Explore fresh perspectives and expert takes on design, development, and digital innovation.
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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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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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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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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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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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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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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Outsourcing software development has one of the widest quality distributions of any business decision an organization can make. Done well, it is transformative. Done poorly, it is catastrophic. The difference between those two outcomes is not luck.
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Software as a service has become such a familiar business model that it is easy to underestimate what actually goes into building one that works. Building a SaaS product that scales is one of the more challenging business and engineering endeavors in modern software.
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