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Reddit · Projects

I spent a day poking Dots with sticks. Here's what I figured out.

I got access to Dots and spent much of the day trying to understand what actually runs where, what can happen simultaneously, and what counts as a separate worker. (I absolutely used AI to help me put this together. I don’t know if this audience cares, but I figured I’d disclose that up front since some folks get bent out of shape otherwise) The official material explains what Dots can do reasonably well. I found the execution model much less obvious. Some of this is documented; some is simply what I observed by using a Dot on several substantial real-world tasks. 1. The Dot really does have its own cloud computer I gave my Dot a large document-review assignment involving hundreds of PDFs and thousands of pages. It performed that work on what it identifies as its own cloud computer. This appears to be a persistent computer-backed environment where the Dot itself can do substantial, long-running work. More importantly, this isn’t just a five-minute “agent run.” One of my reviews is now clearly a multi-day job, and the Dot has maintained its place, absorbed side questions, and continued without needing me to reconstruct the task every few hours. That continuity may end up being more important to me than raw speed. 2. Delegated Work/Codex tasks are different While the Dot was working on one project, I had it try to launch a separate legal-research task. The launch failed because there was no available execution environment. Initially I assumed the Dot’s own computer was simply busy. But after the first job finished, the second task still could not start. The Dot then reported the key distinction: Its own cloud computer is separate from the execution targets available to the Work/Codex task launcher. So a Dot’s personal cloud computer is not simply a generic worker that delegated tasks automatically inherit. 3. A connected computer becomes another execution target I connected a spare Linux computer through the ChatGPT desktop app. The Dot could then see: \- its own cloud computer \- the connected Linux machine \- no saved Codex cloud environments I told it to launch the previously blocked task on the Linux machine. It did, and the task entered running state there. I did not have to sit at that machine and manually start a separate chat. I gave the instruction to the Dot, and it dispatched the task remotely. 4. Both can work simultaneously While the delegated task was running on the Linux machine, I gave the Dot a different assignment for its own cloud computer. It confirmed that both were active at once: Dot cloud computer -> Task A Connected computer -> Task B So that is genuine parallel execution across separate computer-backed environments. 5. Background agents don’t necessarily need a computer at all This was the part that got much closer to what I had originally imagined Dots would do. With both computer-backed environments occupied, I asked whether the Dot could create a native background research agent without using either computer. It said yes. I gave that agent a bounded research task and explicitly excluded computer/filesystem use. The Dot then reported that the background agent was running with read-only web/documentation tools and no computer target assigned. At that point, three things were happening simultaneously: 1. the Dot working on its own cloud computer 2. a separate task running on the connected computer 3. a native background research agent using neither computer That is the execution distinction I had completely missed from the launch material. 6. It can also context-switch inside a long-running job Another useful behavior appeared accidentally. While the Dot was deep into a large document review, I interrupted it with a factual question about one specific case. It paused the detailed review, checked meeting minutes and another source, resolved the question, updated its understanding of the case history, and then returned to the packet it had been reviewing. When I asked how it had done that “while continuing” the larger job, it clarified that it had not spawned another worker. It had simply switched attention within the same job and then resumed. So I now distinguish: Parallel execution = separate workers/environments active at once. Background agent = separate non-computer worker running concurrently. Intra-task context switching = one Dot temporarily branches inside an existing job, resolves something, and returns to its prior place. For long-running review work, that last capability is surprisingly valuable. 7. It can keep working while waiting for permission On another assignment, the Dot decided that spawning additional reviewers would accelerate the work, but my rules required permission first. It asked. But instead of stopping while waiting for me to respond, it explicitly continued doing the work itself. That sounds minor, but it matters. An autonomous agent that hits one permission boundary and then stops doing everything is not particularly autonomous. So far, the Dot appears capable of distinguishing: “I need permission to do X” from “I therefore cannot make any further progress.” 8. There is also a kind of manager-level queue I have not found a true native queue where a blocked computer-backed task automatically sits in the launcher until capacity becomes available. What I did find is that the Dot can apparently remember a pending assignment itself, periodically re-check execution targets, and attempt to launch it later. There are limits: \- the target list does not necessarily expose whether a connected computer is actually free \- there is no apparent capacity reservation \- a failed launch does not automatically become a queued Work task So this is more like the Dot acting as the queue manager than a native execution queue. Still, that potentially removes another piece of manual babysitting. 9. My current mental model At this point, I think there are at least three distinct execut
r/dry_towelette99
5 Things I Used ChatGPT Dots For—Real Prompts, Real Results

