You need the reason behind a decision, not another vague summary.
OGAD (Off Grid AI Desktop) can answer questions using relevant work material that is available in its selected memory scope. That can include project documents, conversations and supported retained Pro work sources. It cannot reliably recall information it never received, that was excluded or deleted, or that retrieval did not find. Useful memory starts with useful sources.
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What does “memory” mean in a practical workflow?
Think of the task you want to complete: find a decision, recover a commitment or prepare for a follow-up. The app needs source material related to that question. It then retrieves relevant information and gives the model material to use in its answer.
That is different from putting every stored word into every response. A large archive does not guarantee that the right passage will appear for an unclear question. A clear project name, date or subject can help focus the retrieval.
For example, “What happened?” gives little direction. “What did we decide about the garden brochure cover in the review notes?” names the project, topic and likely source.
Which sources can support an answer?
The available sources depend on what you supplied, what supported features retained and which scope is active.
| Source | What must be true |
|---|---|
| Current conversation | The relevant information is in the available conversation context |
| Project document | You added a supported file and it was processed successfully |
| Other project conversations | They belong to the selected project and can be retrieved |
| Captured screen activity | Supported Pro capture was enabled and retained useful material |
| Meeting material | A supported workflow created and retained usable recording or transcript data |
| Other connected work context | The relevant connection and import path supplied usable information |
A menu entry does not mean a source has data. Check that the expected item exists before asking the model to reason about it.
The desktop implementation separates project knowledge search from broader memory search. The selected scope determines which memory tools are offered. Memory scope implementation.
How does a project help you get a better answer?
A project lets you focus the question on a specific body of work. Add relevant documents and keep related conversations together. This reduces the need to restate the same brief and helps you ask questions using a defined set of sources.
Suppose a small agency has a brief, review notes and an approved delivery checklist. Start with those three files rather than importing an entire shared drive. Check that each is readable and ask one question with a known answer.
From this project's brief and review notes, explain why the cover changed. List the stated reasons and cite each source. Separate the final decision from earlier suggestions.
If the files do not state a reason, the right result is an explicit gap. The model should not invent a client's motivation because the answer would otherwise feel incomplete.
Projects with supplied documents are a core workflow. Automatic capture of wider work context is a separate Pro capability on supported platforms. Linux beta108 provides core but does not bundle that Pro layer.
How do you ask a question that can be checked?
Use four pieces: subject, scope, desired output and evidence requirement.
- Name the project or person involved.
- Add the approximate date or source when you know it.
- Ask for a useful form, such as a short decision list.
- Require citations and an explicit statement of missing evidence.
For example:
In the brochure project, find the changes agreed in the latest review notes. Make a table with change, owner and stated deadline. Cite the source for each row. Leave a field blank if the source does not say.
Review the answer against the original passages. You can then turn confirmed items into your working checklist. Do not turn an inferred date into a commitment simply because it appears in a neat table.
For wider retained work, choose the appropriate memory scope and ask an equally specific question. If you stay in a project scope, do not assume the model searched all other projects.
Why can an answer miss something that is stored?
There are several stages between an input and a useful answer. The source must be captured or imported, processed, retained, retrieved and interpreted. A failure or mismatch at any stage can produce a gap.
| What you notice | Useful check |
|---|---|
| A document never appears in answers | Import status and whether its text was extracted |
| An old screen detail is missing | Capture state, exclusions, sampling gaps and retention |
| An answer uses the wrong project | Selected project or memory scope |
| A fact is present but not found | More specific names, phrases or dates in the question |
| A summary conflicts with a source | The original passage and whether the summary inferred too much |
Try search with a distinctive phrase from the source. If you can find the item manually, refine the question around it. If the item is absent, adding more detail to a prompt will not recreate missing evidence.
Does a longer context window mean perfect memory?
No. Context is the material a model can work with during a request. Stored history can be much broader, and retrieval selects relevant material from that history. Those are related but different limits.
A longer context can help with a larger input when the model and hardware support it. It also uses resources. It does not fix a missing document, incorrect source association or a vague query.
Begin with a bounded question. If you need a large review, split it into clear topics and inspect the sources for each before asking for a combined summary. This also makes the output easier to check.
What happens when work changes?
A saved source records what it contained at that time. Later decisions may supersede it. Ask the model to distinguish dates and versions, especially when several notes discuss the same subject.
For follow-ups, ask what the source says is open. Do not assume the app monitors another person's progress or knows that an outside action is complete. A suggested to-do needs confirmation when its state changes.
Retention and deletion also affect recall. If you remove source material, later answers may lose the evidence needed to explain an earlier decision. Keep important final decisions in a source you deliberately maintain.
Build a memory you can use
Start with one project, a few relevant sources and three real questions. Check each answer, correct missing inputs and keep the scope clear. That creates a useful work habit without expecting the app to remember everything perfectly.
Try OGAD with a project you already understand. Ask it to find one decision and show why the source supports it.
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