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Productivity AI Tools
Discover and compare the best productivity AI tools and software. Browse 882+ curated tools with reviews and rankings.
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Afterparty is an AI agent product that does the work that comes after a meeting. Your note taker records the call and hands over the transcript, and Afterparty finds every action in it and writes the draft that action calls for: the recap email, the Slack message, the calendar invite, the CRM update. It works on top of the note taker you already use rather than replacing it, and it draws context from your email, calendar and Slack so each draft goes to the right person in the right thread. It is built for anyone who leaves a meeting holding a list of follow-ups, and its purpose is to turn that list into drafts you simply approve. The product is framed around an everyday problem: note takers give you a list, and Afterparty does the list. Recording a call and producing a tidy set of action items is the first half of the work. The second half — writing the recap to the client, posting the update in Slack, sending the invite for the next session, moving the deal in the CRM — is still manual, and it is where meeting momentum is usually lost. Afterparty is aimed squarely at that second half, so the follow-through happens right when the meeting ends instead of waiting for someone to find the time. The first thing Afterparty does is catch every action, even the ones said in passing. From a sample kickoff transcript it pulls out commitments such as sending a list of store managers, sending a recap and pilot proposal with pricing by Friday, writing up a one page plan for leadership, setting up a sandbox account, checking with Dana about onboarding capacity, and booking a room for the prep session. If you do not have a note taker, you can paste a transcript or upload a .txt, .vtt or .srt file instead, so the same workflow applies to any meeting you can capture. Context is what makes the drafts usable. Before writing, Afterparty reads your email and Slack so each draft goes to the right person in the right thread. The example on the site shows an action to "Send Priya the recap and the pilot proposal" turning into a draft addressed to Priya Shah with the subject line "Pilot recap and proposal," written in your voice and referencing the twelve-week pilot across Harbor Street, Eastgate and Millbrook, the priced proposal coming by Friday, the one page plan, and the kickoff workshop on October 14. Afterparty also skips what is already done and asks when it needs something. For an action to send an NDA, it searches Gmail for "in:sent NDA Kestrel" to see whether the document has already gone out. For a one page pilot plan in Notion it raises a question — "What budget should the plan assume?" — with an answer field, plus "Answer and draft" and "Skip" options, so you can supply the missing detail or drop the action entirely. Nothing happens without you. Every action waits in Afterparty, and approving an email simply places a draft in Gmail or Outlook — you still press send. One click moves each approved item into the right app, and the agents move on to the next one. The product also learns from your edits. When you approve, edit or dismiss a draft, Afterparty notes who people are and how you like things written, and the next meeting's drafts start from that. A visible memory panel in the example captures details such as "Tom Becker: handles the sandbox and anything technical" and "You sign off with 'Talk soon, Alex'," and the rewrite example shows a bloated opening being trimmed down. You can read, change or clear this memory in Settings. Once your recorder is connected, the whole flow runs after every call. You connect the recorder a single time, every transcript arrives on its own, and the agents get to work the moment you hang up. Supported meeting tools include Granola, Fireflies, Fathom, Zoom, tl;dv, Google Meet and Gong. Under the hood, Afterparty's agents are strictly read-only. They look at your email, calendar and CRM for context, but they cannot send, post or change anything. Reading is also targeted: for each action the agents look up only what that draft needs, such as recent threads with the people from the meeting, your calendar around the dates that came up, or the CRM contact — and they only read while a meeting is being drafted. Drafts are written in the language the meeting was held in. Privacy is treated as a core promise. Your meetings, drafts and app data are never used to train AI models, and no other user can see them. Deleting your account in Settings removes everything with it: meetings, drafts, memory and app connections. The full details live in the privacy policy. The benefit is speed and completeness rather than another tool to manage. Recap emails, Slack posts, invites and CRM notes are ready before you are back at your desk, written with context pulled from your own tools, and every one of them waits for your approval. You keep the final say on every send, post and update. Use cases described on the site include sales and client meetings, where a kickoff call generates a recap email, a priced proposal follow-up, a one page plan for leadership and a CRM stage update in HubSpot; internal coordination, where an action becomes a Slack message asking a colleague about onboarding capacity; scheduling, where a follow-up session turns into a calendar invite; and document work, where an action to produce a one page plan is drafted in Notion. Each of these is drafted from the transcript plus the context already sitting in your inbox, calendar and chat. Afterparty connects to meeting recorders, email, calendar, chat, CRM and project tools, listing Gmail, Google Calendar, Outlook, Slack, Microsoft Teams, HubSpot, Salesforce, Attio, Notion, Linear, Jira, Asana, ClickUp, monday.com, Google Docs, Google Drive, Confluence, OneDrive, Granola, Zoom, Google Meet, Gong, Fireflies, tl;dv, Fathom, Zendesk, Intercom and GitHub, plus "many more." Pricing starts free at $0 a month for email and calendar drafts and five meetings a month with no credit card. Pro is $29 a month (or $290 a year, saving $58) for sends to every app, auto import, learning how you write, and 20 meetings a month. Max is $79 a month (or $790 a year, saving $158) for frontier models, your own instructions, six months of context and 60 meetings a month. Prices are in USD, and every plan includes the approval inbox and memory you control. Afterparty is, in short, the second half of the meeting. Your note taker delivers the list; Afterparty turns each item into a finished draft in the right app, with the context to send it to the right person, and leaves the final click to you — so the actions from a call get done while the call is still fresh.
