How it stays current
Every answer, with the day it was true.
Every shared record your company has ever kept died the same way: it went stale, people noticed, and they quietly stopped trusting it. That is the honest objection to a context layer, and it deserves an honest answer — not a promise to keep it updated. Four mechanics, and the receipt behind every answer.
Context drift
Reality moves. The document does not.
The decision gets made in a meeting. The scope changes in Slack. The ticket moves in Jira. And the context your AI reads — the file, the wiki page, the onboarding doc — records none of it. Nobody lied. The work simply moved faster than the writing.
This is why stale context is worse than no context. An AI with nothing to go on says it does not know. An AI with a six-week-old plan writes you a confident, fluent, wrong answer — and the board reads it on Thursday. Freshness is not a feature you bolt on. It has to be the thing that holds the record up.
Four mechanics
How it stays current. Not how we hope it does.
Captured where the decision happens
Nobody types the context in. In Parallel joins the meeting and reads the threads, so a decision enters the record at the moment it is made — not when someone remembers to write it down. The job of maintaining the file is removed rather than reassigned.
Stamped with when it was true
Every record carries two timestamps: when it happened, and when it was captured. Your AI does not just get the fact — it gets the date the fact was true, so “as of Tuesday’s review” is something it can actually say.
Traceable to the meeting it came from
Every record names its source and links back to it. If an answer looks wrong, you do not argue with the AI — you open the meeting it came from and check. A claim you cannot trace is a claim you cannot trust.
Explicit about status
A decision is proposed, reviewing, approved, or rejected — and it says which. Goals whose date has passed without a review are surfaced for triage rather than left to rot. Nothing quietly presents itself as settled when it is not.
Anatomy of an answer
What your AI actually receives.
“Every answer carries its source” is easy to write on a website. Here is the thing itself — one decision, as your AI reads it over MCP. Illustrative content; the fields are the real ones.
Decision
approved
- What was decided
- Volume calculator cut from the pricing page launch
- title
- Status
- Approved
- proposed · reviewing · approved · rejected
- Why
- The calculator needed pricing tiers that are still under review. Shipping the page without it beats holding the page for it. Revisit once tiers are signed off.
- rationale, captured from the discussion
- Who decided
- Named, with the room that agreed it
- decided_by
- When it was decided
- 14 July 2026, 10:00
- occurred_at
- When it was captured
- 14 July 2026, 11:36
- created_at
- Where it came from
- Pricing review — opens the meeting it was said in
- source + link
- Who can see it
- The workspaces it belongs to, and nobody else
- scope
No summary of a summary. The claim, the reason behind it, the person who made it, the day it was made, and a link to the room it was said in — so “where did you get that?” has an answer that does not depend on the model’s memory.
Read it. Correct it.
Captured automatically. Not beyond your reach.
Automatic capture earns the freshness. It does not earn infallibility. A record your people cannot correct is one they will learn to work around — so the record stays open, in plain language, and anyone who knows better can fix it.
You can read what it believes.
The record is not a black box of embeddings. It is a list of decisions, risks, questions and commitments in plain language, each one openable. If you want to know what your AI will say before it says it, you can go and look.
You can correct it.
Wrong title, wrong rationale, wrong status — change it, from the app or from your AI. A decision captured as proposed becomes approved when the team signs off. The correction sticks for everyone, not just for your chat session.
You can put it in the right place.
Context captured against the wrong workspace can be reassigned to the right one. Questions get resolved, commitments get closed, goals past their date get extended, finished, or archived.
Who decided stays fixed.
You can revise a rationale; you cannot quietly rewrite who made the call. Attribution is part of the record, not a mutable field — a revision belongs in the rationale or in a follow-up decision.
Honestly
What this does not do.
It will not read a decision nobody said out loud. If the call was made in a corridor and never spoken about again, no context layer will catch it — ours included. It will not stop two sources disagreeing; it will show you both, with their dates and their origins, and leave the judgement where it belongs. And it will not make a badly-run programme well-run. It makes what your company already knows available, current, and traceable. The deciding is still yours.
Ask it something you already know the answer to.
That is the only honest test of a context layer. Connect it, ask about a project you know cold, and check the answer against the receipts. The full product is free for 20 days.
- Who can see what →
The access model, in plain language.
- In Parallel vs context files →
Why a CLAUDE.md drifts, and this does not.
- In Parallel vs built-in AI memory →
Why per-tool memory never reaches your team.