Tri-City AI Links
Generative AI in Insurance Claims: Triage, Letters, and Fraud Detection
Discover how generative AI transforms insurance claims via automated triage, personalized letters, and advanced fraud detection. Learn about real-world applications, accuracy rates, and the shift toward agentic AI in 2026.
Vibe Coding Model Selection: Claude vs GPT-4 vs Gemini
Stop wasting money on the wrong AI. Learn how to strategically select between Claude, GPT-4, and Gemini for vibe coding to cut costs and boost efficiency.
Math-Specialized LLMs vs General Models: Accuracy & Cost
Compare math-specialized LLMs against general models. Discover how Qwen2.5-Math rivals GPT-4 in accuracy at a fraction of the cost, and learn why RL training beats SFT.
Rate Limiting and Abuse Detection for LLM Endpoints: A Practical Guide
Learn how to protect LLM endpoints from abuse and cost overruns. Discover why token-aware rate limiting beats simple RPM rules and how to implement defense-in-depth.
Product Design with Multimodal Generative AI: Rapid Prototypes and Iterations
Discover how multimodal generative AI transforms product design by merging text, images, and data for rapid prototyping. Learn the 6-stage workflow, see real-world benefits, and avoid common pitfalls.
Migrating Between LLM Providers: How to Avoid Vendor Lock-In in 2026
Stop renting intelligence. Learn how to migrate between LLM providers using model-agnostic proxies and self-hosted infrastructure to cut costs, reduce latency, and escape vendor lock-in.
BERT vs GPT: Encoder-Only vs Decoder-Only Paths to Language Understanding
Discover the key differences between BERT and GPT. Learn how encoder-only vs decoder-only architectures impact language understanding, generation, and implementation costs.
Benchmarking Scaling Outcomes: Measuring Returns on Bigger LLMs
Discover how to measure true returns on scaling LLMs. Move beyond generic benchmarks to performance-per-dollar analysis, avoiding data contamination pitfalls.
Few-Shot Learning with Prompts: How Example-Based Instructions Improve Generative AI
Learn how few-shot learning boosts generative AI accuracy by providing examples instead of complex instructions. Discover best practices for crafting prompts, when to choose it over fine-tuning, and real-world applications.
Use Case Discovery for Generative AI: Sizing and Prioritizing Opportunities
Learn how to discover, size, and prioritize generative AI use cases. Move beyond hype to measurable business value with practical frameworks and real-world data.
Transformer Depth vs Width: Choosing the Right Architecture for LLMs
Discover how transformer depth vs width impacts LLM performance. Learn when to prioritize parallel speed with wide models or sequential reasoning with deep architectures.
Allocating LLM Costs Across Teams: Chargeback Models That Work
Learn how to effectively allocate LLM costs across teams using proven chargeback models. Discover why traditional cloud metrics fail for AI, how to handle RAG and agent costs, and steps to build a transparent billing system.