SuperLocalMemory is a governed memory brain for AI agents, positioned as one local-first memory shared by every agent a person or team runs. According to its listing, Claude Code, Codex, Cursor, ChatGPT and any MCP or CLI agent share the same governed memory, so context learned in one tool is available to the others. The product's stated purpose is to give agents durable memory that is trustworthy rather than approximate. Instead of guessing, recall tells you whether a memory actually answers the question, is only related to it, or is missing entirely. It is aimed at people running one or more coding agents on the same project, and at builders who need memory to be governed, with profiles, roles, an audit trail and verified erasure wrapped around a core that runs on the user's own machine. The project is open source under AGPL-3.0 and built by Qualixar, described as an AI Reliability Engineering lab behind 10 open-source products. The maker's relaunch post describes a rebuild around failures that showed up only after the first versions could already save and retrieve context. The harder failure was that a retrieval layer usually returns the closest thing it has, even when that thing does not actually answer the agent's question. In a chain of agents this compounds: one agent saves a half-related note, the next one treats it as fact, and the error travels onward. A second class of problem appeared once several agents shared durable state. The team needed to know when a fact was true, which agent wrote it, and who was allowed to read it, and whether deleting it really removed the derived copies. Those questions, accuracy of recall and governance of shared memory, are the two axes the relaunch was organised around. The headline capability is governed recall that refuses to bluff. Queries return one of three labels: supported, related, or no answer. Memories that are merely similar are handed back separately and labelled as related, while something is only marked as an answer when a stored memory actually supports it. When several agents share one memory, that label travels with the handoff, so a downstream agent inherits the uncertainty instead of a false certainty. An optional Answer Check verifies recall, checked by Laya on the user's Mac or by Jev online. One commenter singled out this distinction as the most valuable part of the design, noting that returning no answer is more useful than passing a vaguely relevant fact to the next agent. SuperLocalMemory is presented as one memory brain for every agent rather than a separate store per tool. Claude Code, Codex, Cursor, ChatGPT and any MCP or CLI agent connect to the same governed memory, whether through the Model Context Protocol or the command line. The system is described as mesh-connected, and the relaunch is accompanied by a separate mesh product listing from the same maker. The stated benefit is continuity across tools: what one agent learns does not have to be re-explained to the next one. The stated risk, which the makers explicitly invite feedback on, is where shared memory helps and where it becomes dangerous when more than one coding agent works on the same project. That open question is the reason access control and labelling sit in the shared layer instead of being left to individual agents to handle. Beyond text, the product includes optional local picture and PDF memory. Users can find pictures and PDFs by describing them, using Google's EmbeddingGemma 2. Memory is also time-aware: recall takes time into account, and every fact keeps a record of who wrote it and when, and the system tracks when each fact was true. The research behind the product describes related machinery, including a full cognitive memory taxonomy, adaptive forgetting, a memory lifecycle modelled as Langevin dynamics rather than hand-tuned decay, a retrieval metric drawn from information geometry, a distance metric that prefers full-fidelity embeddings over quantized ones, and a formal way to detect contradictions between memories. Governance is the V4 layer of the system. It enforces profiles, scopes, roles and role-based access, maintains a hash-chained audit trail, and offers verified erasure so that deleting a memory can be shown to have removed it. The first preprints describe local-first memory for multi-agent AI with a defence against memory poisoning through isolation and Bayesian trust scoring, and no cloud or LLM calls. Reliability claims are presented with unusual candour: the V4 paper opens with a negative result, reporting ten mechanisms that were implemented and reachable on a live call path yet ineffective at their final connection, plus two mechanical checks added to tell implemented, reachable and effective apart. Fault-injection testing of the write path covered eleven scenarios each run 200 times, holding 2,199 of 2,200 scoped properties. Measured properly, a governed write takes 11.0 ms, and most of that is described as the cost of durability rather than governance. The overall approach is local-first and evidence-led. The core memory path runs on the user's machine, so memory does not have to leave it. Memory is stored as facts rather than loose text; facts are ranked so that recency and relevance are respected, and old memories are forgotten. Everything is open source under AGPL-3.0, and the design is backed by four arXiv preprints published between February and August, covering local-first memory for multi-agent AI, the mathematical foundations of retrieval and forgetting, the cognitive taxonomy of the living brain, and the V4 governed memory system. According to the co-authors, each paper added something the product actually ships. Benefits stated or directly implied include a reduction in compounding errors across agent chains, because related-but-wrong context is labelled instead of silently promoted to fact. Users get continuity: one memory shared across Claude Code, Codex, Cursor, ChatGPT and other MCP or CLI agents, so context carries over between tools and sessions. They get provenance for every fact, the ability to know when a fact was true, and an audit trail of what happened. They get to enforce who can read what, and to demonstrate that data was erased. They also retain control over where the core runs, since it sits on their own machine, and they can inspect the implementation because it is open source. Concrete scenarios described in the content include running more than one coding agent on the same project and sharing memory between them; finding pictures and PDFs by describing them rather than by filename or folder; recalling a fact while knowing whether it is still true and which agent wrote it; and applying roles and scopes so that different people or agents see different parts of a shared memory. Another scenario is the handoff between agents, where the supported, related or no-answer label is passed along so the receiving agent does not treat an approximate memory as an answer. The makers also invite technical readers to examine the evaluation of the write path under fault injection, which speaks to teams that need reliability evidence before trusting governed memory in production workflows. The audience is developers and teams working with AI coding agents, particularly people running more than one agent on the same project, along with anyone building on MCP or CLI agents who needs shared, governed memory. Integrations named in the content are Claude Code, Codex, Cursor, ChatGPT, and any MCP or CLI agent. Google's EmbeddingGemma 2 powers picture and PDF retrieval, while Laya and Jev perform Answer Checks locally and online respectively. The launch is listed as Free and categorised under AI Coding Agents and LLM Memory, with topics including Open Source, Developer Tools, Artificial Intelligence and GitHub. The project is open source under AGPL-3.0, with code hosted on GitHub under Qualixar, and makers Arun Pratap Bhardwaj, Varun Pratap Bhardwaj and Garima Singh are listed on the launch. SuperLocalMemory's primary value proposition is memory an agent can be trusted with. By refusing to answer when the stored evidence does not support a claim, by keeping provenance and time attached to every fact, and by wrapping a locally running core in roles, an audit trail and verified erasure, it aims to make shared agent memory both useful and safe across the tools a team already uses.
Reelbird is a free, open-source screen recorder for macOS 15 and later. It records your Mac screen, camera and microphone, and a share link is on your clipboard the moment you stop recording. Later you can add auto-zoom, a smooth cursor and captions, then update that same link. It is built for Apple silicon Macs, requires no account, and is MIT licensed. Its main purpose is to combine the fast, link-on-stop workflow of Loom with the polished auto-zoom look of Screen Studio in a single take, for free, with the files kept on your Mac. The problem it solves is a split in existing screen recording tools. Loom gets you a link fast, but on its free Starter plan it stops each video at 5 minutes, keeps 25 videos, records up to 720p and offers no downloads, and it has no auto-zoom. Screen Studio produces polished auto-zoom videos but costs $29 a month, or $9 billed yearly, and its share link only exists after you export. Reelbird does both from one take, for free: the link is ready when you stop, the polish can come later under the same link, and every take is kept as MP4 files on your Mac. Reelbird sets no limits of its own. Where the alternatives still do more: Loom has comments, view counts and apps for every platform, and Screen Studio has a more mature editor and a signed download. Recording starts with a simple choice. You pick a display, a window or an area, and the shortcut ⌥⇧R starts a recording from any app. The picker shows windows to choose from, including ones on other desktops, along with switches for microphone, camera, system audio and Share while recording. Camera, microphone and system audio record as separate tracks, so screen, camera, microphone and system audio stay apart. Keeping those tracks separate means you can move the camera bubble or mute system sound after recording instead of committing at capture time. The recording bar shows the timer, microphone level, pause, restart, delete and Stop. Share while recording is the core of the workflow. With it turned on, Reelbird uploads a 1080p stream to your own bucket as you record. When you stop, a Shared popover shows the link with Copy, Open in Browser and Update Link, and the link is already on your clipboard. You can paste it anywhere and it plays in any browser a moment later, with no app and no sign-in. The link never changes, even when you update the video: after editing, Update link replaces the video and the URL stays the same, so everyone you already sent it to sees the new version. Polishing happens under that same link, whenever you have time. Auto-zoom follows your clicks and typing, with a Subtle to Punchy slider in the Zoom inspector and zoom regions marked on the timeline; a real export zooms