Chalked is the reply layer for Mac. Open a supported conversation and it prepares what you would actually say from the visible thread, live calendar and sourced working context. Press Tab to insert, hold fn to change the intended outcome by voice, then review and send yourself. Accepted or edited communication can become inspectable evidence, so later replies start smarter. Voice is optional. Nothing auto-sends.
I built Chalked because the hard part of replying usually isn’t writing a sentence. It’s reconstructing what you agreed, whether you’re free, and what this person actually needs.
Most tools either improve wording after you’ve made the decision, or pull you into another inbox. Chalked stays in the conversation you already opened: it reads a bounded slice, prepares a reply in the notch, Tab inserts it, and holding fn lets you change the intended outcome by voice. You still review and send it yourself.
The longer-term bet is that communication should become resolved work. Sourced commitments and decisions can improve the next reply—and give the AI tools you already use cleaner working context.
I’d especially value blunt feedback from agency owners, founders, consultants, recruiters and anyone whose important conversations span several apps: where does Chalked save real reconstruction, and where does it still get in the way?
the "hold fn to revise by voice" bit is what stands out to me over the usual reply-suggestion tools. curious whether that voice pass happens on-device or gets sent off to process, given it's touching your calendar and past commitments in the same breath - that's a different privacy bar than a normal dictation app.
Hi, this looks like a cool project. Is this available on pc? I'm curious about how exactly the app tracks what you write? What sources does it use to figure out the best thing to say?
abt the sourced facts u accepted before, if one goes stale do i hunt it down and delete it myself or does it age out on its own
Tab is the risky part. Typing a reply is slow enough that you re-check what you actually agreed to, and one keystroke removes exactly that pause. The failure mode I'd worry about isn't a bad reply, it's a good one with the wrong date in it, and that goes out faster than anything you wrote by hand. Anything it pulled from the calendar or an old thread should have to survive a glance before Tab does anything.
About Chalked for Mac on Product Hunt
“Your replies ready with your work's full context”
Chalked for Mac launched on Product Hunt on September 4th, 2026 and earned 89 upvotes and 7 comments, placing #14 on the daily leaderboard. Chalked is the reply layer for Mac. Open a supported conversation and it prepares what you would actually say from the visible thread, live calendar and sourced working context. Press Tab to insert, hold fn to change the intended outcome by voice, then review and send yourself. Accepted or edited communication can become inspectable evidence, so later replies start smarter. Voice is optional. Nothing auto-sends.
Chalked for Mac was featured in Mac (103.7k followers), Productivity (660k followers) and Artificial Intelligence (477.8k followers) on Product Hunt. Together, these topics include over 286.5k products, making this a competitive space to launch in.
Who hunted Chalked for Mac?
Chalked for Mac was hunted by Atticus Jackson. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how Chalked for Mac stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.