5 Things I Used ChatGPT Dots For—Real Prompts, Real Results

I gave my ChatGPT Dot five jobs from my actual life. Meet Norm: my AI helper for trip research, microphone shopping, untangling my to-do list, setting up a price watch and requesting a morning AI briefing. This is my hands-on experience with OpenAI's ChatGPT Dots, including readable excerpts from the real conversations—not a simulated live demo. Personal details have been cropped out. Five jobs in this video: 1. Research a family hiking trip and compare the logistics. 2. Compare microphone options and recommend a fit. 3. Organize messy notes into a practical checklist. 4. Set a daily price-check request with a specific threshold. 5. Request a concise AI-news briefing with sources. Travel research was still in progress. Shopping recommendations are Norm's, not my hands-on microphone tests. The price-watch conversation shows a setup confirmation, not a delivered future alert; the morning briefing shows a sample, not verified recurring delivery. No purchases or bookings are shown. What is the first everyday job you would give your Dot? Follow Krish Adavi here and on LinkedIn for practical AI. Builder tools and deeper articles: https://a2zai.ai AI Systems Brief newsletter on LinkedIn: https://a2zai.ai/briefs #a2zai #ChatGPT #OpenAI #AIAgents #AITools @OpenAI
@A2ZAI
ai.genel's Dot proactively handles invoice, Slack replies, and screenshots in parallel

ai.genel's Dot proactively handles invoice, Slack replies, and screenshots in parallel

早速dots使ってみてる肌感 ①同時に複数の対話・依頼ができるのが新体験 これまで） 自分「請求書作って」 GPT「こちら、請求書作りました」 dot） dot「請求書今月未対応っぽいよ」（喋りかけてくる） 自分「おお、やっといて あとslackの返事もしといて」 自分「あ、これらのケースXで事例としてアウトプットしたいからスクショも取っといて」 dot「了解～、請求書の対応進めます。」 dot「先にslackの返事を終え、スクショも保存済みです。」 ...しばらく時間が空いて dot「請求書完成したよ～」 要は、一回の出力を待たずにたくさんの会話・依頼ができる。 その上で、着実に全部に対応して、順次回答してくれる。人や、もう。 ②Slackのエージェントがイイ Claude Tagとか他にもこういう系ありましたが、ぶっちぎりで良さそう。 自身のコンテキストを全てもったエージェントが自分の代わりに回答も、作業もしてくれる。 ちょっとこれは色々実践したおして研究します。
GENEL | 動画生成AI
ChatGPT dots速報解説。今度こそ「自分専用の秘書」として活躍する未来がはっきり見えました。

ChatGPT dots速報解説。今度こそ「自分専用の秘書」として活躍する未来がはっきり見えました。

ChatGPT dotsがついに僕にもロールアウトされました！ そしたらさっそく、使い始めた初日から、忘れていたメールの期限を先回りして教えてくれたんです。 しばらく使ってみると、使えば使うほどに「自分専用の秘書」の未来が見えました。 ということで今日は、基本の使い方と、実際に驚いた体験を22分で速報解説します。iPhoneでの音声通話も収録しています。 【動画で使用したツール & 配布物】 ChatGPT dots OpenAIによる公式紹介はこちらです。 ▶︎ https://openai.com/ja-JP/index/introducing-dots/ dotsの始め方（公式ガイド） ▶︎ https://learn.chatgpt.com/docs/dots/getting-started 動画内の情報は2026年10月1日時点です。dotsは対象アカウントへ順次提供されています。 【目次】 00:00 使い始めて、笑っちゃうくらい楽しかった 00:54 dotsの基本 02:53 dotsの使い方 05:16 プレゼンだけでは伝わらなかったこと 07:17 メールの確認から、返信の下書きまで進んだ 09:19 Mac miniに置いた仕事の資料を使えた 11:08 作業チャットを動かして、結果を持って帰ってきた 14:01 これまでと同じでは？ 15:31 One more thing：音声通話 15:52 iPhoneからdotと実際に話してみた 20:11 音声通話を体験して感じたこと 21:10 まとめ：僕にとっては秘書 ツイッターとインスタ、やってます。 ▶︎ https://twitter.com/LeoTohyama ▶︎ https://www.instagram.com/leotohyama/ 使用素材 ▶︎ Epidemic Sound:http://www.epidemicsound.com ▶︎ Artlist:https://artlist.io/jp ▶︎ Motion Elements:https://bit.ly/2IyJhAx
@leo_tohyama
OpenAI Dots 實測：把耗時操作交給雲端電腦

