Prompt Engineering
Prompt engineering and practical AI skills for professionals: repeatable prompts, project spaces, and workflows you can use on Monday.
40 articles
Articles about Prompt Engineering
What 9,700 Real Users Actually Do With Claude
Most debate about AI and work runs on anecdote. Anthropic's June 2026 Economic Index, Cadences, offers something rarer: behavioural data on what roughly 9,700 real users do with AI, matched to how they feel about their careers. Almost every conversation produces real work, and the heaviest delegators are the most optimistic. Here is what a people leader should take from it.
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Ground the Model, Do Not Trust Its Memory
A weak model with the right tool beat a strong model working from memory. Anthropic's biology-agent benchmark put numbers on it: accuracy ran as low as 16.9% from recall and cleared 99.7% once grounded in the authoritative source. The lesson holds for every regulated workflow that turns on a rule, rate or standard. Ground the model, do not trust its memory.
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Two Doctors Disagree: AI Can Map the Conflict, Not Resolve It
When a treating doctor and an independent examiner disagree, the delegate has to weigh two medical opinions and determine liability on the balance of probabilities. AI can build the comparison so you spend your time on the judgement, not the sorting. Here is a de-identified workflow that keeps the weighing, and the decision, with the delegate.
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You Are No Longer the Smartest Person in the Room
The knowledge advantage that used to define senior leadership is exactly what AI now hands to everyone. A peer-reviewed study of how AI changes the skills top managers need argues the deepest shift is human, not technological. Here is what your job becomes when you are no longer the most informed person in the room, and a protocol to lead that way this week.
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Don't Let AI Write the Messages That Build Trust
When employees sense AI wrote a leader's praise or feedback, sincerity ratings collapse from 83 per cent to as low as 40. The fix is a three-lane triage: let AI draft the logistics, pressure-test the decisions, and never touch the messages that carry the relationship. Set it up in under an hour on Monday.
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Structured Outputs: Get the Same Shape Every Time
Structured outputs give an AI response a stable, checkable shape: required fields, data types and allowed values. This guide shows how to design an output contract, test it and keep human review where it belongs.
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Build a Golden Test Set Before You Trust an AI Workflow
One impressive answer proves almost nothing. Build a small golden test set of normal, difficult and boundary cases, score the output against observable criteria, and record every release decision.
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AI Can Stress-Test an Emergency Plan. It Cannot Run the Drill.
AI can challenge a de-identified emergency plan against scenarios, missing roles, communication failures and changed workplace conditions. It cannot test how people behave under pressure. Regulation 43 keeps the testing, the training and the drill itself human.
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AI Can Draft WHS Training. It Cannot Verify Competence.
AI can draft WHS learning objectives, scenarios, quizzes and facilitator notes from verified source material. It cannot observe a worker performing the task or certify competence. This guide sets out where the two human gates sit and how to run the drafting workflow without letting a completion record impersonate a competent worker.
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AI Can Map a Section 29 Household Services Claim. It Cannot Decide What Is Reasonable
AI can organise a de-identified section 29 household services claim by task, pre-injury contribution, post-injury capacity, household composition, family contribution, disruption and cost. It cannot apply the word reasonable. This guide gives you the evidence map, the prompt and the human decision line.
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AI and the Reasonable Administrative Action Exclusion: Map the Actions, Keep the Judgement
A practical guide to where AI genuinely helps with a section 5A reasonable administrative action determination, and exactly where the work stops being organisation and becomes human judgement.
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Make AI Disagree With You Before You Decide
Sixty per cent of executives now use AI to support their decisions, and the models they reach for lean toward agreement. The most useful instruction a leader can give AI is to push back. Here is how to build the disagreement in on purpose.
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Rehearse the Hard Conversation Before You Have It
The most expensive conversations a leader has are the ones walked into cold. The practice field for them now sits in the same window you draft the email in. Here is how to rehearse the hard conversation on a model before you have it for real.
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Context Engineering: What the Model Is Allowed to See
The reliability of an AI system is decided less by how you word the prompt and more by what you let into the context window. Context engineering is the named discipline for that, and it is the highest-leverage AI skill for anyone doing real work, especially in regulated settings.
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AI-Assisted Psychosocial Risk Assessment: A WHS Governance Workflow That Keeps the Sign-Off Human
A practical WHS governance workflow for Australian financial-services teams: use AI to synthesise de-identified survey data and draft the written psychosocial risk assessment, while a competent person always sets the rating, chooses the controls, and signs off.
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Set the AI Norm: Your Team Copies How You Use It
The biggest lever on whether AI lands in your team is not the licence or the training budget. It is whether you, the manager, visibly use it, set the standard, and make it safe to try. The evidence is now clear, and so is the move.
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AI-Assisted Onboarding: A 90-Day Plan That Keeps the Human In
Onboarding is where unmanaged AI does the quietest damage, because a new starter cannot tell a confident wrong answer from a right one. Here is a 90-day pattern, with a ready-to-build Onboarding Assistant project, where AI drafts and organises and people decide and connect.
