The Security Architecture Behind Reliable AI Agents
A practical guide to AI agent security architecture: least privilege, untrusted input handling, sandboxing, tool gating, observability…Continue reading on Towards AI »
26 stories
A practical guide to AI agent security architecture: least privilege, untrusted input handling, sandboxing, tool gating, observability…Continue reading on Towards AI »
A technical reflection on why data scientists need software engineering principles when AI agents write code. The post A Scaffold at the Gate: Building AI Applications That Can Evolve appeared first on Towards Data Science.
In my previous Radar article, “Architectural Guardrails for AI-Generated Code,” I argued that AI coding agents need a layer that can hold architectural decisions in a structured corpus, retrieve the relevant ones, put them into the agent’s context before it writes code, and enforce explicit…
In my previous article, I explored executor independence: the idea that different execution mechanisms should be able to satisfy the same operational specification. By executor independence, I mean th
The Context Bleed: Why LLMs Fail at Patient Privacy When multi-tenant agent runtimes share memory buffers across concurrent clinic sessions, a routine ear infection summary leaks another patient’s …
The $80,000 Hallucination: Why RAG Fails at Healthcare Eligibility Verification Reading comprehension is not transactional verification. When an autonomous intake bot checks a static PDF brochure …
A phased agentic workflow that centralizes interpretation while preserving execution authorityContinue reading on Towards AI »
In this video, I walk through how a good architect handles a vague business problem: running business discovery, turning vague words into measurable numbers, defining success criteria, finding the real problem the client never mentioned, doing technical discovery (replatform vs refactor vs…
The 25mg Refill: Why Language Models Cannot Handle Clinical Math When an autonomous portal bot parses informal patient language to clear an inbox ticket, an ambiguous message becomes a five-fold …
A bank spent six months building a beautiful new UI to fix its flat loan book. Nothing changed. Drop-off stayed at 35%. What went wrong? The problem was solved before it was understood.
In my previous article, I argued that software automation needs a layer between operational intent and execution. The reason is simple: the specification should describe what success means, and the ex
Two ideas get welded together in a lot of engineering rooms, and the weld is wrong. Someone says “we’re going multi-tenant,” and within a…Continue reading on Towards AI »
Your Agent’s Memory Is a Liability: Track State, Not History There is a French draft in one of my test apps that I keep like a fossil. Article 96924661: a title, a slug, zero paragraphs. A June …
Making Intent Routing Explainable: Calibrated Probabilities, Decision Records and a Four-Tier Cascade
When an autonomous receptionist schedules an acute myocardial infarction for next Tuesday, the failure isn’t conversational intelligence — it’s architectural negligence. Here is how to engineer deterministic triage interceptors.
SoPhi Harness— Hands that Don’t Freeze: A Tool Interface Built For a Future it Hadn’t Earned Yet Series: Building SoPhi — a Kotlin Agent Harness — Article 06 A line cook working a busy pass …
AgenticSystemCore: a folder of Markdown texts that people and agents can use in multiple ways Existing technologies for future simpler combined understanding and use An open format that turns plain …
The following article originally appeared on Vanishing Gradients and is being republished here with the authors’ permission When an AI agent can explore a dataset, choose a modeling approach, run the analysis, and explain its findings, what should the data scientist do?
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