OpenAI Dots 實測：把耗時操作交給雲端電腦

耗時的網頁操作一直占著本機？ 這次把批次任務交給 OpenAI Dots，讓它在雲端電腦執行。 從交代需求、生成與下載，到成果交回本機建檔，用一批配樂製作看看工作怎麼交出去、拿回來。 錄影當時，我們用自建 MCP 做任務交接，橋造好了。 後來 Codex 更新，片尾留了一個小插曲。 章節 00:00 認識 Dots 與 24/7 雲端電腦 00:27 把耗時網頁操作交出去 00:44 MCP 交接與電話確認 04:37 Dots 接手，開始雲端製作 05:53 成果怎麼交回 Codex？ 06:50 最後的小插曲 #OpenAIDots #Codex #AI協作
@SyrcusAI
Kevin Ly's Dot Dex reports his Codex project status from his Mac

Kevin Ly's Dot Dex reports his Codex project status from his Mac

I asked my AI where my project was up to. From my phone, it checked my connected Mac and found what was finished and what still needed building. This is OpenAI's Dot. I named mine Dex. Setup was simple: pick a name, pick a look, save. My existing account plugins loaded straight away, and Dex started suggesting things it could help with. What interests me most is having one place to ask about my Codex projects. It can work in the cloud and with files on my connected Mac, with the same Dot available on phone, desktop and web. You can call it too. My first call didn't connect, and the project lookup took a while and needed clarification. Early days, but being able to pick up my work without remembering which chat I left it in is something I'm keen to keep testing. #OpenAI #Codex #AIAgents
Kevin Ly
Reddit · Projects

The mindset shift that made Dots actually useful for me

When Hermes came out, and now with Dots, I saw a lot of people having the same problem I did. There was a ton of hype around having an always-on assistant, but it was hard to figure out what I would actually use it for. The shift for me was changing my mindset to: What do I already know is important to me, but I don't want to constantly keep my mind on? Once I started thinking about Hermes and Dots that way, I started finding a lot more useful cases for them. For example, in my use cases: Upwork: Keep an eye on new jobs and notify me when one actually matches what I'm looking for. Fantasy: Keep up with my team and suggest waiver pickups or help me evaluate trades when something comes up. Travel: Watch flight prices and let me know when there's actually a good deal. Not because the price changed $10, but because there's something actually worth my attention. I was originally looking at these assistants as something that should do my work or make decisions for me. What ended up being more useful was having them keep an eye on the things I already care about and bring them back to my attention when it matters. I still want to do the creative thinking and make the decisions. I just don't want to constantly be the one checking everything.
r/Playful_School6693
My Dot found an old planning doc on my computer by itself

My Dot found an old planning doc on my computer by itself

I tested OpenAI Dots on my own computer. I set up my custom Dot "Doletas" (orange sloth avatar), gave it read-only access to my machine, and asked it to review projects related to "Black" in my Nomics Workspace. Without further guidance, it autonomously searched my files, found an old Drive document from September 16 containing my "Planejamento de 16 de setembro", and reported back. It confirms Dots can browse local files, and Dots usage does not count against the GPT-6 Astra chat limit. First-hand test, screen-recorded on the creator own machine.
@viniparizottomkt
Dot proactively completed an invoice and Slack replies, unprompted

Dot proactively completed an invoice and Slack replies, unprompted

Quote-post from GENEL (動画生成AI, @ai.genel) quoting another user's first-hand Dots report (Japanese, translated): dot proactively entered Slack conversations without being mentioned ('it jumps in on its own — it's like a human'). The quoted user reports: dot flagged an unhandled invoice for the month on its own, then when asked, replied to Slack messages, saved screenshots for an X post, and later completed the invoice — handling multiple concurrent requests and responding to each without the user waiting on one output at a time. The quoting author adds: a Slack agent with full user context replying and working on their behalf is 'ぶっちぎりで良い' (far and away the best of its kind). NOTE: this card quotes another user's first-hand account verbatim inside a quote-post with the quoter's own commentary.
@ai.genel
My Dot rebuilt a YouTube video in 5 minutes while I drove

