Earlier note · November 2
Tuesday after 3 p.m.
SupersededAI Foundations 04 · select, test, refresh
Keep a small reference for stable background and voice, then add the current task evidence separately. Give facts a source and date, resolve conflicts before drafting, and refresh the information when it changes. A context card is a maintained input, not a promise of permanent memory.
Ryan Wanner · recorded course lesson · February 2026
All classes and lessons20:27 recorded course lesson · Watch with captions on YouTube
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Try the fictional freshness test. Stable background belongs in a short reference; the latest task evidence travels separately.
Tuesday after 3 p.m.
SupersededWednesday after 3 p.m.
Current task evidenceFICTIONAL PRACTICE CONTEXT Role: Cedar House Realty. Draft for human review; do not invent facts or send. Voice sample: Here is what we know. Here is the open question. I will check the missing detail. Current source, November 3: Wednesday after 3 p.m. Earlier Tuesday note is superseded. Task: Draft one short showing-confirmation question. Name the controlling source and list unknowns.
This builds ordinary text. It does not connect an account or create persistent AI memory.
Select the role, audience and actual voice sample useful to this task. Leave unrelated information out.
Ask for a draft, require unknowns to stay visible and specify which actions need review. Keep secrets and unnecessary personal data out.
The fictional older note says Tuesday; the newer confirmed note says Wednesday. Mark the older note superseded and carry Wednesday into the current task.
Compare a draft without and with the relevant card using the same request. Check factual accuracy, voice and next action.
Update the task evidence when a relevant fact changes. Record the owner, review date and change note; re-run the check.
Remove anything that does not help this request. Keep the source file you own and verify how your chosen tool retrieves it.
Pass check: the current draft uses Wednesday, identifies the newer note and preserves unanswered questions. Change the source date and run the check again before calling the workflow reliable.
don't forget to update.
give it the real stuff, not just descriptions.
Is the context lean?
User-supplied context does not become a technical system instruction because a section is named system.
Saved files, retrieval, Projects and memory features behave differently. Check actual behavior.
Mark which dated fact is current and which is superseded; do not ask AI to guess.
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Context freshness test and working card
# Context freshness test Current companion to AI Foundations 04 · November 8, 2026. All practice details are fictional. ## Stable context Cedar House Realty writes short, factual client updates. Voice sample: Here is what we know. Here is the open question. I will check the missing detail. Preference: draft for review. ## Conflicting sources Older, November 2: Tuesday after 3 p.m. Newer confirmed note, November 3: Wednesday after 3 p.m.; Tuesday superseded. ## Working card Owner and review date: Relevant role/audience: Actual permitted voice example: Current task facts, source and date: Superseded facts: Unknowns: Output request: Actions requiring review: Connection status: not established by this document. ## Test Run the same request without and with the relevant context. Record both outputs. The current draft must use Wednesday, name the newer note and preserve unknowns. For the second run, add a confirmed November 4 note changing availability to Thursday after 4 p.m. Mark Wednesday superseded. The revised draft must use Thursday after 4 p.m. and cite the November 4 note. Keep the context lean. A saved document is not a guarantee of retrieval or permanent memory.
The practice is a current authored companion, not a reconstruction of every field shown on the historical screen.
Editorial learner questions.
No. It is a maintained source you provide, and the tool can still miss facts or instructions.
No. The recording's rough heuristic is not a technical limit. Refresh when the task changes or outputs drift.
No. Storage, retrieval, project context and memory have different behavior. Check the product you use.
Relevant role, actual voice examples, sourced facts, task instructions and review boundaries.
When a relevant fact or preference changes. Keep the owner and last-reviewed date visible.
Identify the conflict, consult the appropriate current source and mark the older record superseded.
Selected caption excerpts from the historical recording. These are deliberately non-contiguous passages, not the full transcript. Current practice and corrections are written separately above; the original recording is unchanged.
But who is the AI? What is it doing? How is it helping you? Voice. How should it sound? Tone, vocabulary, how do you sound or how do you want to sound? How do you make it yours?
Knowledge. So, this is again kind of all those reference points like what are the key things that you can provide to this AI that it can't just go find on the internet or it hasn't been trained on.
A lot of people once they build it, they don't update it.
don't forget to update.
So make sure that you are showing examples as much as you possibly can of things that have worked or things that you uh like. So give it the real stuff, not just descriptions.
Is the context lean? So is this what's required for this project?
Define a bounded job before asking AI to produce it.
Use source facts and explicit criteria to judge the result.
Keep a reversible version of a request that works.
After the freshness check
The context exercise shows why a current source matters. The Agent Constraint Accelerator is an option when you want help applying that discipline to your own business workflow.