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Ideas for operating AI in the real world.

From the field

Clear frameworks, engineering practices, and operating lessons for enterprise teams moving from AI ambition to dependable work.

8 field notes · 8 practices

FeaturedAI Agents / 8 min read

From Copilots to AI Employees: A Practical Enterprise Operating Model

An AI employee is not a general-purpose chatbot. It is a governed agent with a defined role, approved knowledge, permitted tools, measurable outcomes, and explicit human escalation.

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AI AgentsVoice AIEnterprise AutomationWhatsApp AutomationLegal TechnologyKnowledge SystemsAI EngineeringRAG

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Field notes

7 min read

What Makes an Enterprise Voice AI Agent Production-Ready?

Production voice AI must manage timing, interruptions, noisy inputs, tool failures, escalation, and multilingual quality—not merely produce a convincing synthetic voice.

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6 min read

How to Choose the First Workflow for Enterprise AI Automation

The best first AI workflow is frequent, measurable, bounded by clear rules, and painful enough that teams will participate in redesigning it.

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7 min read

Designing WhatsApp Automation That Customers Actually Want to Use

Useful WhatsApp automation resolves a clear customer need, minimizes repeated questions, completes a workflow, and offers a visible path to a person.

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8 min read

A Safe Operating Model for AI-Assisted Contract Review

AI can accelerate first-pass contract review, but source visibility, approved playbooks, reviewer authority, and auditability must remain explicit.

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7 min read

Building an Enterprise Knowledge System People Can Trust

A trustworthy knowledge system needs ownership, permissions, freshness, citations, and feedback—not only a search box connected to documents.

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8 min read

Evaluation-Driven Development for Reliable AI Systems

Evaluation-driven development turns business requirements and production failures into repeatable tests that guide model, prompt, retrieval, and workflow changes.

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7 min read

RAG in Production: Retrieval Quality Matters More Than Prompt Tricks

A production RAG system succeeds when it retrieves the right permitted evidence consistently; prompt polish cannot recover information that was never found.

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