My Dot rebuilt a YouTube video in 5 minutes while I drove

최근 나온 dot가 궁금해서 바로 써봤습니다. 운전하면서 유튜브 링크 하나를 보내고 비슷하게 만들어달라고 했고, 영상을 분석할 수 없다고 하길래 웹에서 필요한 오픈소스를 내려받아 분석하라고 했습니다. 중간에 방향을 한 번 더 잡아준 것까지, 내가 요청한 건 세 마디 정도??. 이렇게 5분 뒤 오픈소스 3개를 주제로 한 26초짜리 영상이 나왔네요. 완성본이라기보다는 초안이지만, 운전하는 동안 이 정도 결과물이 만들어졌다는 게 꽤 놀랍고 당황스럽네요.
@solid.hwan
Overnight sprint: 3 GitHub projects, a draft PR, 193 tests, a take-home invitation

Overnight sprint: 3 GitHub projects, a draft PR, 193 tests, a take-home invitation

I told my dot: “Surprise me by morning.” The rules were simple: spend nothing, leave my existing projects alone, and pull an all-nighter. By 9 AM, Buddy had: • Published 3 new GitHub projects • Opened an independently audited draft PR • Passed 193 targeted tests • Sent 3 DevRel applications and received a take-home invitation I also asked it to turn the night’s work into a Blender city. That’s the video below. Each district represents something it worked on. Partway through, the cloud workspace reset. Buddy rebuilt the lost files, reran the checks, and saved everything again. I handled sign-in and permission approvals. No extra money spent. No earnings yet, but working code, a real contribution and a hiring conversation to follow up on. @OpenAI @ChatGPTapp @OpenAIDevs, this is what a night with my dot looked like. I’m open to paid, remote DevRel and technical-demo projects. Repos and PR in the replies 👇
@jhahimanshu653
My Dot made me a 55-second motion-graphics explainer video

My Dot made me a 55-second motion-graphics explainer video

な！！！なんとー！！ ChatGPTに仕事を任せられる「相棒」が登場したらしい😳 新機能「dots」に 「あなたは何ができるの？」って聞いたら、 できること・使い方・設定方法を55秒の動画にしてくれた💡 噂のGPT-6.1 Solでモーショングラフィックにしてもらった。 探す時間を、創る時間へ。 こういうAIの使い方、いいよね🌙 みんななら、何を任せたい？ ※順次提供中。利用できる機能はプランや環境によって異なりようです。 以下のプロンプトでつくりました。 ”あけみん”て入ってるから気をつけてね🤣 「dotsのできること、理想の使い方、設定方法を誰もがわかるような形でモーショングラフィックにして、あけみんぽく、誰もが目を引く感じで、ガチでよろしく」
@akemi.work
Projects

Dot 'benny' found a major bug while investigating another issue

i’m now doing all of my engineering work through my dot (benny) - it’s incredibly responsive, routes and delegates work across threads and cloud environments, and keeps track of all of my various tasks for me while proactively following up and pushing them forward. just now my dot told me that while looking into one issue it found another major bug in an adjacent function and asked if it should put out a draft PR. this is the way!
@rennsong
OpenAI dot 첫 사용 후기｜AI 비서 ‘닷율’에게 전화해봤어요

OpenAI dot 첫 사용 후기｜AI 비서 ‘닷율’에게 전화해봤어요

OpenAI DevDay 2026에서 발표된 dot을 직접 써봤습니다. OpenAI dots의 AI 비서에게 ‘닷율’이라는 이름을 붙이고, 꾸미고, 직접 전화해봤어요. UXUI·프론트엔드 강사 율쌤이 첫 사용에서 확인한 대화, 통화 요약, 작업 연결의 가능성과 한계를 담았습니다. 일반 챗봇과의 차이, Claude Cowork Dispatch의 데스크톱 작업 방식도 함께 살펴봤어요. 이번 테스트에서는 다른 Codex 세션으로 내용을 전달하지 못한 부분도 그대로 남겼습니다. AI를 실제 작업에 활용하는 법을 함께 배우고 싶다면, 바이브메이킹 클래스에서 만나요. AI UXUI 디자인·웹기획·프론트엔드 바이브코딩 과정 안내: https://www.vibemaking.kr/classes/ai-uxui-frontend-bootcamp ※ Shorts 설명의 주소는 클릭되지 않아 복사해서 브라우저로 열어주세요. 일정과 모집 정보는 클래스 페이지에서 확인할 수 있어요. 제작 기록 실제 통화 녹화본을 바탕으로 닷율과 함께 컷 편집·자막·모션그래픽·음량 보정을 진행했고, 배경음악과 효과음도 코드로 제작했습니다. 제 피드백을 반영해 화면과 오디오를 여러 차례 다듬었어요. 대화 화면 일부는 실제 대화를 모션그래픽으로 재구성했습니다. 음성에는 실제 AI 비서와의 통화가 포함됩니다. OpenAI 공식 소개 영상의 짧은 발췌도 포함했으며, 관련 공식 자료는 아래에 남깁니다. 공식 자료 OpenAI dots 소개: https://openai.com/index/introducing-dots/ OpenAI dots 기능: https://chatgpt.com/features/dots/ Claude Cowork Dispatch 안내: https://support.claude.com/en/articles/139470
@flowyullab
OpenAI Dots 첫 사용기 #OpenAI #dots #AI에이전트 #ChatGPT

