Seattle Skeptics on AI

Seattle Skeptics on AI2026-08-04T06:50:58+00:00https://seattleskeptics.org/Tamara Weedhttps://seattleskeptics.org/author/tamara-weed/Safety by Design in Generative AI: Embedding Protections into Product Architecture

Explore Safety by Design in Generative AI, a framework by Thorn and NIST that embeds protections into product architecture to prevent harm like CSAM, moving beyond reactive filters to proactive engineering.

2026-08-04T06:50:58+00:002026-08-04T06:50:58+00:00Enterprise TechnologyTamara Weedhttps://seattleskeptics.org/author/tamara-weed/Safety by Design in Generative AI: How to Embed Protections into Product Architecture

Explore Safety by Design in Generative AI, a framework by Thorn and partners like NIST that embeds protections into product architecture. Learn how to prevent CSAM and other harms through proactive development, deployment, and maintenance strategies.

2026-08-04T06:50:58+00:002026-08-04T06:50:58+00:00Enterprise TechnologyTamara Weedhttps://seattleskeptics.org/author/tamara-weed/Marketing Content at Scale with Generative AI: Product Descriptions, Emails, and Social Posts

Learn how to scale marketing content using generative AI for product descriptions, emails, and social posts. Discover top tools, best practices, and how to maintain brand voice in 2026.

2026-08-03T05:54:40+00:002026-08-03T05:54:40+00:00Enterprise TechnologyTamara Weedhttps://seattleskeptics.org/author/tamara-weed/BERT vs GPT: Choosing Between Encoder-Only and Decoder-Only AI Models

Explore the key differences between BERT and GPT architectures. Learn how encoder-only and decoder-only models impact NLP tasks, performance, and implementation costs.

2026-08-02T05:52:42+00:002026-08-02T05:52:42+00:00Science & ResearchTamara Weedhttps://seattleskeptics.org/author/tamara-weed/BERT vs GPT: Understanding Encoder-Only vs Decoder-Only Architectures

Explore the key differences between BERT and GPT architectures. Learn why encoder-only models excel at understanding while decoder-only models dominate text generation, and how to choose the right one for your NLP project.

2026-08-02T05:52:42+00:002026-08-02T05:52:42+00:00Science & ResearchTamara Weedhttps://seattleskeptics.org/author/tamara-weed/Comparative Prompting: How to Ask AI for Options, Trade-Offs, and Recommendations

Learn comparative prompting: a proven technique to ask AI for structured options, trade-offs, and recommendations. Improve decision quality by 73% with specific criteria.

2026-08-01T06:11:24+00:002026-08-01T06:11:24+00:00Enterprise TechnologyTamara Weedhttps://seattleskeptics.org/author/tamara-weed/Incident Response for Harmful LLM Outputs: A Practical Guide to Bias & Fairness Failures

A practical guide to detecting, containing, and remediating harmful LLM outputs, focusing on bias, fairness, and prompt injection attacks.

2026-07-31T05:56:14+00:002026-07-31T05:56:14+00:00Enterprise TechnologyTamara Weedhttps://seattleskeptics.org/author/tamara-weed/How Generative AI Transforms Construction Bids, Schedules, and Safety Plans

Discover how generative AI is transforming construction bids, schedules, and safety plans. Learn about tools like ALICE and nPlan that optimize timelines, reduce risks, and enhance safety through predictive analytics.

2026-07-30T05:56:42+00:002026-07-30T05:56:42+00:00Enterprise TechnologyTamara Weedhttps://seattleskeptics.org/author/tamara-weed/Enterprise LLM Strategy Roadmap: How to Plan, Govern, and Scale AI in 2026

Learn how to build a winning Enterprise LLM Strategy Roadmap in 2026. Discover the 5-phase implementation process, governance best practices, and cost-control tactics to scale AI successfully.

2026-07-29T05:53:12+00:002026-07-29T05:53:12+00:00Enterprise TechnologyTamara Weedhttps://seattleskeptics.org/author/tamara-weed/Architectural Standards for Vibe-Coded Systems: Reference Implementations

Explore architectural standards for vibe-coded systems. Learn how reference implementations and strict governance prevent technical debt and security risks in AI-generated software.

