Before / First draft
Instruction
Help me announce our choir rehearsal.
Authored example output
Join us Monday at 6 p.m. in the church hall for choir rehearsal with our singers and pianist. We look forward to a wonderful evening of music.
Keep what you are building
Work stays in this tab. Save on this device or export before closing. Shared-device users may see saved work. Local drafts are not sent to a model or instructor.
Keep an account copy
Save explicitly to continue on another device. Account copies are private to you and authorized IHA staff; they are not public, sent to an AI model, or submitted for assessment. Use fictional or permitted, non-sensitive information.
Account saving is optional. Your browser work stays available without signing in.
Work here without an account. Save or export when you want to keep it.
Build with AI
Understand what an AI answer can tell you
LESSON 01 / 06 ACTIVITY 01 / 08
Course guide · outcomes, syllabus & finishing your work
AI for everyday life
Build confidence using AI for everyday tasks. Practice asking useful questions, checking answers, protecting private information, and participating in decisions that affect your community.
The work you will leave with
An everyday AI use plan: one useful task, a checked example, a privacy boundary, a correction, and questions to bring to a community conversation.
Before you start
No prior AI experience is required. You need to read a short scenario and record or explain a response; a facilitator or peer can support reading and writing. Use a phone, computer, or the printable lesson pack. No purchase or AI account is required for the core course. Optional account saving and AI coaching have separate sign-in and usage requirements.
Time and pacing
150–195 minutes of estimated lab practice across six lessons. These are planning estimates, not measured learner averages. Allow additional time for reading, decision checks, revisions, and optional fieldwork. Try one lesson per session; pause and resume at any activity.
By the end, practice demonstrating these outcomes
- 1. Understand what an AI answer can tell you
Distinguish a useful generated draft from a verified fact or an action that actually happened.
Lab estimate: 25–30 minutes
- 2. Give a clear task and useful context
Write instructions that define the audience, source information, output, and boundaries.
Lab estimate: 25–30 minutes
- 3. Check claims against sources
Trace an important claim to supporting information and preserve uncertainty when support is missing.
Lab estimate: 25–35 minutes
- 4. Protect information and pause under pressure
Choose safer practice inputs and independently verify an unexpected request before acting.
Lab estimate: 20–30 minutes
- 5. Build a small workflow you can check
Document and test one repeatable task with a human review step and a fallback.
Lab estimate: 25–35 minutes
- 6. Help your community make an informed choice
Create a bounded discussion brief that includes affected people, evidence, alternatives, and accountability.
Lab estimate: 30–35 minutes
What finishing means here
- Try the AI creation task in each lesson: edit a prompt, inspect live drafts if you sign in, or analyze the authored examples. Record what you checked and what improved. Live model use is optional.
- Make an independent artifact for each lesson using the changed scenario.
- Review each artifact against the lesson criteria. Record evidence or a revision needed, then explain one change in your reflection.
- Attempt all 18 decision checks, read the feedback, and revisit choices you cannot yet explain.
- Complete the final application and assemble your course artifact. Ask a peer or facilitator to challenge its facts, reasoning, and limits.
- Export your work and choose one bounded next use. Revisit a key decision the following day without the example.
The course tracks work recorded, not mastery. Authored answer feedback supports practice; written artifacts need human judgment. Self-review, reaching the last screen, or filling every field does not earn an IHA certificate or establish business results.
Save and return
Use “Your work” to save on this device, export a backup, or optionally save to an account. On a shared device, consider an exported file instead. Return to this pathway and choose “Resume saved work”; account work loads through “Your work.” Device saves include your activity position. A paper learner can use the same outcomes and criteria.
Generation versus supplied evidence
Watch context change the answer
Your AI workspace
Give it a task. Change one instruction. See what improves.
Run sends your instruction to the Academy AI provider and stores the run with your account. Sign-in and available usage required. Examples below are open to everyone.
Compare the examplesOne task. Two instructions. A more useful result.
Authored teaching examples, not live model runs or your results.
After / More useful draft
Improved instruction
Write an internal planning note, not a public announcement. Use four labels: proposed time, offered space, confirmed people, next action. Use only the supplied facts and keep acceptance and the pianist unconfirmed. Use the supplied source.
Authored example output
Proposed time: Monday, 6 p.m. Offered space: church hall; choir acceptance pending. Confirmed people: two singers; pianist unconfirmed. Next action: the organizer decides whether to accept the hall and checks accompaniment before making a public announcement.
Why the instruction changed
- The audience changes from the public to the planning team.
- Status labels stop an offer from becoming a confirmed arrangement.
- The output is useful because it shows exactly what the organizer needs to do next.
Take it further
Now make it your own
Change one fact: the choir accepts the hall, but the pianist declines. Update only the affected lines and preserve the proposed time as proposed.
Add this variation to your instruction and run it again, or explain how you would revise the authored example. The starter prompt does not include this change automatically.
Decide what actually improved
- Only the changed statuses are updated.
- No new participant or booking is invented.
- The note distinguishes an action to take from an action completed.
No live run? Evaluate the authored example and label your notes as example analysis.
Need the concept or a reference?
Distinguish a useful generated draft from a verified fact or an action that actually happened.
A model is the underlying system that produces an AI response; a chat app gives you a way to interact with it. Generative AI produces material using learned patterns and the information available in the conversation. A prompt is your instruction, and context is the information supplied for the task. Some apps can search or use connected tools, but those are separate capabilities to check. A response can also reflect missing perspectives or unfair assumptions, so ask who may be misrepresented as well as whether the facts are right. You will practice with invented examples before deciding where a real tool would help.
An AI assistant can help draft, organize, explain, and explore possibilities. It generates an answer from the information and capabilities available to it. Fluent wording is not evidence that a statement is true. An assistant may misread a question, fill a gap with a plausible detail, or express more confidence than the evidence supports. Begin by asking what you can check independently.
Separate three things: a draft, a claim, and an action. A suggested email is a draft. “The library opens at nine” is a claim that needs a current source. “Your appointment is booked” describes an action that requires an actual booking confirmation. An assistant without a booking connection cannot establish that it reserved anything. Even a connected tool needs a successful result, not just an intention to act.
Use AI where you can inspect the result and recover from mistakes. Rewording a fictional invitation is a useful first task. A consequential decision about someone’s health, money, or access to a service needs appropriate human expertise and reliable sources. Knowing when to stop, ask, or use another method is part of competence. You do not need to accept an answer because it sounds authoritative.
Short example
Synthetic example: Sam asks an assistant to help arrange a neighborhood meeting. It produces an agenda and says the room is reserved. Sam can review the agenda as a draft, but has no booking confirmation. Sam labels the reservation unconfirmed and checks with the venue through its established contact channel.
Questions to ask yourself
- Am I looking at a draft, a claim, or an action receipt?
- What evidence would establish that an action happened?
- Can I explain when I would ask a person for help?
Watch for: Treating confident language as proof of accuracy or completed action.
Optional prompt for a tool you choose
Help me practice distinguishing drafts, factual claims, and completed actions. Give me three fictional examples without labeling the answers. After I classify them, ask what evidence I would need. Do not claim to have contacted anyone or made a booking.
Ask the AI learning coach
Optional AI support
Ask Sage Learning
Ask for a hint or feedback on your draft. AI feedback can be wrong. Check it against the source and review criteria; it does not award a grade or credential.
Sign-in and your existing AI allowance apply. What you send goes to the AI provider and is saved in your Sage Learning conversation history. Use fictional or permitted, non-sensitive material. Nothing is sent until you select the button below.