Saying no is fast.Saying why is the work
A stakeholder asks for one more thing before the release. You already made the call, in a meeting three weeks ago, for reasons you would have to go and dig up. Khint drafts the answer with the trade-off attached, using the session where the decision was taken and the ticket where it was recorded, then leaves it as a draft you send.
The no takes a minute,
the reason takes an hour
Nobody struggles to type “not this quarter”. What costs the afternoon is everything around it: finding when the trade-off was decided, restating it without sounding dismissive, and writing it somewhere the next person who asks will actually read. So most refusals ship thin, get re-litigated in the next meeting, and the same request comes back in six weeks. Khint keeps the reasoning close to hand: your session holds what was decided today, and your Knowledge index holds what was decided in Jira and Confluence months ago.
Start a session before a task. Every capture, every run and every note you drop lands in it, in order, so the thread of what you were doing survives the interruptions.
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Jira
Confluence
Notion
Linear- Read active sessionMemory
- Search your KnowledgeKnowledge
- Reply to emailAgent
The reply lands here.
The real Memory and Knowledge surfaces: the running context of today's work, and a local index of your tools. Both stay on your machine.
From the ask to an answer that holds
A stakeholder emails: can we add multi-currency to checkout before the launch.
Keep the decision where you took it
Refusals are only defensible if the reasoning survived the meeting it was made in. Start a Memory session for the release, jot the calls as they land, and Khint keeps a compact running summary of the objective, the open threads and the decisions. That summary is what your agents read later, so the answer you send in three weeks is built on what the room actually said, not on your memory of it.
Select the request where it arrived
The ask lands in an email, a Slack thread, a comment on a ticket. Select it, press Cmd+Shift+K, and the palette opens over the app you are already in. An agent reads exactly what you highlighted, nothing else on screen, so a long thread can be narrowed to the paragraph that carries the actual request.
Run an agent that answers with the trade-off
Save an agent called “Answer with the trade-off”. No prompt yet? Type a one-line description and press Generate, then tighten it with Improve. Ask it for the four things a good refusal carries: the decision, the reason in one sentence, what would have to give to fit it in, and what happens next. Turn on the session-context option in the agent editor and it writes with the release context already in hand.
Let it look up the decision you cannot remember
For calls made months ago, index your tools in Knowledge. Khint keeps a local index of your Jira, Confluence, Notion and Linear content and passes the few most relevant excerpts to every agent, so the reply can cite the ticket where scope was frozen instead of paraphrasing it. The index is built on your machine and the search costs no credits. See how Knowledge works.
Answer where they asked, log it once
Connect Gmail and the palette adds a Create draft row, so the reply is waiting in your inbox for a last read before you send it. Then post the same reasoning as a comment on the request ticket in Jira, or as a short Confluence or Notion entry, and the next person who asks gets the answer without asking you. See how integrations work.
One shortcut for the answer you owe
Up to five steps in series: agents first, then the write that puts the answer where they asked.
Each step feeds the next, and a write step hands back its result, so the draft link comes out the end of the run rather than a paragraph you still have to place. Swap the last step for a Slack message when the request arrived in chat, or for a comment on the request ticket when the answer belongs on the record more than in someone's inbox. Build it by describing it: on the Workflows page, type what the routine should do and Khint drafts the steps for you to review.
What Khint will not do here
A refusal is a judgement call. The parts that stay yours, stay yours.
It does not make the call
The agent writes up a decision you already took. It has no view on your roadmap and no way to check a claim you did not give it, so a reason you never wrote down is a reason it cannot cite.
Nothing is sent for you
The Gmail step creates a draft, not a sent message. Writes to Jira, Confluence, Notion, Linear and Slack are explicit steps with a target you pick, so an answer only leaves your machine when you decide it is ready.
It reads the selection, not the screen
An agent sees the text you highlighted, plus the compacted summary of your active session if you turned that option on for it. The rest of the thread, and the rest of your desktop, stay out of the prompt.
Your decisions stay local
Memory sessions live in a local database on your machine and are never synced to Khint's servers, and the Knowledge index of your Jira, Confluence, Notion and Linear content is built and searched on the same machine.
Answer the tenth request as well as the first
The reason a refusal reads badly is rarely the wording, it is the hurry. Once the answer is an agent instead of a blank reply box, the request that arrives at 18:40 gets the same structure as the one you answered on Monday morning. Keep the agent in a pack with the rest of your stakeholder writing and share that pack with your team, so two product owners answering the same stakeholder do not send two different stories. When a batch of requests piles up in one thread, let Super Khint propose the replies and the ticket comments as a list, and run the rows you agree with.
Common questions
How does Khint help me decline a feature request?
It removes the two slow parts, not the decision. Select the request where it arrived, press Cmd+Shift+K, and run a saved agent that returns the answer in the shape a good refusal takes: the decision, the reason in one sentence, what would have to give to fit the request in, and what happens next. The agent can read the compacted summary of your active Memory session, so the release context is already in the prompt, and it can search your local Knowledge index for the ticket or page where the trade-off was recorded. You review the draft before anything is sent.
Where does the reasoning come from?
From two places you already have. Your active Memory session holds what has been decided today and this week, kept as a compact running summary that agents read when you turn the session-context option on for them. The Knowledge index holds older material: Khint syncs your Jira, Confluence, Notion and Linear content into a local search index on your machine, and every agent gets the few most relevant excerpts passed into its prompt. Neither replaces a decision you never recorded anywhere.
Can Khint send the reply for me?
It stops one step short, on purpose. With Gmail connected, the palette adds a Create draft row and the answer lands in your drafts for a final read. Writes to Jira, Confluence, Notion, Linear and Slack are explicit actions with a target you pick before the run, so nothing is posted to a ticket or a channel that you did not choose. Khint's Super Khint mode goes further in the other direction: it proposes each write as its own row and waits for you to run the ones you want.
Can I log the refusal on the ticket as well as answering the person?
Yes, and it is the part worth automating. Alongside the reply, a workflow step can add a comment to the Jira issue that carries the request, create a Confluence or Notion page for the decision, or post the summary to a Slack channel. A workflow runs up to five steps in series behind one shortcut, and each step's result becomes the input to the next, so the answer and the record are one run rather than two jobs you do in different apps.
Does my roadmap thinking end up in a chat history somewhere?
No. An agent only sees the text you selected plus the session summary you opted into for that agent. Memory sessions live in a local SQLite database on your machine and are never synced to Khint's servers, and the Knowledge index of your work tools is built and searched locally too. If a request thread contains personal data, you can also enable the per-agent redaction option, which replaces emails, phone numbers and similar identifiers before the text is sent for processing.
Give your next no a reason
Free with 300 credits a month, about 10 AI actions a day. No credit card. Save the agent once, and every request after gets the same answer.