THE ARCHIVE
The previous edition.
Previous articles remain available here. They target experienced AI developers and are no longer updated daily.
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ARCHIVE
Previous edition
Evaluation-Driven Development: Agent Behavior as a Release Contract
Treat agent behavior like software quality: version representative scenarios, score tool use and outputs, and make critical regressions CI release gates.
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ARCHIVE
Previous edition
AI Engineering Trends: Vulkan kernel fusion, agent evaluation, vector operations
Three verified AI engineering updates: llama.cpp’s Vulkan kernel fusion, portable agent evaluation, and Weaviate MCP and vector-operation changes—with practical guidance for software teams.
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Previous edition
Backend-Specific Kernel Fusion: When the Execution Plan Becomes the Bottleneck
Model size is not the whole inference-performance story. Backend-specific kernel fusion reduces GPU dispatches and intermediate-memory traffic by combining operation chains into specialized execution regions.
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Previous edition
AI Engineering Trends: Runtime conformance fixes and context controls
Today’s key AI engineering developments, verified against primary sources and distilled into practical guidance for software teams.
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ARCHIVE
Previous edition
Inference Correctness: When a Model Runs but Computes the Wrong Thing
A model loading successfully in a new runtime does not prove equivalent computation. Learn how to define, test, and operate cross-runtime inference correctness.
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ARCHIVE
Previous edition
AI Engineering Trends: GenAI telemetry, agent memory, inference serving
The day’s key AI engineering developments, verified against primary sources and distilled into practical guidance for software teams.
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Previous edition
Semantic observability: make AI traces explainable
OpenTelemetry’s evolving GenAI conventions provide shared fields for model calls, agents, tools, retrieval, and token use. Learn how to improve diagnosis without confusing telemetry with quality evaluation.
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Previous edition
AI Engineering Trends: Plan validation, DR executors, shell boundaries
Three verified AI engineering developments: stale-plan validation, deterministic disaster-recovery execution, and stronger agent CLI shell boundaries.
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ARCHIVE
Previous edition
Agent Harnesses: The Control Layer Behind Production AI Agents
An agent harness separates model decisions from the tools, permissions, execution environments, state, and recovery logic needed to run agents safely in production.
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ARCHIVE
Previous edition
AI Engineering Trends: Agent Sandbox hardening and evaluation operations
Three verified developments for software teams: isolated agent execution, Gemini CLI security hardening, and operational evaluation workflows in Langfuse.
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ARCHIVE
Previous edition
AI Engineering Trends: Governed plugins, managed MCP, trajectory evaluation
Three verified AI engineering developments: governed plugin marketplaces, organization-managed MCP, and trajectory-aware agent evaluation.
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ARCHIVE
Previous edition
AI Engineering Trends: KV-Cache Performance, Agent Evaluation, and AgentOps
Three verified AI engineering developments on KV-cache performance, production agent evaluation, and AgentOps for software teams.
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ARCHIVE
Previous edition
AI Engineering Trends: Agent Evaluation, Registry Governance, and MCP Discovery
Three verified developments for software teams: portable agent evaluation, governed capability catalogs, and stateless MCP discovery.
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ARCHIVE
Previous edition
Trace-Based Evaluation: Use Agent Execution Traces as a Test Interface
Trace-based evaluation uses structured telemetry from model calls, tools, retrieval, memory, and orchestration to assess an agent’s execution path—not just its final answer—across frameworks.
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ARCHIVE
Previous edition
Capability Mediation: The Missing Control Plane for Agent Tools
Giving an agent tool access is easy. Keeping every call safe as sessions, sandboxes, credentials, and subagents change requires a mediation layer.
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Previous edition
Agent Containment Lessons and SDK Migration Notes for OpenAI and Anthropic
OpenAI’s agent-containment incident, OpenAI Node 7.8.0 telemetry and identity changes, and Anthropic TypeScript SDK 0.122.0 migration checks for production teams.
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ARCHIVE
Previous edition
An Agent Sandbox Is Not a Security Boundary
Agentic security boundaries apply zero-trust thinking to model-driven systems: constrain every tool, credential, service, network path, and handoff outside the model itself.
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ARCHIVE
Previous edition
Agent security, vLLM 0.28.0, and confidential AI evaluations
A technical briefing on the Hugging Face agent-security incident, vLLM 0.28.0 serving changes, and confidential-computing patterns for AI evaluations.