AI EngineeringJun 1, 20268 min read
Shipping production RAG: what actually breaks at scale
Retrieval looks easy in a demo and hard in production. Here is the architecture we reach for, and the failure modes we design around.
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Field notes on shipping production AI.
Engineering practices, product thinking, and lessons from the systems we build. No hype, just what works.
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9 articlesAI Engineering
Cloud & SecurityMay 27, 20266 min read
Guardrails first: securing AI workloads from day one
Encryption, access control, and observability are not afterthoughts. A practical checklist for AI systems handling sensitive data.
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ProductMay 20, 20267 min read
From prototype to product: the first ninety days
The gap between a working demo and a product your business runs on is mostly process. Here is how we close it.
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IndustryMay 13, 20265 min read
Why emerging-market fintech needs different tooling
Legacy RegTech was built for US and EU enterprises. We unpack what changes when you build for everyone else.
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AI EngineeringMay 6, 20269 min read
Evaluating LLM output without fooling yourself
Vibes are not a metric. A grounded approach to evals, regression suites, and guardrails for language-model features.
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Case NotesApr 29, 20266 min read
Four portals, one backend: an architecture story
How we modeled role-based access across business, sales, developer, and testing portals on a single shared API.
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CompanyApr 22, 20264 min read
How we keep engineer turnover low
The people who learn your product should stay on it. A look at how we build teams that last.
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ProductApr 15, 20265 min read
Designing dashboards people actually check
Most dashboards get opened once. We share the patterns that turn analytics into a daily habit for teams.
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Cloud & SecurityApr 8, 20267 min read
Serverless event pipelines that stay cheap at scale
Durable, event-driven workflows without a queue to babysit. The stack we use to keep real-time delivery affordable.
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