T06:01:14+00:002026-04-25T06:01:14+00:00AI & Machine LearningSusannah Greenwoodhttps://ehga.org/author/susannah-greenwood/Security Code Review for AI Output: Essential Verification Checklists

A comprehensive guide for verification engineers on auditing AI-generated code, featuring security checklists, SAST tool comparisons, and a 7-step verification workflow.

2026-04-24T05:58:14+00:002026-04-24T05:58:14+00:00AI & Machine LearningSusannah Greenwoodhttps://ehga.org/author/susannah-greenwood/Continuous Batching and KV Caching: Maximizing LLM Throughput

Learn how Continuous Batching and KV Caching maximize LLM throughput and GPU utilization, reducing latency and costs in production deployment.

2026-04-23T06:44:43+00:002026-04-23T06:44:43+00:00AI & Machine LearningSusannah Greenwoodhttps://ehga.org/author/susannah-greenwood/How to Measure LLM ROI: Metrics and Frameworks for AI Value

Learn how to quantify the financial and operational value of LLM initiatives using hard metrics, soft ROI, and risk-adjusted frameworks to justify AI investments.

2026-04-22T06:17:19+00:002026-04-22T06:17:19+00:00AI & Machine LearningSusannah Greenwoodhttps://ehga.org/author/susannah-greenwood/How to Reduce LLM Latency: A Guide to Streaming, Batching, and Caching

Learn how to slash LLM response times using streaming, continuous batching, and KV caching. A practical guide to improving TTFT and OTPS for production AI.

2026-04-21T06:03:43+00:002026-04-21T06:03:43+00:00AI & Machine LearningSusannah Greenwoodhttps://ehga.org/author/susannah-greenwood/Preventing RCE in AI-Generated Code: Deserialization and Input Validation Guide

Learn how to prevent Remote Code Execution (RCE) in AI-generated code by fixing insecure deserialization and implementing strict input validation.

2026-04-19T06:40:32+00:002026-04-19T06:40:32+00:00AI & Machine LearningSusannah Greenwoodhttps://ehga.org/author/susannah-greenwood/Generative AI for Media and Publishing: Mastering Headline Variants and Editorial Tools

Explore how Generative AI is transforming media and publishing through headline variants, advanced editorial tools, and new compensation models in 2026.

2026-04-18T05:55:45+00:002026-04-18T05:55:45+00:00AI & Machine LearningSusannah Greenwoodhttps://ehga.org/author/susannah-greenwood/Logit Bias and Token Banning: How to Steer LLM Outputs Without Retraining

Learn how to use Logit Bias and token banning to precisely steer LLM outputs, prevent unwanted words, and align brand voice without the cost of retraining.

2026-04-17T06:03:46+00:002026-04-17T06:03:46+00:00AI & Machine LearningSusannah Greenwoodhttps://ehga.org/author/susannah-greenwood/Security Telemetry and Alerting for AI-Generated Applications: A Practical Guide

Learn how to implement security telemetry and alerting for AI-generated apps. Stop false positives and detect prompt injections with a modern monitoring stack.

2026-04-16T06:31:30+00:002026-04-16T06:31:30+00:00AI & Machine LearningSusannah Greenwoodhttps://ehga.org/author/susannah-greenwood/Video Understanding with Generative AI: Captioning, Summaries, and Scene Analysis

Discover how Generative AI transforms video into data. Learn about Gemini 2.5, Sora 2, and techniques for automated captioning, summaries, and scene analysis in 2026.

2026-04-15T06:18:32+00:002026-04-15T06:18:32+00:00AI & Machine LearningSusannah Greenwoodhttps://ehga.org/author/susannah-greenwood/Allocating LLM Costs Across Teams: Chargeback Models That Work

Stop the AI budget bleed. Learn how to implement LLM chargeback models that accurately allocate AI costs across teams, including RAG and agent-based workflows.

2026-04-14T06:05:47+00:002026-04-14T06:05:47+00:00AI & Machine LearningSusannah Greenwoodhttps://ehga.org/author/susannah-greenwood/Retrieval Augmented Generation for Open-Source LLMs: Tools and Best Practices

Learn how to implement Retrieval Augmented Generation (RAG) using open-source LLMs. Discover the best tools like LangChain and vLLM to stop AI hallucinations.

2026-04-13T05:55:21+00:002026-04-13T05:55:21+00:00AI & Machine LearningSusannah Greenwoodhttps://ehga.org/author/susannah-greenwood/Toolformer: How LLMs Learn to Use External Tools via Self-Supervision

Learn how Toolformer teaches LLMs to use external APIs via self-supervision, overcoming math and fact errors without massive human datasets.

2026-04-12T05:56:56+00:002026-04-12T05:56:56+00:00AI & Machine LearningSusannah Greenwoodhttps://ehga.org/author/susannah-greenwood/Throughput vs Latency: Optimizing LLM Inference Speed and Transformer Design

Explore the critical tradeoff between throughput and latency in LLM inference. Learn how transformer design, batching, and PagedAttention impact speed and cost.