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AI Week in Review, 8-14 June 2026: A Frontier Model Pulled by Government Order
The week a US directive forced Anthropic to suspend two new frontier models worldwide, plus six verified vendor moves and a repeatable method for turning AI news into Monday actions.
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Claude Model Routing for Regulated Work: Which Model to Use for GRC, WC and HR Tasks
Choosing a Claude model is a governance decision, not a speed decision. Route by capability tier, score the task, and keep accountable review with named people, with worked examples for GRC, workers compensation and HR.
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AI as a Red Team for Leaders: How to Challenge Thinking Without Surrendering Judgement
A practical method for using AI to stress-test leadership decisions across six challenge modes, while keeping evidence, judgement and accountability with the right people.
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AI Decision Memos for Leaders: Sharpen the Thinking Without Outsourcing the Decision
A practical method for using AI to structure a leadership decision memo, grounded in named decision frameworks, while the leader keeps the judgement and the accountability.
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Build the Knowledge Spine That Stops Generic AI Output
Generic AI output is a context problem, not a prompt problem. Learn how a governed knowledge spine grounds your models in real organisational knowledge, with worked examples for GRC, workers compensation and HR.
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Gold Standard Claude Workspace Setup
A gold standard Claude workspace for Australian enterprise teams. The right surface for each job, the files that carry context, an interview method to build each one, and the data-governance gates that keep it safe.
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Gold Standard ChatGPT and Codex Setup
Build ChatGPT and Codex into one AI operating system for Australian enterprise work: the right surface per job, an interview method to build each one, and the data gates that keep it safe.
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Build an Offline GRC Controls Console Without Creating Shadow IT
A single-file controls console can sharpen evidence review without leaking data. Treat it as a governed end-user computing tool, not a free win.
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Build a WC Evidence Chronology Tool Without Outsourcing Judgement
A practical pattern for using an LLM to build an offline, de-identified workers compensation evidence chronology tool that organises facts while the delegate keeps every SRC Act decision.
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Turn a Teams Transcript Into a Controlled HR SOP
A staged, evidence-first method for converting a recorded HR meeting into a governed standard operating procedure with an owner, a version history and a review rhythm.
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AI Can Draft Recovery Conversation Scripts, but the Listening Stays Human
A practical guide to using AI to draft motivational-interviewing-informed scripts, talking points and follow-up messages for recovery-at-work conversations. De-identification first, the MI frame in the prompt, and a human reviewer before any words reach an injured employee.
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AI as a Leadership Thinking Partner: Make It Attack Your Plan
Most leaders use AI to confirm their plans. The sharper use is to attack them. Pre-mortems, stress-tests and rehearsals that strengthen judgement instead of flattering it.
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AI in Performance Reviews: Draft the Words, Keep the Judgement
AI can synthesise a year of evidence notes into a solid first draft of review feedback. It cannot own the rating, the calibration case or the conversation. Here is the workflow that keeps the line clear.
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AI Literacy Is a Management Skill, Not a Training Module
Managers must embed AI literacy through daily behaviours like prompting, verification, privacy hygiene, escalation and review to ensure responsible AI use.
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Prompt Libraries Make WC AI Safer Only When Human Review Comes First
A practical SRC Act article on de-identification, placeholder prompt libraries, file-note drafting and human review controls for workers compensation communications.
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Leveraging AI to assist dissecting the SRC Act Review
A practitioner workflow for employers to dissect the December 2025 SRC Act Review with AI tooling. Project setup, four prompt patterns, submission scaffolding, and the two human review gates that keep the work defensible.
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The Incapacity Cross-Check Workflow: AI as a Calculation Auditor
Section 19 calculations are arithmetic-heavy and error-prone. AI shines as a second pair of eyes, not as the primary calculator. Here is the workflow.
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Custom Projects vs Raw Chats: When to Graduate Your AI Workflow
Raw chat is fine for ideation. For any workflow you run more than twice, Custom Projects pay back fast. Here is the rule for when to graduate.
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RAG Explained for Non-Engineers: How AI Reads Your Documents
RAG is the architecture behind most enterprise AI tools you will meet in 2026. The acronym hides a simple idea. Here it is, explained in plain English with a working analogy.
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Your First AI Workflow Without a Single Line of Code
You do not need n8n, Zapier or a developer to get genuine productivity from AI workflows. Pick a task. Stitch three prompts together. Save the recipe. Repeat next week.
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SRC Act and AI Assisted Determinations: A Practitioner Framework
AI can draft a determination in minutes, but the SRC Act still demands a qualified human decision maker. Here is the practitioner framework that keeps both true.
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Prompt Engineering Fundamentals: The 2026 Update for Working Professionals
The 2026 frontier models reward precision more than they did 18 months ago. This is the practical pattern set every working professional should be using now.
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2M-Token Multimodal Contexts: Where They Actually Pay Off
Two-million-token multimodal context is real. The marketing says it replaces RAG. The production data says it does not. Three workflows where it pays off and three where it does not.
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