AI SQL workflow: define the data contract and validate read-only samples first
A safe, practical AI SQL workflow: minimal schema, metric definitions, clarification prompts, read-only samples, join checks, and reporting review.
2026-09-23AI TUTORIALS
Learn tools by doing real tasks
Practical tutorials with steps, examples, prompts and pitfalls—not generic tool roundups.
AI project status updates: turn meeting notes into a decision-ready risk ledger
A practical AI project-update workflow: extract evidence from meetings, define risk triggers, clarify decisions, and track next-week verification.
2026-09-21AI invoice OCR workflow: extract fields, then route exceptions for human review
A practical AI invoice and receipt workflow: fixed fields, document classification, deduplication, exception rules, evidence, privacy, and human review.
2026-09-17AI product images for ecommerce: lock product facts before generating lifestyle scenes
A practical AI ecommerce image workflow: product-facts cards, constrained prompts, composition drafts, verified text overlays, and fidelity review.
2026-09-16AI localization QA for Chinese-English websites: find missing text and fix real language defects
A practical AI localization QA workflow for Chinese-English websites: URL pairs, rule checks, glossary context, semantic review, SEO, and release checks.
2026-09-13Do not start AI release notes with a feature list: build a change-evidence sheet first
A practical AI workflow for release notes: verify changes, audience impact, availability conditions, and unknowns before drafting clear product updates.
2026-09-13Do not ask AI to merely summarise open survey responses: preserve evidence and validate themes
A practical workflow for AI-assisted open-response analysis: redaction, extraction, theme boundaries and validation.
2026-09-08Do not ask AI to make a project proposal sound professional first: build a fact sheet
A practical proposal workflow using confirmed facts, scope boundaries, dependencies and AI-assisted consistency checks.
2026-09-03Do not start AI onboarding with a document dump: build reviewable role tasks
A practical AI onboarding workflow built around approved sources, safe practice, review cards and knowledge-base updates.
2026-09-02How to repurpose one webinar without losing the evidence trail
Turn a webinar into a guide, social posts, FAQ candidates and future topics with timestamps, evidence cards and human review.
2026-08-31Do not just save competitor landing-page screenshots: turn public pages into testable experiments
A practical AI workflow for landing-page research: observed evidence, structural hypotheses, constrained copy and review.
2026-08-29Do not use AI to merely summarise customer pain points: build a product-decision ledger
A practical feedback workflow: original evidence, factual extraction, problem clusters, transparent priority and follow-up validation.
2026-08-27Build a source-backed presales Q&A library with NotebookLM
A practical NotebookLM workflow for reviewable presales answers: approved sources, conditions, evidence cards, conflicts and maintenance.
2026-08-26Do not hit generate first: use a shot list for AI short videos
A practical AI short-video workflow: one CTA, shot list, continuity card, captions, review and outcome tracking.
2026-08-20Do not ask AI for ten social posts first: build a content calendar you can review
A practical social-content workflow: audience questions, evidence, channel adaptation, approval and seven-day review.
2026-08-19Do not give a supplier spreadsheet straight to AI: a practical product-import cleanup workflow
A controlled workflow for turning supplier spreadsheets into import-ready product data: schema, mappings, SKU review, AI constraints and batch testing.
2026-08-16Do not send every website form to sales: build a deduplicated AI lead workflow with n8n
A practical lead workflow for small teams: validate form data, deduplicate, create a factual AI brief, assign an owner and handle failures.
2026-08-13Do not let AI invent support replies: build reviewable reply components from real tickets
Support macros are not one block of standard wording copied everywhere. Build components from real tickets, conditions, boundaries and next steps so AI can draft faster without making false promises.
2026-08-12