Seattle Skeptics on AI

Privacy-Aware RAG: How to Protect Sensitive Data in Large Language Model Systems
Privacy-Aware RAG: How to Protect Sensitive Data in Large Language Model Systems

Tamara Weed, Jan, 27 2026

Privacy-Aware RAG protects sensitive data in AI systems by filtering out personal information before it reaches large language models. Learn how it works, where it’s used, and why it’s becoming essential for compliance.

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Structured Reasoning Modules in Large Language Models: How Planning and Tool Use Boost Accuracy
Structured Reasoning Modules in Large Language Models: How Planning and Tool Use Boost Accuracy

Tamara Weed, Jan, 26 2026

Structured Reasoning Modules transform how LLMs solve complex problems by breaking reasoning into Generate-Verify-Revise steps. This new approach boosts accuracy by over 12% on hard tasks and reduces errors, making it essential for finance, science, and legal AI systems.

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Encoder-Decoder vs Decoder-Only Transformers: Which Architecture Powers Today’s Large Language Models?
Encoder-Decoder vs Decoder-Only Transformers: Which Architecture Powers Today’s Large Language Models?

Tamara Weed, Jan, 25 2026

Decoder-only transformers dominate modern LLMs for speed and scalability, but encoder-decoder models still lead in precision tasks like translation and summarization. Learn which architecture fits your use case in 2026.

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Prompt Chaining vs Agentic Planning: Which LLM Pattern Fits Your Task?
Prompt Chaining vs Agentic Planning: Which LLM Pattern Fits Your Task?

Tamara Weed, Jan, 24 2026

Prompt chaining and agentic planning are two ways to make LLMs handle complex tasks. One is simple and cheap. The other is smart but costly. Learn which one fits your use case-and why most teams get it wrong.

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Agentic Behavior in Large Language Models: Planning, Tools, and Autonomy
Agentic Behavior in Large Language Models: Planning, Tools, and Autonomy

Tamara Weed, Jan, 23 2026

Agentic LLMs plan, use tools, and act autonomously-transforming AI from passive responders to active problem-solvers. Learn how they work, where they're used, and why safety remains a critical challenge.

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The Next Wave of Vibe Coding Tools: What's Missing Today
The Next Wave of Vibe Coding Tools: What's Missing Today

Tamara Weed, Jan, 22 2026

Vibe coding tools generate code fast but fail at system design. Today's platforms can build components but not scalable architectures. The next wave must solve context, governance, and planning gaps to move beyond prototypes.

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What Counts as Vibe Coding? A Practical Checklist for Teams
What Counts as Vibe Coding? A Practical Checklist for Teams

Tamara Weed, Jan, 21 2026

Vibe coding lets teams build software by describing what they want-no code editing needed. Learn the five rules, the right tools, and when to use it-plus the risks of skipping tests and reviews.

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Budgeting for Generative AI Programs: How to Plan Costs and Measure Real Value
Budgeting for Generative AI Programs: How to Plan Costs and Measure Real Value

Tamara Weed, Jan, 20 2026

Generative AI isn't just a tool-it's a system with hidden costs. Learn how to budget for data, compliance, training, and ongoing maintenance to realize real ROI. Avoid the 73% failure rate by planning for the full lifecycle.

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How to Use Agent Plugins and Tools to Extend Vibe Coding Capabilities
How to Use Agent Plugins and Tools to Extend Vibe Coding Capabilities

Tamara Weed, Jan, 19 2026

Learn how agent plugins and tools like Cline, Cursor, and Anima extend vibe coding to build apps with natural language. Discover real-world uses, Chrome extensions, limitations, and how to start today.

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Domain-Specialized Generative AI Models: Why Industry-Specific AI Outperforms General Models
Domain-Specialized Generative AI Models: Why Industry-Specific AI Outperforms General Models

Tamara Weed, Jan, 18 2026

Domain-specialized generative AI models outperform general AI in healthcare, finance, and legal fields by focusing on industry-specific data. Learn how they work, where they excel, and why they're becoming the standard for enterprise AI.

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Hardware-Friendly LLM Compression: How to Optimize Large Models for GPUs and CPUs
Hardware-Friendly LLM Compression: How to Optimize Large Models for GPUs and CPUs

Tamara Weed, Jan, 17 2026

Learn how LLM compression techniques like quantization and pruning let you run large models on consumer GPUs and CPUs without sacrificing performance. Real-world benchmarks, trade-offs, and what to use in 2026.

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Trustworthy AI for Code: How Verification, Provenance, and Watermarking Are Changing Software Development
Trustworthy AI for Code: How Verification, Provenance, and Watermarking Are Changing Software Development

Tamara Weed, Jan, 16 2026

Trustworthy AI for code is no longer optional. With AI generating millions of lines of code daily, verification, provenance, and watermarking are essential to prevent security risks, ensure compliance, and maintain developer trust.

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