标签：#product

Hire AI employees that live in your Slack, Teams, Telegram Discussion | Link

Installs your API into a customer's codebase in one command Discussion | Link

Turn photos into 3D Gaussian Splats on your Mac Discussion | Link

Review AI edits like stacked PRs at generation time. Discussion | Link

Every inventory tool says real-time. Every single one. Open the settings. Find the sync frequency configuration. It says 15 minutes. Or 10. Or 30 on the cheaper plan. That's not real-time. That's a cron job. There's a meaningful architectural difference and the industry has collectively decided to pretend there isn't. I want to make the technical case for why this matters — and ask why so few tools have actually fixed it. What "real-time" actually means technically Real-time in distributed systems has a specific meaning. It means the system responds to events within a bounded, predictable latency — not on a schedule. javascript// This is NOT real-time — this is scheduled // Latency: up to 15 minutes (the full interval) setInterval(async () => { const stock = await getSourceOfTruth(); await syncToAllChannels(stock); }, 15 * 60 * 1000); // This IS real-time — event-driven // Latency: network round-trip (~milliseconds) orderEventBus.on('order.confirmed', async (event) => { const updated = await decrementStock(event.sku, event.qty); await propagateToAllChannels(updated); }); The first example responds to state changes on a schedule. The second responds to events as they happen. These are fundamentally different architectures with fundamentally different latency guarantees. Calling the first one "real-time" is technically incorrect. It's scheduled sync. The schedule is just short enough that most users don't notice — until they do. When users notice The failure mode is predictable and well documented: javascript// Flash sale scenario — 10x normal velocity const normalOrdersPerWindow = 500 / ((24 * 60) / 15); // ~5.2 const flashSaleOrdersPerWindow = normalOrdersPerWindow * 10; // ~52 // 52 orders processed against potentially stale stock // per 15-minute window // across multiple channels simultaneously // none of which know what the others have sold 52 orders per window. At 2% oversell rate — just over 1 oversell per window. Across 96 windows per day — nearly 100 oversel

I’ve rounded up the best smart speakers that let you talk to Alexa, from the popular Echo Dot to the newest Echo Studio.

Session reports for Claude Code & Codex to improve your code Discussion | Link

Cloudflare Tunnels, managed from your menu bar Discussion | Link

The air purifier giant’s P50 pedestal fan is whisper-quiet and surprisingly versatile, even if its built-in voice assistant feels stuck in beta.

File manager for Linux homelab and NAS-style servers Discussion | Link

Teach your AI to build document templates Discussion | Link

Ship AI that stays on-brand Discussion | Link

Screen recording studio for Windows Discussion | Link

Discover new Codex plugins, sites, and annotations that help analysts, marketers, designers, investors, and other teams get more done with AI.

Frontend automation has been getting pretty wild lately. 🫠 A few months ago, this comparison would...

