AI training courses, built around your team's work.

After the day, your team can

• Explain how AI tools work, and why they can sound sure and still be wrong.
• Brief any AI tool with the role, the task, the context and the format.
• Research a topic with tools that show their sources, then check each source.
• Turn a rough idea into a slide deck, a visual, and a small app or web page.

A starting point. We shape the final outcomes with you on the call, so they may change.

How the day runs

1. How AI works. What these tools do well, where they get things wrong, and what must never go into them.
2. Prompting and context. Giving AI the role, the task, the context and the format, then saving that setup to use again.
3. Research and ideas. Research tools that show their sources, plus a notebook that answers from the files you give it.
4. Visuals and building. A slide deck and a visual, then a small app or web page you build by describing it in plain English.

After the day, your team can

• Turn a year of scattered department notes into a clear written plan for next year.
• Set next year's targets, then have AI argue against them before anyone else does.
• Build the deck that walks management through the plan.
• Check every figure AI produced before the plan goes out.

A starting point. We shape the final outcomes with you on the call, so they may change.

How the day runs

1. Where AI fits in planning. What AI does well in a planning cycle, plus the parts it gets wrong.
2. Briefing AI on a department. Giving it the goals, the numbers and the limits before it writes anything.
3. Writing the plan. Building the plan section by section, then checking every figure in it.
4. Building the deck. Turning the written plan into slides management can read in ten minutes.

After the day, your team can

• Build one closing checklist that covers every step your team repeats each month.
• Clean and reconcile a messy data set with AI, then find the entries that don't match.
• Write variance commentary management understands on the first read.
• Trace every AI figure back to its source before it enters a finance document.

A starting point. We shape the final outcomes with you on the call, so they may change.

How the day runs

1. Where AI fits in closing. The closing tasks AI handles well, plus the ones it must not be trusted with.
2. Prompting for accurate numbers. Stating the source, the assumptions and the format so figures can be traced.
3. Spreadsheets and reconciliation. Cleaning a messy data set, then finding the entries that do not match.
4. The management report. Turning the closing file into commentary a non-finance reader understands.

After the day, your team can

• Turn a year of notes into a solid first-draft review.
• Rewrite vague feedback into words the person can act on.
• Spot wording that could start a dispute, before the review is shared.
• Build the HR summary of a full review cycle for management.

A starting point. We shape the final outcomes with you on the call, so they may change.

How the day runs

1. Notes into a first draft. Feeding a year of notes to AI, then getting a review draft back.
2. Fair and specific wording. Cutting vague praise, then adding the examples that back a rating.
3. What goes into an AI tool. The staff details that must be removed before anything is pasted in.
4. The HR summary. Pulling the themes out of a full review cycle into one report for management.

After the day, your team can

• Test a decision with AI before you commit to it.
• Pull the two or three decisions out of a long business review pack.
• Read a KPI sheet with AI, then check the numbers it gives back.
• Build the leadership deck from the analysis in the same sitting.

A starting point. We shape the final outcomes with you on the call, so they may change.

How the day runs

1. AI as a thinking partner. Testing a decision against AI, then asking it to argue the opposite case.
2. Business reviews. Turning a long review pack into the two or three decisions the meeting needs.
3. Numbers and forecasts. Reading a KPI sheet, then building a forecast with the assumptions written down.
4. The leadership deck. Setting the storyline first, then turning it into slides the room can follow.

After the day, your team can

• Use Copilot with confidence across Outlook, Teams, Word, Excel and PowerPoint.
• Get a usable answer the first time with one structured prompt method.
• Set up scheduled prompts so routine work runs without anyone at the keyboard.
• Build a no-code agent in the Microsoft 365 agent builder and use it in Teams.

A starting point. We shape the final outcomes with you on the call, so they may change.

How the day runs

1. Foundations. How AI works, and where Copilot sits inside Microsoft 365.
2. Prompts for Copilot. The method, then the moves that repair a weak answer.
3. Copilot across the apps. Mail, meetings, documents, spreadsheets and decks.
4. Agents. Scheduled prompts, the agent builder, then a first look at Copilot Studio.

After the day, your team can

• Use Gemini across Gmail, Docs, Sheets, Slides, Meet and Drive.
• Build a Gem for a task that keeps coming back, then share it with the team.
• Set up a notebook that answers questions from your documents, with citations.
• Schedule prompts that run on their own, and build one no-code automation.

