Insights

Engineering notes, not thought leadership.

Everything here is written by the people building the systems: architecture decisions, evaluation methods, integration realities and the cases where AI is the wrong answer.

Latest

Why most AI agents never make it into production

Prototype agents fail on the axes a demo never measures: reliability, permissions, observability and cost. A look at where the gap actually sits.

Agentic AI

Why most AI agents never make it into production

Prototype agents fail on the axes a demo never measures: reliability, permissions, observability and cost. A look at where the gap actually sits.

Argbit Engineering2026-07-149 min read

Architecture

Designing reliable agentic systems

Orchestration, memory and tool boundaries decide whether an agentic system is dependable. Architecture patterns we return to repeatedly.

Argbit Engineering2026-06-2811 min read

MCP

MCP in the enterprise: architecture, security and governance

The Model Context Protocol makes tool access uniform. That uniformity is exactly why enterprises need a gateway, a permission model and an audit trail.

Argbit Engineering2026-06-0512 min read

All writing

Agentic AI

Why most AI agents never make it into production

Prototype agents fail on the axes a demo never measures: reliability, permissions, observability and cost. A look at where the gap actually sits.

Argbit Engineering2026-07-149 min read

Architecture

Designing reliable agentic systems

Orchestration, memory and tool boundaries decide whether an agentic system is dependable. Architecture patterns we return to repeatedly.

Argbit Engineering2026-06-2811 min read

MCP

MCP in the enterprise: architecture, security and governance

The Model Context Protocol makes tool access uniform. That uniformity is exactly why enterprises need a gateway, a permission model and an audit trail.

Argbit Engineering2026-06-0512 min read

Automation

When not to use an AI agent

Many workflows presented as agent problems are better served by a queue, a rules engine or a well-designed form. How we make the call.

Argbit Engineering2026-05-197 min read

Evaluation

Evaluating AI systems beyond accuracy

Accuracy on a static set says little about an operational system. What we measure instead: task completion, escalation quality, latency, drift and cost.

Argbit Engineering2026-04-3010 min read

Enterprise AI

The architecture of enterprise AI automation

Where deterministic workflow engines end and AI reasoning begins — and how to connect both to the systems where the work actually lives.

Argbit Engineering2026-04-0813 min read

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