Llama 4 Behemoth and the State of Open Weights in 2026
Llama 4 Behemoth shifted what open-weights models can do. Where the open frontier stands in 2026 and how the gap to closed models has narrowed.
8 min read
Agentic AI & LLMs
Agentic AI & LLMs archive page 247 of 631
Agentic AI & LLMs
Agentic AI, LLM engineering, and the models behind modern automation — multi-agent systems, LLM evaluation and comparisons, RAG, fine-tuning, AI infrastructure, security, and production AI engineering.
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Mamba-3 and State-Space Models: The Post-Transformer Architecture Race in 2026
Mamba-3 and the state-space-model family now power production deployments. Where they beat transformers, where they lose, and what's next.
9 min read
Mixture of Depths: Adaptive Compute per Token for Cost-Efficient LLMs
Mixture of Depths lets models skip layers for easy tokens and spend compute on hard tokens. The 2026 implementations and what they save.
8 min read
Model Cards and System Cards 2026: What Regulators Now Expect by Default
Model cards graduated from research norm to regulatory expectation in 2026. The new schema, what to disclose, and what to keep proprietary.
8 min read
Model Latency Profiles by Provider: TTFT, TPS, and p99 in 2026
Headline tokens-per-second numbers hide what matters. The 2026 latency profiles by provider — TTFT, TPS, and p99 — for production planning.
7 min read
Multi-Hop RAG: Designing Retrieval Pipelines for Complex Questions
Multi-hop questions break naive RAG. The 2026 retrieval patterns that handle 'who is the manager of the engineer who shipped Y' style questions.
8 min read
Multi-Provider Failover: Patterns That Don't Drop Quality
Multi-provider failover protects against outages but can drop response quality. The 2026 patterns that preserve both reliability and quality.
7 min read
Negative Prompts and Constraint Engineering for Safety
Telling the model what not to do is its own discipline. The 2026 patterns for negative prompts, constraint engineering, and safe behavior.
7 min read
NIST AI RMF Generative Profile: Mapping Controls to Your LLM Stack
NIST's generative-AI profile updated the AI Risk Management Framework. How to map its controls to a real LLM stack in 2026.
8 min read