A starting point. We shape the final outcomes with you on the call, so they may change.

How the day runs

1. Foundations. How Gemini works, where it sits in Workspace, what is safe to put in.
2. Prompts and Gems. The prompt method, then a Gem for a task that comes back every week.
3. Gemini across the apps. Mail, documents, data, decks, meetings and Drive.
4. Notebooks and automation. Questions against your sources, then scheduled actions.

After the day, your team can

• Use Projects, Custom Instructions, Memory, Voice and web access on everyday tasks.
• Write prompts that state the role, the task, the context and the format.
• Fix a weak answer with one follow-up, without starting over.
• Build a personal AI workspace for your research, drafts or reports.

A starting point. We shape the final outcomes with you on the call, so they may change.

How the day runs

1. ChatGPT and how it works. Plus the features that save the most time.
2. Prompts. The formula, then the follow-ups that fix a weak result.
3. Advanced prompts. Iteration, tone, accuracy and longer tasks.
4. Your AI workspace. Projects, custom GPTs, then a build for your own work.

After the day, your team can

• Pick the right Claude model for the job in front of you.
• Save your company's writing rules once, so every draft Claude writes follows them.
• Connect Claude to your team's tools through Connectors and MCP.
• Know when a job needs Claude the app, and when it needs Claude Code.

A starting point. We shape the final outcomes with you on the call, so they may change.

How the day runs

1. Meet Claude. How it thinks, the models, and how to prompt so it follows.
2. Power features. Projects, Artifacts, and your company's writing rules saved once.
3. Connections. Connectors and MCP, so Claude gets to your tools.
4. Claude the app and Claude Code. When to use each one.

After the day, your team can

• Set up Claude Code and build your first small tool in class.
• Use the ask, plan, build, check loop with the core commands.
• Turn a task you do every week into a reusable skill.
• Hand multi-step work to agents, then finish a project from start to end.

A starting point. We shape the final outcomes with you on the call, so they may change.

How the day runs

1. Setup. Install Claude Code, terminal basics, then a first session.
2. The everyday loop. Core commands, file edits, ask, plan, build, check.
3. Skills. Turn a task you do every week into something reusable.
4. Agents and delivery. Hand over multi-step work, then finish the project.

After the day, your team can

• Tell which work is worth handing to an agent, and which isn't.
• Build a no-code agent in the Microsoft 365 agent builder.
• Set up Claude with Projects and Artifacts for the same job.
• Connect an agent to a knowledge source, then design the workflow it runs.

A starting point. We shape the final outcomes with you on the call, so they may change.

How the day runs

1. Agents in plain language. What they do, and where they fail.
2. Copilot Agent Builder. A no-code agent on a knowledge base.
3. Claude for agent work. Projects, Artifacts, then connections.
4. Agentic workflows. Classify, analyse, recommend, then communicate.

After the day, your team can

• Write prompts that state the goal, the context, the source and the format.
• Fix a weak answer with a follow-up, without starting over.
• Use the features that change the answer, like file uploads and saved projects.
• Build a first agent that runs one weekly job on its own.

A starting point. We shape the final outcomes with you on the call, so they may change.

How the day runs

1. AI foundations. How these tools work in plain language, plus where they get things wrong.
2. The prompt method. Goal, context, source and expectations, then the follow-ups that fix a weak prompt.
3. Features that change the answer. File uploads, saved projects, research modes, custom instructions.
4. Your first agent. Instructions, knowledge, actions, then a test on a weekly job.

After the day, your team can

• Every department names one AI use for its own work by the end of the morning.
• Everyone writes a prompt that gives a usable answer on the first try.
• Everyone knows what company information must never go into a public AI tool.

A starting point. We shape the final outcomes with you on the call, so they may change.

How the day runs

1. What AI does now. What these tools do well, and where they fail.
2. One way to prompt. The method a whole company can share, shown live on ordinary tasks.
3. Department by department. What changes for marketing, finance, HR, operations and service.
4. Safe use. What stays out of the tool, and how to check an answer before it is used.

After the day, your team can

• Read six months of numbers and find what changed.
• Explain a variance in one paragraph a director will understand.
• Build the review deck from the analysis on the same day.
• Rework the forecast for the rest of the year from what the numbers show.

A starting point. We shape the final outcomes with you on the call, so they may change.

