All field notes

Chatbots earn their place when they resolve issues rather than deflect them. Here is what to specify and how to measure it.

Chatbot platforms are judged on escalation and context access more than on conversation quality. This guide covers what to compare — and whether chat fits.

Vision projects succeed on data collection and edge conditions rather than on model architecture. Here is what to commission.

Your CRM vendor has added AI features. This guide covers evaluating them honestly against standalone tools, and the governance questions nobody asks.

ERP AI features operate on data with financial and regulatory consequence. This guide covers verifying accuracy, controls, and auditability before enabling them.

Generative AI features succeed on evaluation, latency and cost discipline rather than on model choice. Here is what to commission.

Customers do not trust agents because they are told to. This guide gives leaders the design patterns that earn customer trust, the disclosure and recourse customers expect, a sequencing that grows trust with scope, and how to measure it.

Hiring an AI leader is hard because the credentials that look impressive rarely predict delivery. This guide gives executives the questions that reveal production experience, the red flags, and what to ask referees.

An evaluation report is the main evidence executives receive about whether an AI system works. This guide shows how to read one: what the pass rate hides, how to test the test set, and what the failure analysis reveals.

Leaving an AI vendor is harder than leaving most software vendors, because the assets are prompts, connectors, and evaluation data. This guide covers what to recover, in what order, and how to avoid repeating the dependence.

Executives without technical depth still have to judge whether their AI team is capable. This guide gives observable signals: the artifacts, the failure handling, the refusals, and the impressive signs that mean nothing.

ITSM AI features promise deflection and triage. This guide covers measuring them honestly and the knowledge quality that decides whether they work.

A knowledge base feeding an AI system needs structure, ownership, and freshness controls. This guide covers what to compare beyond authoring convenience.

Marketing AI produces volume easily and accuracy rarely. This guide covers brand consistency, claim substantiation, and measuring whether it actually works.

AI proposals die in finance review for predictable reasons. This guide gives the questions a competent CFO will ask, what a strong answer contains, and how to prepare before the meeting.

Security review is where AI deployments stall, usually because the team cannot answer basic questions about permissions and data. This guide gives the questions a competent CISO asks and what a good answer contains.

AI programs rarely fail loudly; they accumulate symptoms. This guide gives executives ten observable signs, what each actually indicates about the underlying problem, and the correction that addresses it.

Executives get plenty of advice on AI failure and little on what success actually looks like early. This guide gives ten signs a program is working, including the second-order ones that appear before the financial results.

Voice systems are judged on latency and interruption handling before accuracy. Here is what to specify and what to test.

Voice agents succeed or fail on latency and interruption handling, not on how the voice sounds. This guide covers what to compare.

Most executive misconceptions about agents are reasonable inferences from how AI is marketed. This guide corrects the ten most consequential ones and shows what each correction changes about the decisions being made.

The first hour of an AI incident decides whether it is a contained event or a story. This guide gives executives a sequence for that hour: contain, assess, assign, communicate, preserve, and the five mistakes to avoid.

When an agent sends the wrong email or approves the wrong payment, the question arrives fast: whose fault is this? This guide gives executives an accountability model by layer, what vendors do and do not carry, and the records that matter.

Org charts were drawn for a world where all work was done by people. This guide shows executives how agentic AI changes spans, layers, team composition, and the shape of functions, and how to sequence the redesign without breaking what works.