2026-07-28T05:51:32+00:002026-07-28T05:51:32+00:00Enterprise TechnologyTamara Weedhttps://seattleskeptics.org/author/tamara-weed/Navigating Copyright in Generative AI: Fair Use, Licensing, and Data Provenance

Navigate the legal complexities of generative AI in 2026. Learn how fair use, licensing deals, and data provenance impact your business strategy and copyright compliance.

2026-07-27T06:05:44+00:002026-07-27T06:05:44+00:00Enterprise TechnologyTamara Weedhttps://seattleskeptics.org/author/tamara-weed/Prompt Injection Risks in Large Language Models: Attacks and Defenses

Explore the critical risks of prompt injection in LLMs. Learn how attackers exploit semantic ambiguity, common attack vectors like jailbreaks and stored injections, and practical defense strategies including context partitioning and input filtering.

2026-07-26T05:59:13+00:002026-07-26T05:59:13+00:00Enterprise TechnologyTamara Weedhttps://seattleskeptics.org/author/tamara-weed/How Generative AI Is Transforming Automotive Design, Diagnostics, and Connected Experiences

Discover how generative AI is revolutionizing automotive design, diagnostics, and in-car experiences. Learn about real-world applications, challenges, and future trends shaping the industry.

2026-07-25T05:59:06+00:002026-07-25T05:59:06+00:00Enterprise TechnologyTamara Weedhttps://seattleskeptics.org/author/tamara-weed/GPU Selection for LLM Inference: A100 vs H100 vs CPU Offloading

Compare NVIDIA A100, H100, and CPU offloading for LLM inference. Learn about performance differences, cost-efficiency, and when to choose each option for your AI infrastructure.

2026-07-24T06:26:11+00:002026-07-24T06:26:11+00:00Enterprise TechnologyTamara Weedhttps://seattleskeptics.org/author/tamara-weed/How to Build Custom Benchmarks for Enterprise LLMs: A Practical Guide

Learn how to build custom benchmarks for enterprise LLMs. Move beyond generic metrics to evaluate tone, compliance, and task success with practical steps and LLM-as-a-Judge techniques.

2026-07-23T05:58:58+00:002026-07-23T05:58:58+00:00Enterprise TechnologyTamara Weedhttps://seattleskeptics.org/author/tamara-weed/Test Coverage Targets for AI-Generated Code: Realistic Benchmarks for 2026

Discover realistic test coverage targets for AI-generated code in 2026. Learn why 80% is no longer enough and how to use risk-based testing, mutation scores, and path coverage to ensure maintainability and reduce defects.

2026-07-22T05:56:19+00:002026-07-22T05:56:19+00:00Enterprise TechnologyTamara Weedhttps://seattleskeptics.org/author/tamara-weed/Building Trust in Generative AI: A Practical Guide to Stakeholder Engagement and Transparency

A practical guide to building ethical generative AI programs through stakeholder engagement and transparency. Learn how to implement robust frameworks, navigate 2026 regulations, and build lasting trust.

2026-07-21T06:10:19+00:002026-07-21T06:10:19+00:00Enterprise TechnologyTamara Weedhttps://seattleskeptics.org/author/tamara-weed/API vs Open-Source LLMs: The 2026 Decision Framework for Cost, Privacy, and Performance

A practical decision framework for choosing between API and open-source LLMs in 2026. Compare costs, privacy, and performance to avoid expensive mistakes.

2026-07-20T05:54:18+00:002026-07-20T05:54:18+00:00Enterprise TechnologyTamara Weedhttps://seattleskeptics.org/author/tamara-weed/How to Build Content Moderation Pipelines for LLMs: A Practical Guide

Learn how to build effective content moderation pipelines for LLMs using hybrid approaches and policy-as-prompt strategies to reduce risks and costs.

2026-07-19T05:56:45+00:002026-07-19T05:56:45+00:00Enterprise TechnologyTamara Weedhttps://seattleskeptics.org/author/tamara-weed/How to Detect Fabricated References in LLM Outputs: A Guide for Researchers

Discover how to detect fabricated references in LLM outputs. Learn why AI creates ghost citations, the risks to academic integrity, and tools like CERCA to verify sources.

