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Field Notes

AI guides for business decision makers

Practical AI guides for company decision makers. Choose a first task, plan a small trial, compare suppliers and decide whether the result is worth paying for. No AI background is needed. Each guide separates source-backed facts from our assessments and recommendations.

Articles
20
Articles with source references
17
Classes
4

Customer education

14 articles

What the work is, what it costs, and when it is the wrong thing to buy. Written for the person deciding, not for the person building.

  1. 01What is a forward-deployed engineer?A forward-deployed engineer works inside your organisation for the length of a deployment: watching the actual workflow, choosing the smallest system that fixes it, building it on your infrastructure, and handing it over. This note describes the role, what it is not, and when it is the wrong thing to buy.reviewed 24 Aug 20264 sectionsMethod and judgement — nothing on this page is stated as a fetched fact.4 statements0 source references
  2. 02FDE, AI consultant, or software agency?Three suppliers sell overlapping things and price them differently. This note sets out what each one is accountable for, what you get at the end, and the question that separates them: who is responsible when the system is wrong in production.reviewed 24 Aug 20263 sectionsMethod and judgement — nothing on this page is stated as a fetched fact.3 statements0 source references
  3. 03AI pilot plan for small business: a four-week buying testChoose a first AI project, run a four-week trial, and decide whether to expand. A practical plan for owners who need useful work and clear costs.reviewed 6 Sep 20265 sections1 statement1 source reference
  4. 04How to measure AI ROI before expanding a pilotMeasure AI ROI using completed work, review time, adoption and full operating costs. Includes a worked example and an expansion checklist.reviewed 6 Sep 20265 sections1 statement1 source reference
  5. 05AI SaaS, API or private cloud: a buyer’s decision guideCompare a ready-made AI service, a model API, private cloud and an on-premise deployment using your workflow, data boundary and operating team.reviewed 6 Sep 20265 sections1 statement1 source reference
  6. 06AI procurement checklist: what to put in a supplier trialTurn an AI supplier demonstration into a reviewable purchase: define the workflow, test set, data boundary, acceptance criteria, full costs and exit handover.reviewed 6 Sep 20265 sections1 statement1 source reference
  7. 07Internal AI knowledge assistant: a company-document pilotTest an internal AI assistant using company documents, source ownership, permissions, citations and outdated policies. Includes a measurable pilot plan.reviewed 6 Sep 20265 sections1 statement1 source reference
  8. 08HR onboarding AI assistant: a practical pilot planPlan an HR onboarding assistant for approved policies and routine tasks, with source checks, human handoffs and clear boundaries for personal cases.reviewed 6 Sep 20265 sections1 statement1 source reference
  9. 09Manufacturing SOP AI assistant: a supervised pilotTest a manufacturing SOP assistant for correct equipment, document versions and permissions, with supervisor review and explicit stop criteria.reviewed 6 Sep 20265 sections1 statement1 source reference
  10. 10AI for school administration: notices and routine enquiriesPlan AI help for school notices and routine enquiries using approved sources, bilingual review, privacy boundaries and measurable pilot criteria.reviewed 6 Sep 20265 sections1 statement1 source reference
  11. 11Customer support AI pilot: replies with a human handoffTest customer support AI with reviewed drafts, approved sources and human escalation. Measure resolved cases, review time and consequential errors.reviewed 6 Sep 20265 sections1 statement1 source reference
  12. 12Invoice processing AI pilot: from PDF to reviewed recordTest invoice AI using field accuracy, duplicate checks, exceptions and finance review. Includes a worked pilot and criteria for approving draft records.reviewed 6 Sep 20265 sections1 statement1 source reference
  13. 13AI tender and proposal workflow: draft with approved evidenceUse AI to organise tender requirements and draft from approved evidence. Keep eligibility, pricing, commitments and submission under accountable human review.reviewed 6 Sep 20265 sections1 statement1 source reference
  14. 14Logistics document AI pilot: extraction with human reviewTest logistics document AI for shipment matching, units, versions and source accuracy, with operator approval, an exception queue and clear stop criteria.reviewed 6 Sep 20265 sections1 statement1 source reference

Technical

2 articles

How a deployment is actually put together, and what the choices trade against.

  1. 01How to deploy a private company ChatGPTThe shortest honest path from "we want our own ChatGPT" to a system employees use: what the four moving parts are, which decisions are irreversible, and the two places every one of these deployments gets stuck.reviewed 24 Aug 20264 sections7 statements5 source references
  2. 02Open WebUI, AnythingLLM, Onyx: which is for whatThree self-hostable projects that all get described as "private ChatGPT" and are built for three different jobs. What each one is actually shaped for, the licence differences that matter, and how to choose without installing all three.reviewed 24 Aug 20264 sections11 statements6 source references

Compliance

2 articles

Issue-spotting for the questions that decide whether a deployment is allowed to exist. Not legal advice.

  1. 01Data residency is not the same as complianceChoosing an EU region does not make a deployment lawful under the GDPR, and keeping data in Hong Kong does not answer the PDPO. Residency answers one question — where the bytes sit. This note sets out the other questions it leaves open, with the text of each instrument behind them.reviewed 24 Aug 20264 sections14 statements10 source references
  2. 02Questions to ask before adopting an AI vendorEleven questions, in the order that saves the most time, with what a usable answer looks like. Written for the person who has to sign, and structured so that four of the eleven can be checked from the vendor’s own published pages before the first call.reviewed 24 Aug 20263 sections8 statements6 source references

FDE practice

2 articles

How the work is done: observing, scoping, deploying, handing over.

  1. 01Observe the workflow before choosing the technologyThe first three days of a deployment decide most of it. This note describes what to watch, what to write down, and the four questions that turn an observation into a scope — plus the two signals that mean the project should not be an AI project at all.reviewed 24 Aug 20264 sectionsMethod and judgement — nothing on this page is stated as a fetched fact.3 statements0 source references
  2. 02Handing over an AI system responsiblyA deployment that only its builder can operate has not been delivered. This note sets out what has to exist at handover — runbook, evaluation set, ownership, upgrade path, and the decision log — and why human oversight is a duty to staff rather than a line in a slide.reviewed 24 Aug 20264 sections6 statements2 source references