AI at Work: Two-Guide Content Production Session
**Date:** 2026-04-08
**Duration:** ~25 minutes
**Repos touched:** assortedLLMTasks
Context & Motivation
User wanted to create shareable guides for non-technical people on how to use AI effectively. The work evolved across three iterations:
- Initial request: “Share a walkthrough of how to set up this environment for a non-technical person who hasn’t done anything like this before, with prompting and context best practices.”
- Pivot: User realized a corporate audience wouldn’t have the same freedom to install CLI tools and set up their own environment. Requested a second guide focused on applying AI in a work context — web interfaces, corporate tooling, building custom tools without coding.
- Enrichment: User asked “Are there any more specifics from my implementations that would be useful to mention/include?” — triggering a deep exploration of the memory system, feedback rules, guidance files, and project implementations to extract transferable lessons.
- Decision: Keep the CLI setup walkthrough as-is and create a separate work-focused guide rather than merging them
- Alternatives considered: Rewriting the first guide to be more generic; adding a “corporate” section to the original
- Rationale: The audiences are fundamentally different. Someone setting up their own Claude Code environment has different needs than someone using claude.ai through a company plan. Merging would dilute both.
- Trade-offs: Some prompting content overlaps between the two guides
- Decision: Drew from actual implementation mistakes and learnings (verify-before-asserting, dual-persist, graduated autonomy, pipefail bug, bakeoff results) but anonymized them for the corporate audience
- Alternatives considered: Keeping it fully generic; linking directly to the specific implementations
- Rationale: Generic advice (“be specific in your prompts”) is everywhere. Real stories with real consequences are what make a guide stick. But the audience doesn’t need to know about Discord webhooks or autonomous dev agents.
- Trade-offs: Lost some specificity in anonymizing, but gained relatability
- Decision: Introduced CRAFT (Context, Role, Action, Format, Tone) as the prompting mental model
- Alternatives considered: Using existing frameworks (RISEN, CO-STAR, etc.)
- Rationale: CRAFT is simple enough to remember and covers the five things that matter most. The acronym is intuitive and the letters map to natural questions you’d ask yourself.
- Trade-offs: It’s not the only valid framework — but having any framework beats having none
- Decision: Emphasized Google Apps Script, browser bookmarklets, HTML files, Sheets formulas, Slack Workflow Builder — all things that require zero IT approval to create
- Alternatives considered: Including Python scripts, npm tools, browser extensions
- Rationale: The audience is non-technical and in a corporate environment. Anything requiring
npm installor admin access is a dead end. The listed tools genuinely require nothing but a browser. - Trade-offs: More powerful tooling (actual scripts, APIs, automation platforms) is out of scope
- What Claude Code is and why terminal-based
- Full setup: terminal install (WSL for Windows), Node.js, Claude Code, auth
- Basic usage and permission system
- The CLAUDE.md instruction system (project + personal)
- Prompting best practices (7 techniques with before/after examples)
- Context management (window limits, session hygiene, institutional knowledge)
- 4 practical workflow examples
- Common pitfalls
- Mindset shift (search engine → junior colleague)
- Corporate AI landscape (what you can/can’t do, AI usage policies)
- CRAFT prompting framework with worked examples
- Few-shot prompting, chaining, constraints, “Act As” technique
- 5 real work patterns (first draft accelerator, data translator, review partner, learning accelerator, process builder)
- Building custom tools without coding (Google Apps Script, bookmarklets, HTML calculators, Slack automations)
- 6 lessons from real AI systems (mistakes→rules, verify don’t assume, dual-persist, context crash recovery, A/B test approaches, graduated autonomy)
- Common pitfalls (copy-paste trap, confidentiality, automation without understanding, overreliance)
- Measuring progress
- Quick reference prompt starters table
feedback_verify_before_asserting.md→ Lesson 2 (verify don’t assume)feedback_test_before_asking.md→ Lesson 2 (“done” means verified)feedback_learnings_dual_persist.md→ Lesson 3 (save in two places)feedback_pipefail_grep.md→ Referenced in mistakes-become-rules framingproject_claude_bakeoff.md→ Lesson 5 (A/B test approaches, adversarial buying research)project_autonomous_dev.md→ Lesson 6 (graduated autonomy, production deploy incident)- Consider posting to WordPress as standalone articles — these guides are long enough and useful enough to be blog posts on pezant.ca
- The two guides could link to each other — the CLI guide could link to the work guide for people who can’t install things, and vice versa
- Team sharing — the work guide is specifically designed to be shareable with colleagues. Consider distributing via the interview practice tool or buying assistant channels where non-technical people interact
- The prompting section overlaps — if a third guide is ever written, extract the prompting principles into a standalone reference that both guides link to
assortedLLMTasks/tasks/2026-04-08-claude-code-setup-walkthrough.md— CLI setup guideassortedLLMTasks/tasks/2026-04-08-ai-at-work-productivity-guide.md— Corporate AI guideprivateContext/deliverables/closeouts/2026-04-08-ai-at-work-guides.md— This closeout
Decisions Made
1. Two Separate Guides Instead of One
2. Anonymized Real Lessons vs. Generic Advice
3. CRAFT Framework for Prompting
4. “Building Your Own Tools” Section Focused on Zero-Install Options
What Was Built / Changed
Guide 1: Claude Code Setup Walkthrough
**File:** assortedLLMTasks/tasks/2026-04-08-claude-code-setup-walkthrough.md
**Commit:** 66efefd
8-part guide covering:
Guide 2: AI at Work Productivity Guide
**File:** assortedLLMTasks/tasks/2026-04-08-ai-at-work-productivity-guide.md
9-part guide covering:
Learnings Captured
Drawn from existing memory/feedback (not newly created):
No new memory or guidance files created
This session was content production, not system/workflow changes. The learnings were already captured — this session repackaged them for an external audience.