2026-07-18T05:57:46+00:002026-07-18T05:57:46+00:00Science & ResearchTamara Weedhttps://seattleskeptics.org/author/tamara-weed/Design Patterns for Safe, Reliable, and Maintainable LLM Agents

Explore proven design patterns for building safe, reliable, and maintainable LLM agents. Learn how to balance autonomy with control using deterministic chains, single-agent systems, and security-first strategies like Plan-Then-Execute.

2026-07-17T07:52:02+00:002026-07-17T07:52:02+00:00Enterprise TechnologyTamara Weedhttps://seattleskeptics.org/author/tamara-weed/Data Augmentation for LLM Fine-Tuning: Synthetic and Human-in-the-Loop Approaches

Learn how to boost LLM fine-tuning performance using synthetic data and human-in-the-loop validation. Discover PEFT strategies like LoRA to save costs.

2026-07-16T05:57:26+00:002026-07-16T05:57:26+00:00Enterprise TechnologyTamara Weedhttps://seattleskeptics.org/author/tamara-weed/Cost Control for LLM Agents: Tool Calls, Context Windows, and Think Tokens

Learn how to control costs for LLM agents in 2026 by optimizing context windows, managing tool call efficiency, and navigating think token pricing. Discover strategies to cut infrastructure bills by up to 50%.

2026-07-15T05:50:03+00:002026-07-15T05:50:03+00:00Enterprise TechnologyTamara Weedhttps://seattleskeptics.org/author/tamara-weed/Contact Center ROI from Generative AI: How to Improve Handle Time, CSAT, and First Contact Resolution

Discover how Generative AI boosts contact center ROI by cutting handle time, raising CSAT, and improving First Contact Resolution with real data and implementation strategies.

2026-07-14T06:03:14+00:002026-07-14T06:03:14+00:00Enterprise TechnologyTamara Weedhttps://seattleskeptics.org/author/tamara-weed/Cut GenAI Costs by 60%: Scheduling, Autoscaling, and Spot Instances Guide

Learn how to cut generative AI cloud costs by 60% using intelligent scheduling, AI-specific autoscaling, and spot instances. Practical strategies for 2026.

2026-07-13T05:53:45+00:002026-07-13T05:53:45+00:00Enterprise TechnologyTamara Weedhttps://seattleskeptics.org/author/tamara-weed/Human Feedback in the Loop: Scoring and Refining AI Code Iterations

Master Human Feedback in the Loop (HFIL) to boost code quality by 37%. Learn how to score AI iterations, implement structured workflows, and avoid common pitfalls in 2026.

2026-07-12T06:04:00+00:002026-07-12T06:04:00+00:00Enterprise TechnologyTamara Weedhttps://seattleskeptics.org/author/tamara-weed/Token Budgets and Quotas: How to Stop LLM Cost Overruns in 2026

Stop LLM cost overruns with token budgets and quotas. Learn how to implement graduated thresholds, track input/output tokens, and prevent budget surprises in 2026.

2026-07-11T06:00:30+00:002026-07-11T06:00:30+00:00Enterprise TechnologyTamara Weedhttps://seattleskeptics.org/author/tamara-weed/Top Enterprise Use Cases for Large Language Models in 2025: A Practical Guide

Explore the top enterprise use cases for Large Language Models in 2025. From code generation to fraud detection, discover how companies leverage AI for ROI, security, and efficiency.

2026-07-10T06:19:01+00:002026-07-10T06:19:01+00:00Enterprise TechnologyTamara Weedhttps://seattleskeptics.org/author/tamara-weed/Data Classification Rules for Vibe Coding Inputs and Outputs: A Governance Guide

Learn how to implement data classification rules for vibe coding inputs and outputs. Discover frameworks for securing AI-generated code against PII leaks, exposed secrets, and misconfigurations.

2026-07-09T06:35:47+00:002026-07-09T06:35:47+00:00Enterprise TechnologyTamara Weedhttps://seattleskeptics.org/author/tamara-weed/Safety-Aware Prompting: How to Stop AI Leaks and Attacks in 2026

Learn safety-aware prompting techniques to protect your business from AI data leaks and prompt injection attacks. Discover practical steps for secure generative AI usage in 2026.

