> Canonical source: # Corporate AI training Help every team do more and better work with AI. [Book a free 20-minute call]() ![Help every team do more. Sydney leading a teaching session.]() ## Help your teams get more done, together. An illustrative example: customers can’t find their saved projects. AI could help Support reply, Product plan an improvement, and Engineering prepare a fix. 1. ### Support helps the customer. AI can prepare Uses the help guide to draft a clear reply. Groups similar reports into a pattern: “Customers can’t find their saved projects.” People decide Check the reply before sending it and confirm whether the reports point to the same problem. 2. ### Product explores a fix. AI can prepare Brings that pattern together with product goals and sketches a proposal: “Show where the project was saved, with a link to open it.” People decide Confirm the cause, choose the right improvement, and approve a plan for Engineering. 3. ### Engineering prepares the change. AI can prepare After approval, a connected coding tool can use the plan and codebase to draft a change with tests, ready for an engineer to review. People decide Review the code, run the tests, and decide whether it is ready to release. **The common thread.** Customer feedback, product knowledge, and company goals carry through each step. In a connected setup, an approved handoff can trigger AI to prepare the next team’s draft. This is one possibility for a connected system. Training can start with a single step; the tools, access, and wider implementation are agreed separately. **Try this workflow yourself** ### Start with work that crosses a team boundary. Fill in this prompt with a task and the company context behind it. It can help you find a small, useful starting point to discuss with your colleagues. Hello Aristotle ### Find a useful AI workflow across your teams ``` Help us find one practical way for AI to improve work across teams, using shared company context. OUR GOAL [What are we trying to achieve? Include the goals of the teams involved.] THE WORK [Describe a recurring task or problem, which teams touch it, and where work slows down.] WHAT AI COULD WORK FROM [Summarize relevant customer feedback, product information, policies, metrics, or other knowledge we are allowed to share.] OUR TOOLS [Name the approved tools and connections we already have. Write “unknown” for anything uncertain.] Suggest three opportunities in plain language. For each, explain what AI could prepare, how it would help the next team, and which shared information it needs. Consider better quality and alignment as well as more output. Recommend one small starting point and explain why. Map it in a short table: team, input, AI draft, human decision, and what passes to the next team. Flag conflicting goals, missing evidence, and any connections that would need to be set up. If numbers are involved, keep their sources, time periods, and definitions visible. Mark unattributed results unknown. A pattern does not prove cause: suggest what to check before changing a budget or plan. Finish with a simple practice exercise we can try using a safe sample, and how we could judge whether it helped. Ask up to three questions if essential information is missing. Use only the information supplied. Do not invent results or assume our tools are connected. Suggest drafts and plans only. Do not contact anyone, change systems, or publish anything. ``` ### Before you use the result 1. Does the idea serve the company goal and the teams involved? 2. Is the necessary information available in a tool your organization approves? 3. Who will review the work before another team or a customer relies on it? #### Try the idea on a real kind of task. Use a safe sample and ask the next team whether the draft would help them. Compare quality, time spent, and what still needs a person’s judgment. ## Give your teams something useful to try. Pick a task below and open the prompt. Replace the brackets with information you can share in your company’s approved AI tool, then review the result with the team who’ll use it. ****Turn customer feedback into a Product brief.** Help Support show Product what customers are struggling with and which questions are worth exploring.** Hello Aristotle ### Turn customer feedback into a Product brief. ``` Help Support and Product turn customer feedback into a useful product brief. Customer notes, with identifying details removed: [PASTE NOTES] Current product guidance: [PASTE RELEVANT GUIDANCE] Our company and Product goals: [ADD GOALS] Group the problems customers describe. For each, show the source evidence, what the customer was trying to do, and how it relates to our goals. Separate reported problems from possible explanations. Suggest one problem to explore first and explain why. Draft a short Product brief: problem, evidence, questions to investigate, and what a better customer experience could look like. Flag missing or conflicting information. Don’t infer how widespread a problem is from a few reports. Finish with what Support should verify and what Product needs to decide. Prepare a draft only; don’t send it or change any systems. ``` ****Give Engineering a clearer starting point.** Turn an approved Product decision into a brief with useful acceptance checks and the questions still worth asking.** Hello Aristotle ### Give Engineering a clearer starting point. ``` Help Product prepare an approved idea for Engineering to review. Approved Product brief: [PASTE BRIEF] Relevant product behavior and technical constraints: [ADD SOURCES, OR WRITE “UNKNOWN”] Our goal and limits for this change: [ADD GOAL, SCOPE, AND CONSTRAINTS] Write a short implementation brief covering the user outcome, confirmed requirements, what is outside the agreed scope, and decisions still needed. Keep proposed details separate from approved requirements. Suggest acceptance checks tied to the intended behavior, including useful edge cases. Show which source supports each requirement. If the brief doesn’t establish an expected result, turn it into a question for Product. List the technical questions Engineering should resolve before planning the change. Don’t invent a cause, choose an architecture, estimate effort, or write code. Product confirms intent; Engineering checks feasibility and the proposed tests. ``` ****Connect Marketing results to Product questions.