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Hybrid search + reranking for RAG isn’t a free win: prove it with margin‑gated evals (or don’t ship it)
AI Engineering • Aug 31, 2026

Hybrid search + reranking for RAG isn’t a free win: prove it with margin‑gated evals (or don’t ship it)

Hybrid (BM25 + vectors) plus a cross‑encoder reranker is now the default RAG advice, but it can make real systems worse. Here’s a practical, eval-driven way to decide when to rerank using similarity margins and failure-mode buckets.

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The Permission Boundary Pattern: least-privilege tool-using agents without keys to prod
AI Engineering • Aug 30, 2026

The Permission Boundary Pattern: least-privilege tool-using agents without keys to prod

Tool-using agents fail differently to chatbots: they can cross system boundaries. The Permission Boundary Pattern gives you an implementable blueprint for agent identities, per-tool scopes, short-lived credentials, and end-to-end auditability so overreach is detectable and revocable.

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Hybrid retrieval for RAG is the new baseline: stop vector-only failing on SKUs, error codes and policy text
AI Engineering • Aug 29, 2026

Hybrid retrieval for RAG is the new baseline: stop vector-only failing on SKUs, error codes and policy text

Vector-only RAG fails in predictable places: IDs, SKU-like tokens, exact clauses and compliance language. A production hybrid stack (BM25 + dense + reranking + ACL-aware filtering) fixes this, and you can prove it with a simple evaluation harness.

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Model Context Protocol (MCP) integration patterns in the wild: secure, debuggable tool access without a shadow API layer
AI Engineering • Aug 28, 2026

Model Context Protocol (MCP) integration patterns in the wild: secure, debuggable tool access without a shadow API layer

Teams are adopting MCP to standardise tool access for agents, but the hard part is governance: auth, failure behaviour, observability, and versioning. This article covers the integration patterns that keep MCP tool estates secure, debuggable, and maintainable in production.

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How to replace a support triage channel: in-thread, tool-using agents that actually close the loop
AI Engineering • Aug 28, 2026

How to replace a support triage channel: in-thread, tool-using agents that actually close the loop

Your agent is great until it hits a messy inbox: the hard part is not the model, it’s routing, permissions, handoffs, and getting to a real ‘done’ without inventing a new queue. This article lays out a concrete pattern for in-thread, tool-using resolution that keeps work where it started and makes outcomes auditable.

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Production LLM agents need an incident budget: OpenTelemetry tracing, eval gates, and span limits
AI Engineering • Aug 27, 2026

Production LLM agents need an incident budget: OpenTelemetry tracing, eval gates, and span limits

Agentic automation fails in production for boring reasons: you can’t diagnose incidents without drowning in traces, and you can’t ship changes without regression gates. This is a practical playbook for OTel-first tracing, span/trace volume controls, and evals as release gates so on-call can actually operate the system.

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The Durable Agent stack: why agentic automations break at 2am (and how to fix them with resumable workflows)
AI Engineering • Aug 26, 2026

The Durable Agent stack: why agentic automations break at 2am (and how to fix them with resumable workflows)

Most agent demos fail in production for the same boring reasons: retries, partial failure and missing state. A ‘durable agent’ stack treats agents as long-running workflows with checkpoints, idempotent tools and an audit trail you can trust.

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