Do 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.
2026-09-03AI TUTORIALS
Learn tools by doing real tasks
Practical tutorials with steps, examples, prompts and pitfalls—not generic tool roundups.
Do 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.
2026-08-12Do not summarise an interview transcript too soon: find decisions, disagreements and missing evidence
Interview transcripts mix small talk, hypotheses and real decisions. A generic summary loses the disagreement and follow-up information that actually affects the next piece of work.
2026-08-10Do not ask AI to summarise a long PDF: extract an actionable brief with source evidence
A generic PDF summary often misses the condition in a table, appendix, or footnote. Define the decision first, require page evidence, and turn the result into an action table.
2026-08-04Do not prompt product images one by one: set asset rules before using AI at scale
AI product images often change colour, proportion, background or product details from one frame to the next. Separate fixed product facts from variable scene rules before generating at scale.
2026-08-03Do not ask AI for weekly-report insights first: lock the metrics and definitions
The main problem with weekly reports is not slow writing. It is that “growth” can mean different things to different people. Freeze a metric brief, separate facts from hypotheses, then let AI structure the report.
2026-07-31Do not compare contract versions by eye: use AI to locate changes, not to give legal advice
The meaningful change between contract v3 and v4 may be one word in a payment date, renewal clause, or liability cap. AI can locate and structure differences, but it cannot replace legal judgement.
2026-07-28Do not ask AI for a sales-call summary: separate actions, risk, and CRM updates
A fluent AI meeting summary does not tell a sales team what to do next. This workflow extracts commitments, objections, facts to verify and evidence-based CRM updates from a sales call.
2026-07-27Do not just follow the top comment: turn social comments into an AI-assisted topic map
Comment sections mix praise, jokes, purchase questions, real obstacles and off-topic debate. Feeding them all into AI produces vague “insights.” This workflow finds topics that are repeated, verifiable and genuinely answerable.
2026-07-21