in on each click, then out again, planned from the clicks in the recording. The cursor is redrawn from the log so it glides smoothly instead of jittering, and you can resize or hide it after recording. Preview and export use the same Metal renderer, so the file looks exactly like what you watched. Framing options include background, padding, rounded corners, shadow, and a camera bubble you can move after the fact. Audio and captions are handled on the Mac. Auto level measures your voice and sets it to −16 LUFS, so a quiet take comes out at a normal level. Voice enhance uses Apple's sound isolation to take out room noise and hum where your Mac supports it, then applies a gentle compressor, de-esser and presence lift. Ducking dips system audio about 12 dB while you speak and brings it back when you stop. Captions are made on your Mac by Apple's speech recognition; you can burn them in or offer them as a track viewers can turn on. Cut Long Silences finds pauses and removes them in one go, and any cut can be restored. Safe peaks put a limiter on every track and on the mix with a −1.5 dBFS ceiling so nothing clips. Reliability and output formats are designed around not losing work. Every track is written to disk in 2-second segments from the first frame, so if your Mac crashes Reelbird recovers the take on next launch, minus at most two seconds. Warnings for a silent microphone, stalled capture, audio drift, a filling disk or uploads falling behind show up during the recording rather than after it. Exports come in the usual formats: MP4 (H.264), HEVC, ProRes and GIF with hardware encoding, in landscape, square, vertical or 4:3. Overall, the architecture is deliberately simple. Your Mac records and uploads; your bucket — Cloudflare R2, S3, B2 or MinIO — stores the files; any browser plays them. Setup takes about ten minutes, once: a bucket, a scoped API token and a public URL, entered through endpoint, bucket, region, access keys, public URL and prefix fields and verified with Test Connection. Reelbird is native and light: Swift, ScreenCaptureKit and Metal, with no Electron and no third-party dependencies. A take is an open project format — a .reelbird folder of standard MP4s, JSON and an event log — so nothing is locked in. Privacy follows the same principle: nothing leaves your Mac unless you share it. Recordings, edits, captions and transcripts stay in ~/Movies/Reelbird. Captions and titles come from Apple's on-device frameworks, with no API keys and no cloud. Shares go only to the bucket you set up, signed with your own keys, and the secret lives in your Keychain. There is no account, analytics, telemetry, crash reporting or update checks. Links are unlisted, not secret: anyone with a link can watch, so share accordingly, and Stop sharing deletes every file under that link. Reelbird can also be driven by an MCP helper: adding it to an assistant exposes list_sources, start_recording, stop_recording and share, so you can ask for a 20-second demo of a settings page you just changed and get the polished share link back. The benefits follow from that workflow. Because the link arrives the moment you stop, you can share immediately and improve the video later without resending anything. Because the polish happens under the same link, you avoid re-exporting and re-sharing. Because the files live on your Mac and your own bucket, you control storage and cost — Cloudflare R2's free tier of 10 GB with free egress covers most people. Typical scenarios include recording a quick demo of a feature you just shipped, turning a raw take of a task app or settings page into a walkthrough with zooms and captions, recording a voiceover with system audio and ducking or muting it afterwards, and capturing automated demos on request through the MCP integration. Installation, platform and pricing are straightforward. Reelbird is free and MIT licensed, with no paid tier, watermark or export limit. Download the zip from the download page, unzip it, and drag Reelbird to Applications; it is signed with an Apple Developer ID and notarized by Apple, so it opens like any other app. You can also build it from source with git clone and make install using Apple's Command Line Tools, with no Xcode needed. It runs on macOS 15 or later on Apple silicon Macs, and version 0.1.1 shipped in October 2026. It does not work on Windows or Linux, and that is not planned, because Reelbird is built on Apple frameworks throughout. In short, Reelbird gives Mac users a free, open-source way to record the screen, camera and microphone, get a share link the moment they stop, and polish that same take later with auto-zoom, a smooth cursor, captions and audio cleanup under a link that never changes. With your own storage bucket, no account and no telemetry, it is a privacy-conscious alternative that combines Loom's speed with Screen Studio's polish.
Nostaliga is an iPhone and iPad app that turns your listening history into a personal timeline. Pick any song and see the day around it: your photos, places, runs, check-ins, shows and posts. The app brings your music, photos, workouts, walks, the places you have been, and the movies and shows you have watched into one timeline, so that a single track becomes an entry point into a period of your life rather than just a piece of audio. Nostaliga is made for anyone who has ever heard a song and been pulled straight back to a specific time and wanted to see that moment again, the photos that were taken, the route that was ridden, the place that was checked in to, and not only feel a vague sense of nostalgia. The app grew out of a very specific memory. The maker describes hearing "1-800-273-8255" by Logic and being instantly back in 2017, the first year he was cycling, doing long rides with that song on repeat. The song remembered those rides better than he did, but the routes and the photos from them were scattered across Strava, his camera roll and Last.fm. That fragmentation is exactly the problem Nostaliga sets out to solve. The music that triggers a memory lives in one service, the photographic evidence lives in another, the workout data in a third, and the check-ins, shows and social posts somewhere else again. Nostaliga anchors all of those threads to listening history, so instead of hunting through several apps for the same day, you can start from the song and let the app reassemble the context around it. The central interaction is deliberately simple: pick any song and Nostaliga shows you the day around it. The app looks through your listening history and brings back the photos, places, rides, walks and moments from the times you played that track before. Photos, places, runs, check-ins, shows and posts all sit in the same view, arranged around the music rather than around a date. This matters because most memory tools ask you to remember a date or scroll a photo library; Nostaliga starts from the thing that actually triggered the memory. The song is the index, and everything else, where you were, what you photographed, what you were doing, hangs off it. Nostaliga also includes an On This Day experience that works across the years. Instead of looking only at a single song, you can go back to the same date in earlier years and see what belongs to it. That gives the timeline a second axis: one direction from a song into a day, and another from a calendar date back through the years. Together they turn the app into something closer to a personal archive with two ways in, so the memory can be found whether you remember the music or the date. The app draws on a broad set of sources so the timeline is not limited to music. It works with Apple Music and Last.fm for listening history, Photos for imagery, Apple Health and Strava for runs, rides, workouts and walks, Swarm for check-ins, Trakt for the movies and shows you have watched, and Calendar for events. If your listening history does not live in those services, you can import your Spotify listening history, and you can also import your Twitter, Instagram or Facebook archives. Each of these sources contributes a different kind of evidence about a day, where you went, what you did, what you watched, what you shared, and Nostaliga's job is to line them up against the music. Underneath, Nostaliga's approach is defined as much by what it does not do as by what it does. There is no account, and there is no analytics or tracking. Your timeline is built and stored on your device, so the assembled record of your listening, photos, places and activity stays with you instead of being uploaded and held by a service. That makes the app a local, personal archive rather than a social or cloud product. The result is a timeline you can explore without signing up, without a profile, and without the sense that your memories are being collected by someone else. The benefits follow from that design. A song stops being only a song and becomes a way back into a particular stretch of life, the year you were cycling, the city you were in, the film you were watching that week. Because the sources are gathered rather than scattered, you do not have to remember which app holds which fragment; the timeline does it for you. And because the listening history is the organizing principle, the memory is triggered by the same thing that would have triggered it in real life: hearing the track. Finally, the on-device, no-account model means the value of the archive is not tied to a subscription or a login. Concretely, Nostaliga is used when a song brings back a period and you want to see it rather than only recall it. You might pick a track that was on repeat during a first year of cycling and use it to pull up the routes and photos from those long rides. You might use On This Day to revisit the same date in earlier years and see what you were listening to, where you checked in and what you were watching. You might start from a film or show in Trakt and work back to the music of that month, or start from a check-in in Swarm and see what was playing. If your history is spread across Apple Music, Last.fm, Strava, Photos and social archives, importing those sources is the first step in building the timeline you then browse by song or by date. Nostaliga is an iOS app for iPhone and iPad, listed under iOS, Music and Photography. Its connected sources include Apple Music, Last.fm, Photos, Apple Health, Strava, Swarm, Trakt and Calendar, along with imports for Spotify listening history and Twitter, Instagram or Facebook archives. It is free to use. Because it requires no account and performs no analytics or tracking, there is nothing to sign up for before you begin: the timeline is assembled and kept on your own device. The takeaway is that Nostaliga treats your listening history as the thread that ties your memories together. By combining music with photos, places, runs, check-ins, shows, posts and calendar events in one on-device timeline, and by letting you enter it either from a song or from a date, it makes rediscovering the days behind your favorite songs a matter of picking a track and seeing what comes back.
