News & Analysis

Original, in-depth articles on AI engineering, product reliability, and practical technology strategy.

January 16, 2026 · 18 min read

AI Safety Governance in 2026: Moving Beyond Compliance Checklists

As AI systems become more capable, organizations need comprehensive safety frameworks that go beyond regulatory compliance. Explore practical approaches to risk assessment, monitoring, and incident response.

SafetyGovernanceRisk ManagementCompliance
AI Safety Governance in 2026: Moving Beyond Compliance Checklists
Prompt Engineering Patterns for Production: A 2026 Field Guide
January 12, 2026 · 20 min read
Prompt Engineering Patterns for Production: A 2026 Field Guide
Effective prompting combines structure, examples, and constraints. Explore battle-tested patterns for tool use, reasoning chains, output formatting, and error handling.
Vector Search at Scale: Indexing, Quantization, and Hybrid Retrieval
January 11, 2026 · 18 min read
Vector Search at Scale: Indexing, Quantization, and Hybrid Retrieval
Building fast, accurate vector search systems requires understanding index types, quantization trade-offs, and when to combine dense and sparse retrieval. Here's what works in production.
Debugging AI Systems: Observability for Non-Deterministic Behavior
January 10, 2026 · 16 min read
Debugging AI Systems: Observability for Non-Deterministic Behavior
Traditional debugging assumes determinism. AI systems require new tools: trace capture, prompt versioning, output comparison, and statistical analysis of failure modes.
Synthetic Data Generation: When and How to Bootstrap Training Sets
January 9, 2026 · 14 min read
Synthetic Data Generation: When and How to Bootstrap Training Sets
Synthetic data can accelerate development and fill gaps in real data, but quality is critical. Learn practical approaches for generation, filtering, and validation.
Model Evaluation Frameworks: Beyond Accuracy Metrics
January 8, 2026 · 17 min read
Model Evaluation Frameworks: Beyond Accuracy Metrics
Choosing the right evaluation metrics determines what your model optimizes for. Explore frameworks for measuring reasoning, safety, style, and user satisfaction.
Compute Efficiency After Scaling: The New Frontier for 2026 LLMs
January 7, 2026 · 8 min read
Compute Efficiency After Scaling: The New Frontier for 2026 LLMs
Model capability gains are increasingly constrained by cost. The next wave of progress is coming from efficiency: smarter training curricula, selective computation, distillation, and inference-aware architectures.
Tool-Using Agents in Production: Reliability Patterns That Actually Work
January 6, 2026 · 9 min read
Tool-Using Agents in Production: Reliability Patterns That Actually Work
Agents are easy to demo and hard to operate. Here’s a reliability-focused blueprint: constrained actions, observable state, evaluation gates, and safe fallbacks.
Private RAG in 2026: Minimizing Data Exposure Without Losing Quality
January 5, 2026 · 10 min read
Private RAG in 2026: Minimizing Data Exposure Without Losing Quality
RAG can leak data through prompts, logs, and retrieval. The modern approach is defense-in-depth: least privilege, scoped retrieval, redaction, and auditability.
Inference Economics With Long Context: KV Cache, Batching, and Cost per Task
January 4, 2026 · 8 min read
Inference Economics With Long Context: KV Cache, Batching, and Cost per Task
Long context is powerful, but expensive. Understanding KV cache growth, batching limits, and prompt design is the fastest path to cutting cost without cutting quality.
Multimodal Provenance: Why Image Workflows Need Metadata and Traceability
January 3, 2026 · 7 min read
Multimodal Provenance: Why Image Workflows Need Metadata and Traceability
As image generation and editing becomes routine, provenance is moving from “nice-to-have” to table stakes. Build pipelines that keep source, edits, and permissions auditable.
On-Device AI vs API Models: When Small Models Win
January 2, 2026 · 6 min read
On-Device AI vs API Models: When Small Models Win
On-device models trade absolute capability for latency, privacy, and offline robustness. For many UX paths, that trade is exactly what you want.
AI Compliance Without Fear: A Practical Checklist for Product Teams
January 1, 2026 · 9 min read
AI Compliance Without Fear: A Practical Checklist for Product Teams
Compliance is easiest when it’s built into engineering: clear data flows, retention rules, user controls, and audit logs.
Synthetic Data Quality: Metrics Beyond “Looks Real”
December 31, 2025 · 7 min read
Synthetic Data Quality: Metrics Beyond “Looks Real”
Synthetic data is only useful when it improves downstream performance. Measure coverage, fidelity, bias, and leakage—then test on real-world holdouts.
Open-Weight Models: Governance, Fine-Tuning, and Safety Gates
December 30, 2025 · 8 min read
Open-Weight Models: Governance, Fine-Tuning, and Safety Gates
Open-weight models expand innovation, but they require stronger governance: provenance, fine-tune controls, and deployment-time safety checks.
Prompt Injection and Data Exfiltration: Threat Modeling for LLM Apps
December 29, 2025 · 9 min read
Prompt Injection and Data Exfiltration: Threat Modeling for LLM Apps
Prompt injection is an app-layer security problem. Fix it with compartmentalization, strict tool boundaries, and a “never trust retrieved text” mindset.