Archive: 2026/01
Latency Optimization for Large Language Models: Streaming, Batching, and Caching
Learn how streaming, batching, and caching can slash LLM response times by up to 70%. Real-world benchmarks, hardware tips, and step-by-step optimization for chatbots and APIs.
How to Communicate Confidence and Uncertainty in Generative AI Outputs to Prevent Misinformation
Generative AI often answers with false confidence, leading to misinformation. Learn how to communicate uncertainty in AI outputs using proven methods like text size and simple labels to build trust and prevent harmful errors.
Encoder-Decoder vs Decoder-Only Transformers: Which Architecture Powers Today’s Large Language Models?
Encoder-decoder and decoder-only transformers power today's large language models in different ways. Decoder-only models dominate chatbots and general AI due to speed and scalability, while encoder-decoder models still lead in translation and summarization where precision matters.
How to Build a Coding Center of Excellence: Charter, Staffing, and Goals
Learn how to build a Coding Center of Excellence that actually gets adopted-through a clear charter, the right team structure, and measurable goals that reduce bugs and speed up development.
Inclusive Prompt Design for Diverse Users of Large Language Models
Inclusive prompt design ensures large language models work for everyone-not just fluent English speakers. Learn how IPEM improves accuracy, reduces frustration, and expands access for diverse users across cultures, languages, and abilities.
When to Rewrite AI-Generated Modules Instead of Refactoring
AI-generated code often works-but not well. Learn when to rewrite instead of refactoring to avoid technical debt, security risks, and wasted effort. Data-driven guidelines for smarter decisions.
Economic Impact of Vibe Coding: How AI-Powered Development Is Reshaping Software Costs and Competition
Vibe coding slashes software development costs by up to 85% but increases long-term maintenance expenses. Learn how AI-powered development is reshaping competition, skills, and economic risks in 2026.
Beyond BLEU and ROUGE: Why Semantic Metrics Are the New Standard for LLM Evaluation
BLEU and ROUGE are outdated for evaluating modern LLMs. Semantic metrics like BERTScore and BLEURT measure meaning, not word overlap, and correlate far better with human judgment. Here's how to use them effectively.
KPIs and Dashboards for Monitoring Large Language Model Health
Learn the essential KPIs and dashboard practices for monitoring large language model health in production. Track hallucinations, cost, latency, and safety to prevent failures and maintain user trust.
Teaching LLMs to Say 'I Don’t Know': Uncertainty Prompts That Reduce Hallucination
Learn how to reduce LLM hallucinations by teaching models to say 'I don't know' using uncertainty prompts and structured training methods like US-Tuning - proven to cut false confidence by 67% in real-world applications.
Clean Architecture in Vibe-Coded Projects: How to Keep Frameworks at the Edges
Clean architecture in vibe-coded projects keeps AI-generated code from tainting your core logic with framework dependencies. Learn how to enforce boundaries, use tools like Sheriff, and build maintainable apps faster.
Implementing Generative AI Responsibly: Governance, Oversight, and Compliance
Learn how to implement generative AI responsibly with governance, oversight, and compliance frameworks that prevent legal risks, bias, and reputational damage. Real-world strategies for 2026.