Daddy Issues is a companion app for dads, described on its own site as a way to "think ahead" and "fight less." At its core it delivers a weekly family briefing, built by AI around a dad's actual week. The product is aimed squarely at fathers who are involved, who care, and who already do a lot, but who still find themselves reacting instead of anticipating. Its stated purpose is to help dads stay one step ahead each week, before anyone has to remind them. To do that, it connects the elements that make up family life — kids, calendar, responsibilities and tasks — and surfaces what is coming up, what might be missing, and what is worth handling now. The problem Daddy Issues addresses is not a lack of effort or intention — the site says so directly. The failure point it names is timing. A dad may be present and helpful, yet still hear "Did you think about this?", still find out about things too late, and still end up reacting rather than anticipating. The app draws a sharp line between helping and owning: "If someone has to remind you, you're not ahead. You're catching up." It lists the roles a dad does not want to play — the one who gets reminded, the one who reacts late, the one who "helps" but doesn't lead — and sets the opposite as the goal: being the one who already handled it. Because that gap between effort and timing shows up as last-minute stress, repeated reminders and small disagreements, the product treats planning ahead as the thing worth fixing. The central feature is the weekly briefing. It is presented not merely as a summary but as an AI that "connects the dots you don't see." Each week it lays out what's coming up, what actually matters, what the AI spots early, and what to handle now. The briefing is built around the user's real week rather than a generic checklist, and it is designed to be acted on immediately: the user can turn briefing items into actions and add them to their calendar, then be done. The interface example on the site shows a week for Monday, April 14 containing a kindergarten trip on Thursday with a snack needed, a doctor follow-up that is overdue, and a birthday on Sunday with a gift still missing, summarised as "3 items need attention this week." A second core capability is that the app learns how a family works. As the user creates tasks, the AI understands patterns and begins anticipating what matters earlier. The stated result is that things stop slipping — including things the user had not been tracking before. This is a meaningful distinction from a static reminder list or a shared calendar: rather than depending on the dad to enter every future obligation, the system uses the tasks and routines he does create to anticipate what is likely to matter next. Over time that shifts the dynamic from catching up on what was already missed toward surfacing it while there is still time to act. The site describes a deliberately short path to value in three steps. First, connect your basics: calendar, kids and routines. Second, get your weekly briefing, which the AI builds around your actual week. Third, act early, before things pile up. The onboarding is positioned as lightweight — "Takes 1 minute · No setup stress" — with calls to action to "Start being ahead this week" or to "Show me my first week." The emphasis throughout is that the product should fit into an already busy life rather than adding another system to maintain; the dad supplies the basics, and the briefing carries the ongoing thinking work. Daddy Issues frames its approach as owning rather than helping. Its origin story reinforces that: it didn't start as an app but as a personal fix, built by a dad who was tired of being behind — trying to keep track of everything, still missing things, still being reminded. He built something that helps you stay ahead, described honestly as "not perfectly. But consistently." That combination — AI that connects the dots across kids, calendar, responsibilities and tasks, plus a weekly briefing rhythm tied to a real calendar week — is the product's distinctive method. Rather than issuing a stream of constant notifications, it consolidates anticipation into one recurring habit. The promised outcomes are relational as much as logistical: less stress, fewer reminders, more trust. The site sums this up by saying the user doesn't just help more — they take ownership. Read out, those benefits follow from the mechanics: because the briefing surfaces what is coming before it becomes urgent, there is less last-minute scrambling; because the dad is no longer the person who needs reminding, the recurring friction of who remembered what is reduced; and because he acts early, he is seen to be ahead rather than catching up. The tagline "Think ahead. Fight less." captures the same two-sided promise — better preparation and calmer family life. The example week on the site doubles as a set of concrete use cases. A kindergarten trip on Thursday surfaces early in the week, with the detail that a snack is needed — exactly the kind of small item that is easy to discover the night before. A doctor follow-up is flagged as overdue, turning a vague worry into a specific action. A birthday on Sunday is flagged because the gift is still missing, giving the dad lead time to sort it out. Elsewhere the site asks the question "backup clothes for daycare?" — another everyday logistical detail that matters only if it is handled before the morning it is needed. In each case the pattern is the same: the briefing names the item, then the dad turns it into an action and adds it to his calendar. The target user is explicit: dads. The site describes them as involved, caring and already doing a lot, and notes the product is "built for dads - by dads" and "built from real life. Made for yours." The expected starting task is to connect basics such as calendar, kids and routines. On privacy, the site states that it uses anonymous statistics to see how the site is used, with no ad tracking and no profiles, and that essential login storage always stays on, with a linked privacy policy at daddyissues.app/privacy. The product is accessible on the web at daddyissues.app, with "Log in" for existing users and a "Start being ahead this week" path for new ones. In short, Daddy Issues is not trying to make dads try harder; it is trying to change their timing. By connecting kids, calendars, responsibilities and tasks, learning from the tasks they create, and returning a single weekly briefing covering what's coming up, what matters and what to handle now, it aims to replace reacting with anticipating. The result it promises is less stress, fewer reminders and more trust — and the shift from helping out to taking ownership. For a dad who is already doing a lot and still hearing "Did you think about this?", that is the whole proposition.