2026-04-11T06:11:44+00:002026-04-11T06:11:44+00:00AI & Machine LearningSusannah Greenwoodhttps://ehga.org/author/susannah-greenwood/Generative AI in Healthcare: Boosting Diagnostic Accuracy and Treatment Speed

Explore how Generative AI is transforming healthcare by improving diagnostic accuracy, reducing treatment times, and helping eliminate medical bias in clinical settings.

2026-04-10T05:55:50+00:002026-04-10T05:55:50+00:00AI & Machine LearningSusannah Greenwoodhttps://ehga.org/author/susannah-greenwood/Infrastructure as Code for Vibe-Coded Deployments: Repeatability by Design

Learn how to combine the speed of vibe coding with Infrastructure as Code to create repeatable, AI-driven cloud deployments without sacrificing security.

2026-04-08T06:27:40+00:002026-04-08T06:27:40+00:00Cloud Architecture & DevOpsSusannah Greenwoodhttps://ehga.org/author/susannah-greenwood/Generative AI Target Architecture: Designing Data, Models, and Orchestration

Learn how to build a production-ready Generative AI architecture. This strategy guide covers data processing, RAG, orchestration frameworks, and infrastructure.

2026-04-07T06:11:49+00:002026-04-07T06:11:49+00:00AI & Machine LearningSusannah Greenwoodhttps://ehga.org/author/susannah-greenwood/Stop Vibe Coding: How to Avoid Anti-Pattern Prompts for Secure AI Code

Learn why "vibe coding" leads to insecure software and how to replace dangerous anti-pattern prompts with secure, structured frameworks to stop AI-generated vulnerabilities.

2026-04-06T05:55:32+00:002026-04-06T05:55:32+00:00AI & Machine LearningSusannah Greenwoodhttps://ehga.org/author/susannah-greenwood/Observability and SRE Guide for Self-Hosted LLMs

Learn how to apply SRE and observability practices to self-hosted LLMs. Focus on vLLM metrics, Kubernetes AI automation, and the transition from MLOps to LLMOps.

2026-04-04T06:05:48+00:002026-04-04T06:05:48+00:00AI & Machine LearningSusannah Greenwoodhttps://ehga.org/author/susannah-greenwood/Integrating Consent Management Platforms into Vibe-Coded Websites

Learn how to integrate Consent Management Platforms into vibe-coded websites to ensure GDPR and CCPA compliance without ruining your AI-generated site's aesthetic.

2026-04-03T23:38:39+00:002026-04-03T23:38:39+00:00AI & Machine LearningSusannah Greenwoodhttps://ehga.org/author/susannah-greenwood/Prompt Chaining vs Agentic Planning: Choosing the Right LLM Pattern

Learn the critical differences between Prompt Chaining and Agentic Planning for LLM systems. Compare costs, performance, and use cases to choose the right architecture for your AI project.

2026-03-31T06:20:30+00:002026-03-31T06:20:30+00:00AI & Machine LearningSusannah Greenwoodhttps://ehga.org/author/susannah-greenwood/Chain-of-Thought Prompting Guide: Improving AI Reasoning Step-by-Step

Learn how Chain-of-Thought Prompting transforms LLM accuracy by forcing step-by-step reasoning. We cover Zero-shot and Few-shot methods, cost trade-offs, and advanced techniques for 2026.

2026-03-30T06:27:08+00:002026-03-30T06:27:08+00:00AI & Machine LearningSusannah Greenwoodhttps://ehga.org/author/susannah-greenwood/Democratization of Software Development Through Vibe Coding: Who Can Build Now

Explore vibe coding: an AI-driven development method enabling non-experts to build software. Understand tools, security risks, and the new era of citizen development.

2026-03-29T06:09:16+00:002026-03-29T06:09:16+00:00AI & Machine LearningSusannah Greenwoodhttps://ehga.org/author/susannah-greenwood/Image-to-Text in Generative AI: Descriptions, Alt Text, and Accessibility

Explore how image-to-text generative AI transforms visual data into accessible alt text, balancing automation benefits with accuracy limitations.

2026-03-28T06:33:51+00:002026-03-28T06:33:51+00:00AI & Machine LearningSusannah Greenwoodhttps://ehga.org/author/susannah-greenwood/Vibe Coding for E-Commerce: Rapid Launch of Product Catalogs and Checkout Flows

Discover how vibe coding transforms e-commerce development by enabling rapid creation of product catalogs and checkout flows using AI tools.

2026-03-27T06:16:41+00:002026-03-27T06:16:41+00:00AI & Machine LearningSusannah Greenwoodhttps://ehga.org/author/susannah-greenwood/Tempo Labs vs Base44: A 2026 Guide to Emerging Vibe Coding Platforms

Compare Base44 and Tempo Labs for vibe coding in 2026. See which AI development platform fits your workflow, budget, and technical skills.

2026-03-26T06:51:13+00:002026-03-26T06:51:13+00:00AI & Machine LearningSusannah Greenwoodhttps://ehga.org/author/susannah-greenwood/