Hey fellow productivity nerds, We’ve all been there: piling 50 hours of tasks into a 40-hour workweek, only to feel completely burnt out and defeated by Thursday. Remember The Milk is fantastic for capturing what needs to be done, but it doesn't inherently tell you if you actually have the time to do it. I got tired of constantly overflowing my schedule, so I spent some time leveraging MilkScript (RTM's automation engine) to build something I’m calling the RTM Agile Coach. It’s completely free and open-source. Basically, it transforms RTM from a passive checklist into an active, capacity-aware project manager. Here is what it actually does behind the scenes: ⏳ Precision Scheduling Engine: You tell it your working hours (e.g., 9 AM - 6 PM, Mon-Fri). It simulates your task list minute-by-minute. If a task hits 6 PM, it automatically carries the remaining hours over to the next working day. 📅 实时战略排期推演 (Schedule) • 预计完工: 2026-06-06 10:06:15 星期六 （注：排期表展示的预计完工是“最坏情况”（Worst Case）：如果你白天完全没时间做这个任务，晚上要搞到几点。） 🟢 [06-02(二) 10:29 - 10:39] 检查* 回复-0.33🍅 (10m) 🟢 [06-02(二) 10:39 - 11:39] 查询 材料？-1.00🍅 (30m) 🟢 [06-02(二) 11:39 - 13:40] 2.2.5-如何 -2.00🍅 (60m) 🟢 [06-02(二) 13:40 - 15:40] 3-2-1-在 更新 -2.00🍅 (60m) 🟢 [06-03(三) 09:00 - 09:05] 3. 验证-0.17🍅 (5m) 🟢 [06-03(三) 09:05 - 09:35] 弄清楚 是什么-1.00🍅 (30m) 🟢 [06-03(三) 09:35 - 09:40] 3. 验证-0.17🍅 (5m) 🟢 [06-03(三) 09:40 - 11:40] 准备 材料-2.00🍅 (60m) 🟢 [06-04(四) 09:00 - 09:05] 3. 验证-0.17🍅 (5m) 🟢 [06-05(五) 09:00 - 09:05] 3. 验证-0.17🍅 (5m) ➖➖➖➖➖➖ 🧨 标准容量耗尽 (转入加班推演) ➖➖➖➖➖➖ 🧨 [06-06(六) 10:00 - 10:06] 3. 验证-0.17🍅 (5m) (加班) ↳ 📉 * 阻塞瓶颈 : 高顺位任务占据加班通道，后续2任务被迫顺延。 🧨 [06-06(六) 10:06 - 10:06] 4.发放 ** (0m) (加班) 🧨 [06-06(六) 10:06 - 10:06] 4.发放**** (0m) (加班) • 目标死线: 2026-06-06 23:59:59 星期六 🌡️ Visual Workload Heatmaps: It generates a literal heatmap inside an RTM note. At a glance, you can see which days are 🟩 (idle/comfortable), 🟧 (saturated), or 🟥 (dangerously overloaded). 🌡️ 每日实时战略负载热力 (Load Heatmap) 🟨 06-02(二): 69% [ 5.2/ 7.5h] 🟢空闲2.3h 🟩 06-03(三): 35% [ 3.2/ 9.0h] 🔒含日

I don't identify as a gamer. I occasionally participate in board games or an amateur football match,...

Back in February, a friend asked me to join his hackathon team. My first reaction wasn't excitement. It was: "Can I even contribute anything?" I remember repeatedly telling him not to add dead weight to the team and to find someone better. He kept insisting that it didn't matter and that I should just join. The funny thing is, I still don't think I've done anything extraordinary since then. No big startup. No crazy achievement. No overnight success story. Mostly just hundreds of hours of learning, building random things, breaking them, fixing them, and realizing how much I still don't know. But today I caught myself doing something weird. I'm the one thinking about who to bring into a team. And for the first time, I don't immediately feel like I'd be dead weight. Not because I know everything now. Just because I've reached the point where I can look at a problem and genuinely believe that, given enough time, I'll figure out how to contribute. It's a small shift, but it feels important. A few months ago I was wondering if I belonged on a team at all. Today I'm wondering who should be on mine. 👀

A security reviewer finds a critical issue a day or two before the release of an application. While it's an important issue, it sets the team back weeks, frustrating their product management partners and customers. The review came at the most expensive time in the process. There are many examples of how work items move through different processes to deliver software in large companies. While GenAI has allowed us to rapidly create code, it also moved and exposed the bottlenecks in our processes. It has also caused us to re-examine where it is most effective to make certain decisions. This is the challenge, and a deliberate blend of automated, programmatic, and human judgment is well suited to help you solve it. We can borrow from the well-trodden path of value stream mapping here. It is useful for spotting bottlenecks and waste in a given process, but it's also valuable to ask the deeper question of who or what should own each step. Each option earns its place differently. Is there an earlier step that may reduce costs with an agent where it was previously limited by human availability? Or is the stronger determinism of a programmatic step more important for a critical piece of the flow? Some decisions should stay with human judgment, where confidence without context is a liability. The opportunity for security teams and other stakeholders is to scale their impact across these options rather than scaling headcount. Workflow-as-code is not a new idea. There are a number of existing engines where the workflow definition is its own entity, separate from the work itself. GitHub Actions defines pipelines in version-controlled files, while the execution happens on separate runners. Airflow and Temporal follow a similar pattern for data and application workflows. Because the definition lives on its own, a team can change how a given step runs without rebuilding the whole flow. That separation is what makes it practical to adjust who or what owns each step over time. Rather

TL;DR Day 1 of AI Native DevCon was a practical reality check for AI-native software...