Spinachi is a personal health manager that runs on WhatsApp. Rather than asking you to install and learn yet another app, it meets you in the messaging app you already open every day: you forward your lab reports to Spinachi on WhatsApp, and it reads them, sorts them, and keeps your health records — and your family's — in one place. From there you can see where you stand, how things are changing over time, and when your next test is due. Spinachi describes itself simply as "your health, finally in one place," and it is explicit that it is built for organising and tracking health information, never for issuing a diagnosis. The problem Spinachi addresses is a familiar one: health records do not stay in one place. A blood test arrives as a PDF in a family WhatsApp group, a thyroid panel is emailed by a lab, a knee MRI lives on a hospital portal, and vaccination slips sit in a drawer. When you want to know what your last reading was, whether things have changed since the previous test, or when you were last screened, you have to hunt through messages, downloads and paper folders. Multiply that by every member of a household and the picture gets messier still. Spinachi's premise is that the answer should live somewhere you already are, and that the record-keeping should happen for you rather than being another chore you have to maintain yourself. The delivery channel is the product's defining choice. Spinachi works through WhatsApp, so there is no app to download, no account to keep logging into, and no new interface to learn. You sign up for Spinachi and then simply forward your reports as you receive them. Because the entry point is a messaging thread, the workflow fits the way people already share medical documents with their families — the same PDF that lands in your chat can be passed straight to Spinachi instead of being lost in a scroll of messages. Once a report arrives, Spinachi reads it and sorts it. The website shows this organisation in action, with health records gathered together and individual files filed alongside labels such as Lab report, Prescription, Scan report, and Full body checkup. Example documents used on the site include Blood Test 2025.pdf, Knee MRI.pdf, Thyroid Panel.pdf, and Chest X-ray.pdf, sitting under folder-style headings for Health Records, Prescriptions, Lab Results, and Vaccinations. The point is not just storage but structure: instead of a pile of attachments, you get categorised records that can be found again when you need them. Beyond filing, Spinachi is designed to help you understand where you stand. It keeps your records in a form that shows how things are changing over time, so that a single reading stops being an isolated data point and becomes part of a pattern. It also tracks timing: Spinachi reminds you when a retest is due, so follow-up tests do not quietly slip past. This combination — a stored history, a view of change, and a nudge for the next test — is the core of what the product offers. The overall approach is deliberately minimal. You forward a lab report on WhatsApp; Spinachi reads it; Spinachi sorts it for you and your family; the record is kept in one place. There is no app to install, and there is no diagnosis. Spinachi states plainly that it never provides a diagnosis, which keeps its role clearly defined: it is a manager and organiser of the health information you already have, not a source of medical opinion. That boundary matters, because it means the product can be useful for storing and tracking records without making clinical claims. For users, the benefits follow directly from those choices. Records for the whole family end up in a single place rather than being distributed across chats, inboxes and drawers. You can see where you stand and how things are changing, which makes it easier to arrive at an appointment with context rather than guesswork. Retest reminders reduce the chance that a recommended follow-up is forgotten. And because everything happens inside WhatsApp with no app, the effort required to keep the record up to date is close to zero — the act of forwarding a file is the act of filing it. Concrete scenarios follow directly from the document types shown on the site. After a full body checkup, you forward the lab report and Spinachi files it so the results are not lost among other messages. If a household member has a thyroid panel done, the record joins a lab results history that can be compared against earlier tests. Scan reports such as a knee MRI or a chest X-ray are stored alongside the rest of the family's records instead of sitting in a hospital portal. Prescriptions are kept in their own place, and vaccination records are collected together so the household's paperwork is complete. Spinachi is aimed at individuals and families who want their health records organised in one place. Access is through WhatsApp, and getting started means signing up at spinachi.in/start. The service is presented without a download, which makes it approachable for people who do not want to manage another piece of software, and for households where one person ends up holding everyone's paperwork. The takeaway: Spinachi turns WhatsApp into a personal health manager. Forward your lab reports, and they are read, sorted and stored with your family's records in one place. You see where you stand, how it is changing, and when your next test is due — with no app to install and never a diagnosis. The value proposition is straightforward: your health, finally in one place, maintained with the smallest possible amount of effort.
Table Canon is a tool for tabletop RPG game masters that turns uploaded game-night audio into a session recap, an outline, and a prep desk. It is built for the person running the game — the game master who wants to stay in the scene while playing and then sit down later with the whole night in one place. The product states its promise plainly: play the session, prep from the recap. Rather than asking a GM to write notes while the story is moving, Table Canon takes the recording of the session and turns it into written material the GM can actually use when preparing the next game. Callbacks from earlier sessions show up when you prep, so the campaign's own history becomes the source of future hooks. The site frames the whole product around a simple idea: solid foundation, lasting stories. The problem Table Canon addresses is stated directly on its site: you meant to write it down, but the scene had already moved on. Prep night should not start by reconstructing the last session from memory. Notes capture only what you had time to scribble during play, and a general chatbot only knows what you paste into it. Table Canon puts the recap, the outline, and the open threads in one desk, so a promise made three sessions ago can become next week's hook without pausing the table to record it. The goal is to let the GM focus on the game and then prep from what already happened, instead of losing the thread between sessions or hunting through old chats and documents for details that may never have been written down at all. The process begins with uploading a recording. The audio is the notes: you played, and the recording stands in for the note-taking you did not do. Today, on the web, a game master uploads an audio file from game night. Live recording on the mobile app and in the browser is described as coming soon. Also marked coming soon are optional GM notes for secrets and corrections, layered on top of the audio — a way to add information the recording alone would not capture. This approach keeps the GM inside the scene rather than at the edge of it with a notebook, and it means the record of the session is created automatically rather than depending on how much time anyone had to write things down. Once a recording is uploaded, the night lands in one place. Table Canon produces a transcript, speaker labels, an outline, and a Recap. The site states that this material is usually ready in about 15 to 20 minutes, depending on session length, and that users see a "Building your campaign…" indicator until the session is ready. Having the transcript, the speakers, the outline, and the recap assembled together means the GM does not have to piece the evening back together from scattered files, memory, or half-finished notes. The recap and outline are designed to be read before planning the next scene, so preparation starts from a written account of what actually happened at the table. Preparation then starts from that desk. The prep desk surfaces open threads, hooks, and the people who mattered during the session. Earlier nights resurface as callbacks, which is how continuity across a long campaign is maintained without manual bookkeeping. This is described on the site as "the desk you open on prep night" — a single place where the loose ends from previous sessions are already visible. Instead of asking the GM to remember which promise, faction, or unresolved question is still live, the prep desk collects those elements from the campaign's own history and puts them in front of the person planning the next game. The campaign's world is also kept current. Table Canon maintains NPCs, places, and factions that are updated from play, described as "a world that keeps up." When the AI gets something wrong, the site says that this happens and provides tools to fix it: voice samples can be calibrated for better speaker labels, and on any World dossier a GM can use GM corrections to fix names, blurbs, aliases, and mistaken duplicates, merging or marking them distinct. Reviewing the session Recap before sharing it is recommended, and corrections stick for Ask and future sessions. When a fact is fuzzy, the GM can ask — for example, "What did they promise the tavern keeper?" — and the answers cite the sessions they came from. That citation behaviour is a stated differentiator from pasting text into a chatbot: the memory is derived from play, with evidence. The site positions Table Canon against