2026-07-08T06:17:57+00:002026-07-08T06:17:57+00:00Enterprise TechnologyTamara Weedhttps://seattleskeptics.org/author/tamara-weed/Supply Chain ROI Using Generative AI: Forecast Accuracy and Inventory Turns

Discover how generative AI boosts supply chain ROI by improving forecast accuracy and inventory turns. Learn about real-world costs, implementation challenges, and the shift from static planning to dynamic prediction.

2026-07-07T06:13:53+00:002026-07-07T06:13:53+00:00Enterprise TechnologyTamara Weedhttps://seattleskeptics.org/author/tamara-weed/Pipeline Orchestration for Multimodal Generative AI: Preprocessors and Postprocessors

Explore how pipeline orchestration transforms raw multimodal data into actionable AI insights. Learn about preprocessors, postprocessors, and top frameworks like NVIDIA NeMo and Microsoft Azure.

2026-07-06T06:24:17+00:002026-07-06T06:24:17+00:00Enterprise TechnologyTamara Weedhttps://seattleskeptics.org/author/tamara-weed/Education and Generative AI: Curriculum Design, Assessment, and Tutoring

Explore how generative AI is transforming education in 2026 through advanced curriculum design, adaptive assessment, and personalized tutoring. Discover top tools, ethical considerations, and real-world impacts on student outcomes.

2026-07-05T06:00:50+00:002026-07-05T06:00:50+00:00Enterprise TechnologyTamara Weedhttps://seattleskeptics.org/author/tamara-weed/Hybrid Cloud vs On-Prem for LLM Serving: A 2026 Deployment Guide

Explore hybrid cloud and on-prem strategies for LLM serving. Learn how to balance cost, security, and performance using vLLM, Kubernetes, and cloud bursting for enterprise AI.

2026-07-04T06:01:39+00:002026-07-04T06:01:39+00:00Enterprise TechnologyTamara Weedhttps://seattleskeptics.org/author/tamara-weed/Building Better Generative AI: A Guide to Data Pipelines, Deduplication, and Filtering

Learn how to build effective training data pipelines for generative AI. Master deduplication, filtering, and mixture design to boost model quality and cut costs.

2026-07-03T07:07:46+00:002026-07-03T07:07:46+00:00Enterprise TechnologyTamara Weedhttps://seattleskeptics.org/author/tamara-weed/Code Execution for LLM Agents: How AI Runs Code, Risks Involved, and Best Practices

Explore how code execution transforms LLMs into active agents, the security risks involved, and best practices for enterprise deployment.

2026-07-02T06:01:59+00:002026-07-02T06:01:59+00:00Enterprise TechnologyTamara Weedhttps://seattleskeptics.org/author/tamara-weed/Why Large Language Models Excel: Transfer, Generalization, and Emergent Abilities Explained

Discover why Large Language Models excel at diverse tasks through transfer learning, generalization, and emergent abilities. Learn how these mechanisms work, their benefits, limitations, and practical implementation tips for 2026.

2026-07-01T06:21:58+00:002026-07-01T06:21:58+00:00Science & ResearchTamara Weedhttps://seattleskeptics.org/author/tamara-weed/Ethical AI Agents for Code: Guardrails that Enforce Policy by Default

Learn how ethical AI agents use policy-as-code and Law-Following AI frameworks to enforce compliance by default, reducing risk and enhancing trust in enterprise software.

2026-06-30T05:50:03+00:002026-06-30T05:50:03+00:00Enterprise TechnologyTamara Weedhttps://seattleskeptics.org/author/tamara-weed/Grounding LLM Reasoning with External Verifiers: Frameworks, Methods, and Performance Gains

Learn how external verifiers like FOLK, CoRGI, and GRiD ground LLM reasoning, reduce hallucinations, and boost accuracy in text and vision tasks.

2026-06-29T05:57:31+00:002026-06-29T05:57:31+00:00Enterprise TechnologyTamara Weedhttps://seattleskeptics.org/author/tamara-weed/Stochastic Depth in LLMs: How Random Layer Dropping Regularizes Deep Transformers

Explore how stochastic depth regularizes deep transformer-based LLMs by randomly dropping layers. Learn about neural collapse, implementation strategies, and advanced techniques like LAAT and ReplaceMe for better generalization.