** Bring campaign results and product use into one discussion about what to investigate or improve next.** Hello Aristotle ### Connect Marketing results to Product questions. ``` Help Marketing and Product decide what to investigate next using the information below. Campaign results, audience, and dates: [PASTE AGGREGATE RESULTS] Product usage and customer feedback, with dates: [PASTE APPROVED AGGREGATE DATA AND REDACTED FEEDBACK] Shared business goal: [ADD GOAL] Create a short comparison table: signal, source, time period, what it tells us, and what it cannot tell us. Keep campaign engagement, product behavior, and customer comments separate. Flag mismatched periods, missing definitions, and missing attribution. If our shared goal is missing, ask us for it first. Otherwise, suggest three questions the teams could answer together, then recommend one small investigation that would help our goal. Name the evidence we’d need and how we could judge the result. Don’t treat correlation as proof that a campaign caused product use, invent missing numbers, or recommend a budget change as settled. Marketing and Product should check the interpretation before acting. ``` ## Turn AI skills into better everyday work. We’ll shape training around what your company wants to achieve, then practice on work your people recognize. 1. ### Find the work worth improving. Tell us what you want your company to accomplish. Preparation can be a quick discussion of priorities, or a deeper look through team conversations and the resources people use. 2. ### Help AI do a better job. Give AI the company knowledge, team goals, and instructions it needs. Practice using that context to prepare better work for the next person. 3. ### Make useful work easier to repeat. Work through a task, compare the results, and keep useful prompts or instructions. Colleagues can adapt that approach to other work. We’ll agree the starting scope and any larger implementation separately. Is keeping commitments moving between departments your first priority? Explore [AI training for operations teams](). ![Sydney at a cafe table with laptops]() Sydney Liu, founder of Hello Aristotle ## Learn by doing useful work with Sydney. You’ll work with the founder of Hello Aristotle, a business operator who uses AI in his own work. Bring a business goal, a problem that keeps coming back, or a team that wants to do more with AI. We’ll connect the possibilities to work your people recognize, help them practice, and work through what makes the results useful. [Meet Sydney Liu →]() ### What our learners say. A learner’s experience from an individual session with Sydney. > “I work in finance and felt like I was falling behind. After one short session with Hello Aristotle, I had real ways to improve my workflows and the confidence to keep exploring. Sydney breaks things down in a way that’s easily digestible\!” **Nick Toy** Finance Manager · Volkswagen Financial Services ## Get more from your next AI task. Try a free guide to give AI a clearer brief or improve an answer that missed the mark. Share what works with a colleague. [![Hello Aristotle: Give AI the context your work needs]()]() ### [Give AI the context your work needs]() Turn selected notes, documents and emails into a useful work profile. Let AI find the gaps, ask you better questions and save the context for next time. [![Hello Aristotle: Fix a disappointing AI answer]()]() ### [Fix a disappointing AI answer]() Find the missing context, improve the brief and get a better answer. Use one repair prompt, then keep the lesson for the next task. Planning for a team? [How to Choose AI Training for Your Team →]() ## Plan training that works for your team. **Can people with different experience levels join?** Yes\! Tell us about the range in the group. Someone opening an AI tool for the first time needs a different starting point from a daily user. We’ll discuss how to make the training useful for both. **Do we need to choose a tool first?** Tell us what your organization already allows, whether that’s ChatGPT, Claude, or another tool. We’ll work out the setup before the session. Use fictional or appropriately redacted practice material if real work can’t be shared in that tool. **How long does training take, and what does it cost?** We start with at least one hour so there’s time to get the foundations right. Group size, total duration, and format are flexible. We’ll discuss the preparation, scope, and price before you commit. The free 20-minute call helps us work out where to start. **Can AI help our leaders make better decisions?** Yes. For example, AI could compare campaign results with what those customers do in your product, then prepare a shared report for Marketing and Product. Leaders can use it to ask better questions about where to invest, with gaps in the data made clear. **What could people take away?** A practical way to give AI the company and team context it needs, plus prompts, instructions, or a workflow they can adapt. We’ll agree what’s worth building in your session and discuss any follow-up you want. **Is there a qualification at the end?** We offer Aristotle Certificates for reaching practical proficiency milestones. They aren’t an accredited qualification or an employer certificate. We can discuss which skills you want your people to demonstrate in their work. **Does corporate training always mean a workshop?** Workshops are one option. We’ll choose an approach that fits your team and what you want to accomplish. **Several teams need to work together.** Bring a shared goal or a piece of work that passes between departments. We can explore where AI could help each group and what they need from one another. **People need different levels of help.** Tell us where beginners and experienced users are starting. We can discuss whether they should practice together or whether a different arrangement would serve them better. **You need a larger implementation.** If the need includes a company-wide rollout, systems integration, or ongoing support, describe that early. We’ll discuss what can be included in the agreed scope. ## Let’s help your team get more from AI. Tell us what you want your people to accomplish. In a free 20-minute call, we’ll explore where AI could help and what training could look like for your team. [Book a free 20-minute call]()