Thirty-two articles. One through-line: Operations → Automation → AI → Data.

If you landed here from a single post, this guide shows where it fits — and what to read next without getting lost in topics that overlap.

At a glance

  • Start with pain you recognize (Series 1) before buying tools
  • Automate with discipline (Series 2) before adding AI
  • Build AI literacy (Series 3), then run pilots (Series 4) with governance (Series 5)
  • Perspectives, security, and technical notes are appendices — read when relevant

The through-line

Every article on this site supports the same promise: less repetitive work, more human value. Technology is not the starting point — how work actually happens is.

Operations → Automation → AI → Data
     ↑                              │
     └──────── governance ──────────┘

Governance (human review, privacy, change) wraps the path — not a separate project at the end.

How to use this library

You are…Start hereThen
Executive wondering if AI is hypeWhy AI adoption failsProgressive AI for SMBs → Measuring AI ROI
Operations lead drowning in adminFirefighting modeMap friction → Meeting notes pilot
Field / construction managerConstruction field assistantHuman in the loop
IT or digital leading adoptionWhen automation failsAI governance for SMBs → Change management
Quebec organizationAI in QuebecIs our data safe with AI?

Series 1 — Understand real work

Before automating or adding AI, see where time and quality leak.

  1. Firefighting mode — unplanned work vs planned work
  2. Technical debt and unplanned work
  3. The hidden cost of technical debt
  4. Map friction before buying tools

Series 2 — Automate with discipline

Spot wins, estimate real cost, avoid “tool” failures.

  1. Too small for automation?
  2. Spot automation opportunities without a big project
  3. When automation fails (it's rarely the technology)
  4. Automation budget: what it really costs
  5. Start automation without disrupting everything

Series 3 — Understand AI without hype

Framework, prompts, context, capabilities — before a platform purchase.

  1. Progressive AI for SMBs
  2. Will AI replace our employees?
  3. Why AI adoption fails: five pitfalls
  4. Why prompt context matters
  5. Prompting tips for leaders
  6. Context is everything in AI
  7. Multimodal AI for business
  8. Building company knowledge bases (RAG)
  9. Autonomous AI agents and workflows

Series 4 — Concrete pilots

First measurable workflows — always with human validation.

  1. Meeting notes: a low-risk first win
  2. Construction AI field assistant
  3. Measuring AI ROI

Series 5 — Govern and sustain

People, privacy, policy — so pilots survive contact with reality.

  1. Human in the loop
  2. Is our data safe with AI?
  3. AI governance for SMBs
  4. Change management for AI adoption

Appendices

Perspectives: AI in Quebec · 25 years in tech · State of AI (2018 talk) · Microsoft AI research (BBC)

Security: Security-first culture · Security journey · Cybersecurity is everyone's responsibility

Technical: SQL Azure compatibility level

One recommendation

If you only read four articles this month:

  1. Map friction before buying tools
  2. Progressive AI for SMBs
  3. Meeting notes: first AI win
  4. Human in the loop

That sequence mirrors how I work with clients: see the work → adopt progressively → pilot one flow → keep humans accountable.

Not sure where you fit? Book a short conversation — we'll map one realistic first step, not a platform overhaul.