do-it-yourself approaches with a direct comparison. Taking notes while you play means you leave the scene; Table Canon keeps audio as the record and notes optional. Reconstructing the last session before you can even prep leads to scattered memory and old chats; Table Canon puts recap, outline, and prep in one place. Coming back next week and pasting into a new chat causes names to drift; Table Canon keeps the same campaign desk, updated from each night. Building a campaign wiki by hand drifts from what players actually did; Table Canon's memory is derived from play, with evidence. And asking "what did they promise in session 4?" normally means hunting old chats and docs, while Table Canon lets you ask with citations into your actual sessions. The stated outcomes for users follow from that design. After game night you get the night in one place: a recap and outline you can read before planning the next scene. You get a prep desk with open threads and hooks, including callbacks from earlier nights. And you get a world that keeps up, with NPCs, places, and factions updated from play. Together these pieces mean prep time is spent planning forward rather than reconstructing backward. The memory of the campaign evolves each session rather than being frozen at whatever was written down at the time, and answers about past events are backed by the sessions they came from. Concrete use cases appear throughout the site. A game master can upload a recording after game night and, roughly 15 to 20 minutes later, read the recap and outline before planning the next scene. During prep, they can open the desk to see open threads and hooks, including callbacks from earlier nights that become next week's hooks. When a detail is fuzzy, they can ask a question such as what the party promised the tavern keeper and get an answer citing their sessions. They can browse a real campaign from a live table — World, Story, and night-by-night Recaps — and try Ask on the sample campaign, including questions that pull from an earlier night, before uploading anything themselves. After a session is processed, they can review the Recap before sharing it, calibrate voice samples for better speaker labels, and use GM corrections on World dossiers to fix names, blurbs, aliases, or merge mistaken duplicates. Table Canon is built for the table and works with the systems game masters already run, listing Dungeons & Dragons, Pathfinder, Call of Cthulhu, and indie TTRPGs. The site notes that memory stays campaign-shaped, not system-locked. Pricing starts with a free tier: 6 hours of processed audio lifetime, no login and no credit card required, with the option to try as a Guest. Free access includes the full desk — campaigns, World, Story, Prep, and Ask — and the sample campaign tour can be explored without uploading anything. Plans are priced on processed audio hours once a user outgrows Free. The site states that session audio and campaign content run on your account only and are not used for public model training, and that live recording on the mobile app and in the browser is coming soon, while the web beta today supports uploading a session recording. Table Canon's core value proposition is that the session itself becomes the campaign's memory. By turning uploaded game-night audio into a transcript, speakers, outline, Recap, a prep desk of open threads and hooks, and an evolving world of NPCs, places, and factions — all searchable with answers that cite your sessions — it removes the need to take notes during play or reconstruct the last session from memory before prep. Game masters stay in the scene while playing, then open one desk on prep night where earlier nights surface as callbacks, corrections stick, and the story keeps its foundation from session to session.
Winq is a macOS app that turns your Mac's built-in camera into a hands-free input device. It lives in your menu bar and runs entirely on your Mac. Glance at a display to focus it, wink to click, and raise an eyebrow or make a face to fire a shortcut. Winq is made for people whose hands are busy, including multi-monitor power users, developers and creators, and people who want a lighter alternative on their hands because of RSI or limited hand mobility. It runs on macOS 13 or later on both Apple silicon and Intel Macs, and it needs no hardware beyond the camera your Mac already has. The problem Winq tackles is interruption. Hunting for the window you meant, reaching across displays or grabbing the mouse all pull your hands away from the keyboard, the pen tablet or the instrument you are holding. Winq replaces a few of those small physical actions with signals a camera can read reliably. Rather than acting as a full assistive replacement, it positions itself as a lighter option that works alongside macOS Head Pointer and Voice Control. The distinction from Head Pointer is deliberate: Head Pointer moves a cursor with your head, while Winq jumps focus between displays and windows, clicks with either eye, and runs app-aware shortcuts. Gaze focus is the first of Winq's three inputs. You look at a screen and it becomes focused. Gaze picks a display, or a window, not a pixel: settle on a target for a moment and Winq raises it and puts the pointer where you are looking, so your next keystroke or click lands there. The app describes it as like Command-Tab, but with your eyes. You can switch whole screens, or individual windows and panes when you have two to four big windows per screen. Both your head and your eyes count, so glancing with your eyes alone works too. An optional confirm keeps the target highlighted until you raise your eyebrows, and Winq never switches while you type or use the mouse, and never flickers at the edges. Because you look where you click, every click quietly improves accuracy. Wink clicks are the second input. A left wink is a left click and a right wink is a right click, so the two eyes are separate actions. A normal blink closes both eyes, so it is never treated as a click. Calibration learns how open and closed each of your eyes looks, and Winq keeps learning how far you really wink, even if you cannot wink one eye cleanly. A double wink double-clicks and a long wink drags. Glasses mode reads through reflections and glare. If you cannot wink at all, you can dwell to click by resting the pointer, or pull a mouth corner instead; the mouth pull left and mouth pull right gestures ship unbound and can be tried for left and right click. Face shortcuts are the third input, and Winq ships an eleven-gesture vocabulary that you can rebind. Each gesture can fire a keyboard shortcut, a Shortcuts shortcut, an AppleScript, a shell command or a Winq action, either globally or per app, so a nod can save in your editor and send in your mail app. Thresholds are relative to your own calibrated neutral face, and gestures pause while you are talking unless you turn on arming mode. Per-app profiles exist for your editor, browser, design tool and calls. The default bindings are: eyebrow raise, which also confirms a gaze switch, for Mission Control; head tilt left and right, done as a tilt and back, for previous and next Space; nod for Return; head shake for Escape; holding an open mouth to toggle dictation; holding a smile to take a screenshot to the clipboard; pucker, calibrated to you, to play or pause media; and mouth pull left and right, which are unbound by default. Setup is a dot calibration. A dot glides to a few spots on each of your screens, you follow it the way you normally look, and Winq learns how your head and your eyes move together. It takes about two minutes, and the app keeps learning from every click afterwards. While you calibrate, Winq rests: nothing clicks or switches. If you plug in a new screen, Winq offers to calibrate it from the notch, and a live Try it map shows the screen you are facing before you finish. The notch island shows clicks, gestures and switches briefly around the camera notch, and live view shows exactly what Winq reads from your face, as numbers. Under the hood, the pipeline is deliberately narrow. Frames come from your built-in camera through AVFoundation at up to 1280 by 720 and 15 frames per second. Apple's Vision framework performs on-device machine learning for face landmarks, right on your Mac. Winq's core then applies filters, detectors and your bindings to numbers, not pictures: what moves through the app is a small description of your face per frame, angles and eye openness, never an image. The resulting focus, click or shortcut is delivered through macOS Accessibility. Frames are processed in memory and thrown away, with no cloud, no disk, no account and no uploads, so zero frames are saved to disk or sent anywhere. The only things stored are your settings and calibration: head angles and eye measurements on your Mac, never images. The camera light is honest, and Winq's menu-bar icon shows when it is watching and when it is paused. The camera stops when your Mac locks or sleeps. Every setting lives in a plain config.toml that you can change in the settings window or your own editor. It supports global bindings plus per-app profiles by bundle ID, and every threshold is a setting, including settle time, typing pause and mouse guard. Shift-Command-G toggles Winq instantly from anywhere, and Winq also pauses when your Mac locks or sleeps. For tinkerers, this means the behaviour of gaze, clicks and gestures is fully inspectable and editable as text. The payoff is a lighter workflow. Gaze tracking is accurate enough to pick a display or a large window, which is all Winq asks of it; it does not try to point at pixels, because a webcam cannot do that reliably. Updates are signed and install from inside Winq, and every future update is included. Uninstalling is clean: removing Winq from Settings removes the app, its data and every permission. It works with glasses, and when the picture is too poor to be confident, Winq simply does nothing rather than guess. It asks for two permissions, Camera