Author
Anton Macius
Field CTO
Anton Macius is a technology and product leader with experience spanning mobility, infrastructure, AI, and enterprise software platforms. Having worked with organizations including Gett and bp pulse, Anton has led and contributed to the development of high-scale operational systems, digital products, and modernization initiatives across multiple industries. Today, he focuses on building practical, automation-driven platforms in areas such as AI, public infrastructure, property operations, and intelligent workflow systems. Anton is passionate about combining strong engineering foundations with real-world operational impact, helping organizations simplify complexity and scale technology effectively.
13 posts by this author
Indirect Prompt Injection: The Document That Attacks Your Assistant
The most dangerous prompt injection doesn't come from the user — it hides in a document your AI retrieves. Indirect injection turns your own knowledge base into an attack surface. Here's how it works and how to neutralize it.
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Redacting PII at the Wire: Before the Prompt Ever Leaves Your Boundary
The safest place to remove personal data from an AI prompt is before it crosses your boundary. Redaction at the wire masks PII inbound and outbound as a runtime step, so the model gets the context it needs without the identifiers it doesn't.
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The 6 Attack Classes Every Enterprise LLM Faces
Enterprise AI faces a small, well-defined set of attacks on the wire: prompt injection, jailbreaks, data exfiltration, PII leakage, secret leakage, and unsafe tool calls. Here's what each looks like, and where it's caught.
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Why an AI Firewall Has to Be Deterministic, Not Another Model
An AI firewall inspects every prompt and completion crossing your boundary. For regulated enterprise AI it has to be deterministic — rule-based, repeatable, and auditable — not a second model guessing.
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Compiled Is Not Done.
The most dangerous word in autonomous software is “done.” A system that rewards activity ships nothing that works.
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Nobody Assigned This Work.
No sprint board. No manager. The work runs hot where it matters and cools where it doesn't — and the workers follow the heat.
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Drop a Spec. Ship a Feature.
The backlog used to be a queue of work waiting for engineers. Now it’s a queue of specifications waiting for a signature.
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The Organizational Memory Problem: Why Fast-Growing Companies Lose Their Institutional Knowledge
As an enterprise scales, the total amount it knows rises with headcount — but the share any one person can access falls. This article introduces the Knowledge Dilution Curve, names the four inflection points that concentrate knowledge risk, and explains how a Company Brain closes the gap before it becomes an operating problem.
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Enterprise RAG Implementation: The 8-Phase Deployment Playbook
An 8-phase project playbook for enterprise RAG — from use-case scoping and data audit through security review and production monitoring — based on Sphere's AI Foundry delivery path.
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RAG vs. Fine-Tuning: The Enterprise Decision Framework (2026)
An 8-criteria decision framework for choosing between RAG and fine-tuning for enterprise AI — with a real financial-services call-through.
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Compliance as Runtime — Sphere Quarterly · Issue 03
The audit binder is dead. The ledger is the binder. A field guide to making compliance a property of the runtime — every read, write, and AI decision signed by default — by the team that ships the reference implementation.
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The Self-Rewriting Site — Sphere Quarterly · Issue 02
One URL. Every visitor sees a different page. The memory belongs to them. A field guide to browser-resident engrams, declared visitor intent, and pages composed at view-time by the team that ships the reference implementation.
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Agent-Ready Sites — Sphere Quarterly · Issue 01
Your site has an API for humans (HTML). In 2026 it needs one for agents (MCP). A field guide to building marketing sites that LLM agents can actually call, by the team that ships the reference implementation.
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