2026-06-28T05:55:31+00:002026-06-28T05:55:31+00:00Science & ResearchTamara Weedhttps://seattleskeptics.org/author/tamara-weed/Access Control for Vibe Coding Tools: Securing Data Privacy and Repository Scope

Secure your vibe coding workflow by implementing strict access control, managing repository scope, and protecting data privacy against AI-driven risks.

2026-06-27T06:18:41+00:002026-06-27T06:18:41+00:00Enterprise TechnologyTamara Weedhttps://seattleskeptics.org/author/tamara-weed/Service Boundaries in Vibe Coding: How to Stop AI Prompts from Creating Tight Coupling

Learn how to prevent tight coupling in vibe coding by defining strict service boundaries. Discover strategies like constitutional architecture, modular monoliths, and ADRs to keep AI-generated code maintainable.

2026-06-26T06:10:44+00:002026-06-26T06:10:44+00:00Enterprise TechnologyTamara Weedhttps://seattleskeptics.org/author/tamara-weed/Generative AI in Agriculture: Crop Reports, Manuals, and Market Outlooks

Explore how generative AI transforms agriculture in 2026 through automated crop reports, simplified equipment manuals, and predictive market outlooks, bridging the gap between data and actionable farm decisions.

2026-06-25T06:36:25+00:002026-06-25T06:36:25+00:00Enterprise TechnologyTamara Weedhttps://seattleskeptics.org/author/tamara-weed/Data Analysts Automating Reporting Dashboards with Vibe Coding Tools

Discover how data analysts are using vibe coding tools like Glide, Bubble, and Cursor to automate reporting dashboards in 2026. Learn which tools fit your data needs, avoid common pitfalls, and cut development time from weeks to hours.

2026-06-24T06:03:03+00:002026-06-24T06:03:03+00:00Enterprise TechnologyTamara Weedhttps://seattleskeptics.org/author/tamara-weed/How to Fix Bias in Large Language Models: Data and Training Techniques

Learn practical techniques to reduce bias in Large Language Models through data augmentation, adversarial training, and post-processing. Compare costs, accuracy trade-offs, and tools for compliant AI.

2026-06-23T05:54:45+00:002026-06-23T05:54:45+00:00Science & ResearchTamara Weedhttps://seattleskeptics.org/author/tamara-weed/Financial Services Rules for Generative AI: Model Risk Management and Fair Lending

Explore the 2026 regulatory landscape for generative AI in finance. Learn about FINRA's new oversight, model risk management updates, and fair lending compliance strategies to avoid costly penalties.

2026-06-22T06:40:28+00:002026-06-22T06:40:28+00:00Enterprise TechnologyTamara Weedhttps://seattleskeptics.org/author/tamara-weed/Regulatory Readiness for Responsible Generative AI: Documentation and Controls

Learn how to achieve regulatory readiness for generative AI with essential documentation and controls. Understand EU AI Act, NIST AI RMF, and practical steps for compliance.

2026-06-21T05:53:00+00:002026-06-21T05:53:00+00:00Enterprise TechnologyTamara Weedhttps://seattleskeptics.org/author/tamara-weed/Memory and State Management for Persistent LLM Agents: A Practical Guide

Learn how to build persistent LLM agents with robust memory and state management. Explore vector databases, RLEM, and frameworks like Mem0 and LangChain for long-term retention.

2026-06-20T06:06:01+00:002026-06-20T06:06:01+00:00Enterprise TechnologyTamara Weedhttps://seattleskeptics.org/author/tamara-weed/Zero-Trust Architecture for LLM Integrations: A Security Guide

Learn how to secure Large Language Models with Zero-Trust Architecture. Discover key strategies including federated learning, sentinel systems, and strict access controls to protect data privacy.

2026-06-19T05:54:37+00:002026-06-19T05:54:37+00:00Enterprise TechnologyTamara Weedhttps://seattleskeptics.org/author/tamara-weed/When to Rewrite AI-Generated Modules Instead of Refactoring: A Practical Guide

Learn when to rewrite AI-generated modules instead of refactoring. Discover key indicators like complexity and security flaws, and apply the three-strike rule to save time and reduce technical debt.

2026-06-18T06:01:47+00:002026-06-18T06:01:47+00:00Enterprise TechnologyTamara Weedhttps://seattleskeptics.org/author/tamara-weed/