and Accessibility, each with a stated reason at setup. The scenarios Winq is built around are concrete. Multi-monitor power users stop hunting for the window they meant and simply look at the screen they want before typing. Developers and creators keep their hands on the keyboard, the pen tablet or the instrument while their face handles the switching. For RSI or limited hand mobility, Winq offers a lighter alternative to full assistive setups that works alongside macOS Head Pointer and Voice Control. Day to day, that translates into app-aware gestures: a nod that saves in VS Code, an eyebrow raise for Mission Control, an open mouth to toggle dictation during calls, or a pucker to play and pause media. Winq is a Mac app with one price. You get every feature free for one day from the first launch, with no account and no card. If it earns its place, you buy once: the listed price is $5.66, down from $7.98, described as a first-100 offer at 29 percent off. The licence includes gaze focus, wink clicks and all eleven gestures, every future update, and one Mac per licence, which you can move any time. The licence key arrives by email right away, and a portal is available to find your key again. Winq requires macOS 13 or later. It is not on the Mac App Store because App Store sandboxing restricts the Accessibility control Winq needs, so it ships as a download with automatic updates. In short, Winq turns the camera that is already on your Mac into three new inputs: gaze focus, wink clicks and face shortcuts, all processed on-device and controlled through a plain text config file. Look, wink, done.
Rambox is a desktop workspace manager that keeps your apps and accounts organized in ready-to-use workspaces, so you can switch contexts and stay focused. Instead of scattering work across browser tabs, windows and logins, Rambox brings the web apps you already use into one dedicated desktop application, where each client, project or role lives in its own clearly separated space. It is designed for people who work with many tools, accounts and contexts every day, whether on their own or as part of a team, and its core premise is stated plainly on its website: browsers are for browsing, Rambox is for working. Work today is spread across too many apps, too many accounts and too much switching. Rambox describes the challenge in four parts. Tab chaos buries important tools in a maze of browser tabs and windows. Account juggling means that moving between a work Gmail, a personal Gmail and a client Gmail forces you to log out, log back in and lose your flow. Notification noise breaks concentration throughout the day with constant alerts. And the question "where was that file?" becomes a daily puzzle when the file you need could be sitting in Slack, Jira, Notion or Drive, forcing you to search every app separately. According to Rambox, it should not take so much effort just to get back to what you were doing, and that friction is exactly what the product is built to remove. More than 80,000 users across 5,000 companies of all sizes have chosen Rambox worldwide, and its trust logos include Oracle, Amazon, Google, Atlassian and Adobe. The first pillar of Rambox is organization through workspaces. You group apps into workspaces for each client, project or role, and then switch the entire context with one click. Rambox calls these workspaces ready-to-use because they adapt to the way you work rather than forcing you into a single fixed layout. You can open tabs while working inside an app and return to where you left off later, and you can keep different contexts clearly separated so that client work never bleeds into personal or internal work. The product page emphasizes context persistence and improved tabs as part of the workspace experience, meaning the state of your work survives the switches instead of being reset every time you move between tasks. Rambox's second pillar is running multiple accounts without friction. The application lets you use multiple instances of the same app with different logins at the same time, so several mail accounts, messaging workspaces, social profiles or brand accounts can sit side by side. For freelancers, agencies and marketing teams this is the difference between working and continually signing in and out: rather than logging out of one account to reach another, each account gets its own instance inside the workspace it belongs to. The website frames this as perfect for managing several clients, brands or accounts side by side, and it is the feature that most directly attacks the account juggling problem described on the homepage. Finding things is the third pillar. Rambox provides one search bar, reachable with Ctrl K, to find what you need across apps like Slack, Jira, Notion, GitHub and Google Drive, rather than searching each application separately. This Unified Search is one of the newly added capabilities highlighted in the current release, and it is joined by the Command Center, which gives you quick access to your apps and common actions without disrupting your flow. The redesigned interface supports all of this with a cleaner layout, simpler navigation and fewer clicks to get things done, reducing the number of clicks needed to move between apps, workspaces, tasks and contexts. Rambox also notes a redesigned onboarding experience that makes the product easier to set up and understand, plus improved tabs and context persistence, and faster access to what you need. Focus is the fourth pillar, and it is where Rambox's built-in tools come together. Focus Mode and Pomodoro help you reduce distractions and organize your day into focused work sessions. You can mute everything and hide the apps you are not using, so the machine, and your attention, can breathe again instead of being pulled at by constant alerts. An AI Side Panel keeps your AI tools within easy reach while you work in your apps, so you do not have to leave your current context to use them. Desktop integration is what makes the whole approach possible: your web apps run in a dedicated desktop environment, so you are not constantly returning to the browser. The Product Hunt release notes for this major redesign add Quick View to the list of new tools alongside Unified Search, Command Center and the new focus features. Rambox's overall approach is additive rather than disruptive. The company states directly that Rambox does not try to replace the tools you already use, it helps you bring order to them. You keep your existing apps and services; you simply add them to Rambox and keep going. Setup begins with a free download for macOS, Windows or Linux, and no credit card is required to start. From there, you organize workspaces and accounts your own way, deciding which apps belong to which client, project or role. Advanced features are available when you need more control, so the product can start simple and grow with the way you work. The result is a single desktop home for all of your work apps, where context, not just the app itself, is the unit you switch between. The intended outcome is productivity without the noise: fewer tabs, less switching and more clarity in how you work every day. Instead of spending effort getting back to what you were doing, you spend it on the work itself. Because each workspace preserves its tabs and context, returning to a client or project restores the state you left, which reduces the mental reload cost of context switching. Because multiple accounts run side by side, you stop losing your flow to logins. Because Unified Search spans your apps, locating a message or file stops being a separate hunt through every tool. And because Focus Mode, muting and the AI Side Panel live inside the same workspace, protecting your attention does not require leaving your tools. Rambox also emphasizes that it is simple to start and powerful as you grow, with a free starting point and advanced features when more control is needed. Rambox lists several concrete groups it is built for. Freelancers and independent professionals use it to work with multiple clients, tools and accounts without mixing everything up. Marketing, social and analytics teams use it to manage several brands, platforms and logins at the same time, with each context clearly organized. Operations, support and admin roles use it to keep daily tools organized and switch between tasks quickly, without tab overload. Developers use it to switch between repos, environments and tools without losing context, staying focused on their code. The homepage also demonstrates a Personal workspace where chats sit side by side with unread counts and filters for all, unread, favorites and groups, illustrating how one workspace can replace a pile of browser tabs for everyday messaging. Rambox is used by people who work with many tools, accounts and contexts every day, whether on their own or as part of a team. For teams, Rambox offers a dedicated path that brings the same structure to the whole team, with shared setups and better control over apps and accounts. The application runs on macOS, Windows and Linux as a downloadable desktop workspace. Pricing follows a free-to-start model: the site repeatedly states that no credit card is required, that you can start free and upgrade later, and that advanced features unlock when you need more control. Downloads, plans and setup are handled through the official site at rambox.app. The takeaway is straightforward. Rambox turns a scattered collection of web apps and logins into a structured desktop workspace where each client, project or role is one click away, complete with its own accounts, tabs and focus settings. It does not ask you to abandon your tools; it asks you to stop letting them run your attention. Fewer tabs, less switching and more clarity, delivered through organized workspaces, multiple accounts without friction, cross-app search and built-in focus tools, all inside one desktop environment designed for getting work done rather than browsing.