How the day runs

1. Reading the half-year. Putting the numbers to AI, then finding the movements worth explaining.
2. The story behind the number. Turning a variance into a short written explanation.
3. The review deck. Building the slides from the analysis, in the words management uses.
4. The revised forecast. A first-cut projection for the rest of the year, then checking it by hand.

After the day, your team can

• Know which finance tasks AI handles well, and which ones it must not be trusted with.
• Get a formula written and explained without memorising the syntax.
• Clean a messy data set, then find the trends, outliers and variances in it.
• Draft variance commentary, and check contracts and invoices for key terms.

A starting point. We shape the final outcomes with you on the call, so they may change.

How the day runs

1. Where AI fits in finance. How AI tools produce answers, and why that matters for accuracy.
2. Prompts that show the working. Stating the source and the format, then asking AI how it got each figure.
3. Spreadsheets and analysis. Formulas, data cleaning, and the trends and variances in one working file.
4. Reports, documents and data safety. Commentary for management, key terms in contracts, and what confidential data stays out of AI.

After the day, your team can

• Walk into a first meeting knowing the account and its market.
• Turn meeting notes into a structured brief in minutes.
• Send the follow-up and the proposal on the same day as the meeting.
• Check every claim AI makes against a source before it goes into a pitch.

A starting point. We shape the final outcomes with you on the call, so they may change.

How the day runs

1. Prompting for sales work. Giving AI the account, the buyer and the goal before asking for anything.
2. Account research. Researching a company with tools that return sources you can open.
3. Notes to brief to proposal. Turning meeting notes into a brief, then a solution the buyer recognises.
4. The follow-up and the deck. Writing the email that follows a meeting, then the slides behind it.

After the day, your team can

• Set up AI to write in your brand's voice.
• Turn one campaign brief into a month of posts.
• Build campaign images with an AI image tool.
• Turn campaign results into a short report for management.

A starting point. We shape the final outcomes with you on the call, so they may change.

How the day runs

1. Brand voice setup. Teaching the tool how your company sounds before you write anything.
2. Audience research. What your buyers care about, with sources you can check.
3. Campaign copy. Emails, ads, landing pages and social posts from one brief.
4. Images and reporting. Campaign visuals, plus the results report management asks for.

After the day, your team can

• Write an SOP a new joiner can follow on day one.
• Build the weekly operations report from a page of numbers.
• Spot which repeated tasks are worth handing to AI.
• Build a simple form or tracker without writing code.

A starting point. We shape the final outcomes with you on the call, so they may change.

How the day runs

1. Where AI fits. Mapping the repeated tasks in a week and picking the ones to hand over.
2. SOPs and documentation. Turning steps in someone's head into a written guide.
3. Reporting. The weekly operations update, built from numbers in a spreadsheet.
4. Small tools without code. A form, a tracker or a checklist your team can use.

After the day, your team can

• Pull the key clauses out of a long contract.
• Compare two versions of an agreement and list every change.
• Remove names and confidential details before anything goes into a tool.
• Turn a legal memo into a short deck for management.

A starting point. We shape the final outcomes with you on the call, so they may change.

How the day runs

1. Prompting for legal work. Reusable templates for the review and drafting you repeat.
2. Contract review. Pulling out clauses, comparing versions, writing the first summary.
3. Confidential details. How to strip out names and numbers before you paste anything.
4. Memos into decks. Turning a written legal view into slides management can read.

After the day, your team can

• Draft replies that sound like your company.
• Turn an angry complaint into a calm, clear answer.
• Summarise a long email thread before handing it to a colleague.
• Catch wrong details in a draft before it reaches the customer.

A starting point. We shape the final outcomes with you on the call, so they may change.

How the day runs

1. Prompting for service. Giving the tool your tone, your rules and the facts it may use.
2. Everyday replies. Drafts for the questions your team answers again and again.
3. Complaints. Reading what the customer actually wants, then writing a calm reply.
4. Checking before sending. The short list your team runs over every AI draft.

After the day, your team can

• Use the approved office tools for daily writing tasks.
• Turn a long report or a set of minutes into a short summary.
• Draft a memo from a few lines of notes.
• Name the details that must never be typed into an AI tool.

A starting point. We shape the final outcomes with you on the call, so they may change.

How the day runs

1. How AI works. Plain language, no jargon, with what these tools get wrong.
2. Prompting. The four parts of an instruction that gets a usable answer.
3. Everyday office work. Memos, letters, minutes and summaries of long reports.
4. Data rules. PDPA, department policy, plus what stays out of every AI tool.