OpenAI Dots 첫 사용기 #OpenAI #dots #AI에이전트 #ChatGPT

100달러짜리 ChatGPT Pro 구독에 딸려온 OpenAI Dots, 오늘 처음 써봤습니다. 전화로 한국어·영어 테스트 → 숨어 있던 예약 작업 찾기 → MCP 두고 브라우저 켜다 한 소리 듣기 → 앱 동기화 버그 수정까지. 처음엔 헛다리를 짚지만, 방향만 잡아주면 채팅방·Work·Codex 프로젝트를 오가며 일을 연결해 주는 중간 관리자 느낌. 근데 요금은 어떻게 되냐고 물었더니… 지도 확실히는 모른대요 ㅋㅋ #Shorts #OpenAI #OpenAIDots #Dots #AI에이전트 #ChatGPT #ChatGPTPro #Codex #MCP #AI뉴스 #AI툴 #인공지능
@WildDuckLabs
ChatGPTの新機能「Dots」で支出管理ツールを作ってみた

ChatGPTの新機能「Dots」で支出管理ツールを作ってみた

ChatGPTの新機能「Dots」で、支出管理ツールを作ってみました。 やったことは、チャットで「カードと銀行の明細から、プロジェクトごとにいくら使ってるか見えるようにしたい」と伝えただけ。 ・Dotsが連携方法を調べて提案 ・会計ソフトなしの「月1回CSVを入れる方式」に決定 ・明細CSVを渡して「進めて」と送る ・Dotsが指示書を書いて、Codexに開発を依頼 相談を始めてから、完成まで約15分。 できたのは、プロジェクト別の収支・明細レビュー・共通経費の按分までできる「月の帳」というツールです。 最初に提案された自動連携は外部サービスの利用料がかかるので見送りました。 まだ自分のMacだけで動く試作版ですが、「作りたいものを話す→できる」がここまで来たのは驚きです！
@AICommunityRIALA
A DOT-powered personal work archive inside solo Slack

A DOT-powered personal work archive inside solo Slack

슬랙을 혼자 써봤다. 여기에 DOT까지 붙여봤다. 합체 변신 ㅎㅎ 코덱스에서 이것저것 만들다 보니 세션도 많고, 하던 일도 여기저기 흩어져 있다. 어디까지 했더라… 찾는 것도 일이다. 그래서 슬랙에 모으기 시작했다. 내부 프로젝트 진행표, 메일 요약, 영상 소재. DOT한테 찾아서 정리해 달라고 하고 그 글에서 다음 할 일을 이어가는 식이다. 아직 써보는 중인데 뭔가 내 작업 아카이브가 생기는 느낌이다. 혼자 쓰는 슬랙도 이렇게 쓰니 쓸모가 있네. 쌓아두기만 하지 말고, 실제로 꺼내 써봐야겠다.
@autowanseong
Reddit · Projects

Dot as my DevOps bot — monitoring six self-hosted infra tools

Dots versus Jev I've started using Dots today as my DevOps & Analytics go-to bot, basically told it to monitor glitchtip (self-hosted sentry alternative), hetzner VM/server utilization and stats, self-hosted plausible analytics, google search console, logs, and git (self-hosted forgejo). Since it's for 6 apps with a combined 100 daily active visitors and absolutely zero revenues I thought what can go wrong well, the little guy went out started to come back with all of these great suggestions, like set up goals in analytics, fix small bugs and stuff which is starting to look like work really So I'm considering moving back to Jev, "is it broken yes no" and then ignore the answer. What kind of similar successes have you seen with Dots so far?
r/jacob_indie