AirJelly is an always-on desktop AI agent that its makers describe as the world's first context-aware proactive agent. It is aimed at people whose work moves faster than their notes, and its stated purpose is to bring scattered context together so that agents such as Codex and Claude Code can act with the full picture. According to the website, AirJelly reads across every app you use, including Slack, Zoom, Google Docs, Calendar and email, following the simple rule that if something is on your screen, AirJelly can see it. It is positioned as a second brain that organizes itself: the Product Hunt listing calls it a proactive, self-organizing second brain, while the site emphasizes that the agent knows who you are and what you are working on by observing your on-screen activity. 'The problem AirJelly addresses is context sprawl. The website frames it bluntly: you probably have twenty tabs open right now, and AirJelly is for anyone whose work moves faster than their notes. The fragments that matter — a confirmation in a team chat, a deadline mentioned in passing, a saved note you have forgotten about — get scattered across apps and rarely make it into a to-do list. Most AI assistants wait for you to ask before doing anything, which means the user still has to notice and remember. AirJelly's stated difference is that it watches your workflow continuously and acts before you ask, surfacing follow-ups, capturing tasks from conversations, and preparing briefs at exactly the right moment. It also tracks your personal interactions, so you never miss a follow-up or forget a promise. The product is built on three stated steps: watches, remembers and acts. Watching means capturing authorized screen context across your work apps, so the agent has visibility into the conversations, documents and meetings you actually work in. Remembering means building a living timeline of your work, where every task, meeting and message is searchable, forever. Together these two steps create the memory layer: a full log of everything AirJelly observed, across every app, which you can query at any time. The website describes this as moving from context to memory — gathering the scattered signals of a working day into one continuous record that does not depend on you writing anything down. Acting is the part users notice most. AirJelly surfaces what matters and then does something about it: it creates tasks, prepares briefs and sends reminders before you are asked, and its proactive alerts deliver follow-ups, reminders and briefs at what the site calls exactly the right moment. Because the agent has already watched and remembered the relevant context, an alert can arrive with the material attached — for example, a task created from a message, complete with due time and the conversation it came from. The company contrasts this with assistants that only respond to prompts, positioning AirJelly as a system that continuously works in the background rather than one that waits for instructions before it does anything at all. The website lists five core features built around how you work. The Daily Report is an end-of-day summary of what happened, what is pending and what comes next. The Timeline is a full log of everything AirJelly observed, across every app, so past work remains reviewable. Tasks are auto-captured from conversations, meetings and messages, complete with due dates and without the user writing anything down. Memory lets you ask about anything from your past work, anytime. Proactive alerts pull the other features forward by delivering follow-ups, reminders and briefs at the right moment. AirJelly's FAQ adds that task capture happens automatically from conversations, meetings and messages, with context and due dates included. AirJelly's overall approach can be summarized by the site's own progression: from context to memory, and then to action. The home page shows the loop as context for the agent, an activity log and deadline alerts, and it describes the mechanics in three numbered steps — watches, remembers, acts. One highlighted capability is bringing scattered context together so that Codex and Claude Code can act with the full picture. Practically, that means the agent converts your ongoing screen activity into structured context and memory, and then uses that memory to decide when a task, brief or reminder is warranted. The result is described not as a tool you operate but as an always-on companion that observes, retains and intervenes on your behalf. The stated outcomes are time and reliability. By managing everything in your life, AirJelly frees your time for what AI cannot do, or simply for you to enjoy. In practical terms, users get tasks that no longer depend on being written down, follow-ups that are not forgotten, briefs that are ready before a meeting, and a searchable record of past work that can be queried at any moment. The site groups the beneficiaries into four rough buckets: product, operations and engineering teams; founders and executives; researchers and PhD students; and anyone juggling more context than one brain can hold. The unifying benefit is that the user stops having to act as the memory system for their own work. AirJelly's site offers three concrete scenarios. In a product and operations setting, a meeting message became a task: the team confirmed a review in chat, and AirJelly caught it, created the task and attached the conversation, with the task created, the due time set and the context attached. In research and academia, fourteen tabs became one page: tabs spread across papers, docs and notes were read through and turned into a single research summary, including a note the user had forgotten they saved, with key points extracted and the past note surfaced. For founders and executives, an interview in thirty minutes was already prepared: AirJelly saw it on the calendar and prepared a brief with background, recent work and talking points. The FAQ adds that AirJelly also extracts tasks from conversations, meetings and messages automatically. AirJelly is a free download for Apple Silicon Macs and Windows x64 PCs, with Linux support described as coming soon. It reads across every app you use, with Slack, Zoom, Google Docs, Calendar and email named explicitly, and the rule that if it is on your screen, AirJelly can see it. Privacy is addressed directly: screenshots are encrypted and stored on your device, capture can be paused at any time, and specific apps can be excluded. The intended audience is anyone whose work moves faster than their notes — product, operations and engineering teams, founders and executives, researchers and PhD students, and anyone juggling more context than one brain can hold. There is also a Discord community linked from the site for users to join. AirJelly's pitch is simple to restate: instead of waiting for a prompt, an always-on desktop agent watches your workflow, remembers it as a searchable timeline, and acts — creating tasks, preparing briefs and sending reminders before you ask. For people whose work scatters across tabs, chats and calendars, that means less to remember and fewer dropped follow-ups. The product is available today as a free download for Apple Silicon Macs and Windows x64 PCs, with Linux support coming soon. The site's framing sums it up: stop asking, start working.