标签：#Product

Quick, creative video subtitling with direct canvas control Discussion | Link

Fourth of July weekend is the last great grill and griddle sale of the summer, including $250 off my favorite pellet smoker.

Everyone keeps saying AI will let a solo developer take down the giants. And everyone keeps saying the giants will just absorb everything. Both takes are wrong , and I spent a while reading the actual 2025 data to figure out why. I pulled from four of the biggest developer datasets of the year: DORA 2025 State of AI-Assisted Software Development (Google Cloud, ~4,867 respondents) Stack Overflow 2025 Developer Survey (49,009 respondents) GitHub Octoverse 2025 (behavioral data across 180M+ developers) JetBrains State of the Developer Ecosystem 2025 (24,534 developers) Here's the honest synthesis. It's more useful than either hype narrative. The one-sentence thesis AI collapsed the cost of writing software to near zero. It did not collapse the cost of distribution, trust, support, or being liable when it breaks — and those are ~80% of what a software business actually is. So the effect isn't "solos beat giants." The effect is that the middle got hollowed out . The 10-person, VC-funded, me-too startup building a feature is the loser of this era — squeezed from below by a solo who ships the same thing for free, and from above by a giant who bundles it. Solos and giants both survive. The undifferentiated middle doesn't. "AI is an amplifier, not an equalizer" This is the single most important finding of 2025, and it comes straight from DORA: "AI's primary role in software development is that of an amplifier. It magnifies the strengths of high-performing organizations and the dysfunctions of struggling ones." Read quickly, that kills the "AI levels the playing field" fantasy. AI rewards whoever already has good practices — not whoever is scrappiest. But read one layer deeper and it becomes the best available argument for the small team. DORA found the key enabler is independence of action — "the ability to develop, test, and deploy value independently, with little or no coordination cost." In an Adidas pilot they cite, teams in loosely-coupled architectures saw 20–30% produ

Turn to-dos into scheduled tasks Discussion | Link

Pressing enter to accept model suggestions now takes less effort than scrolling past it. One keystroke, and the code is yours. Reading it, understanding it, deciding if it's actually right, that part hasn't gotten any faster. That gap, between how fast we can accept code and how fast we can actually understand it, is where things start to go wrong. The new shape of technical debt We used to know where technical debt came from. Tight deadline, cut corner, # TODO: comment that nobody ever revisits. Rushing was the cause, and we could at least point to it. Now you can build up the same kind of debt on a calm Tuesday afternoon, no deadline in sight, just six suggestions in a row accepted because they looked fine and the flow felt good. Nobody rushed you, and the code still ended up just as unexamined. Same debt, just a different excuse. "It works" is not the same as "I understand why it works" Everyone knows that debugging is twice as hard as writing a program in the first place. So if you're as clever as you can be when you write it, how will you ever debug it? — Brian Kernighan, 1974 Fifty years later, the gap got wider. Kernighan was talking about code you wrote. At least you understood it once. A suggestion that compiles, passes the linter, survives code review and even comes with passing tests can still be standing on a wrong assumption that nobody caught, because nobody was reading it as code. They were reading it as output, and output that makes sense tends to get approved. Compiling is a low bar. Passing tests is a slightly higher one, depending on whether you wrote the tests, or its suggestion shaped or created those too. If it's the second, it's like grading its homework with its own answers. None of it tells you the logic is sound, that the edge cases are covered, or that it does what you actually needed, something we already learned every time we trusted code we didn't write. Somehow it's easy to forget it the moment the code appears inline, in our own edito

A full form backend you can test before paying Discussion | Link

Native code switching, better diarization, more languages. Discussion | Link

Connect your AI agent to postal mail Discussion | Link

Preserving authentic organic posting since the collapse. Discussion | Link

Turn 1 creative into every ad format, instantly Discussion | Link

We started using Jira to manage our internal development workflow. At first it worked fine, but once we outgrew the free tier, the cost became hard to justify. At $15 per user per month, we were suddenly looking at a bill that did not match how we actually used the product. What we Built We created WannaTrack, a lightweight project management tool designed for small dev teams that do not need enterprise complexity. The goal was not to recreate Jira. It was to remove everything we did not use. Key ideas : minimal agile board with no clutter or heavy configuration simple issue tracking flow fast interface for daily development work minimal setup and no onboarding overhead Migration from Jira One of the biggest concerns was switching tools without breaking our workflow. So we built a Jira import tool that lets you migrate existing tickets into WannaTrack without manual effort. This allowed us to switch internally without downtime. Where it is now We now use WannaTrack daily for our own development workflow and are opening it up to other teams who feel the same pain with traditional tools. If you are a small dev team, indie hacker, or startup looking for a simpler issue tracker without overhead, you can check it out here: https://wannatrack.com

Is PlayStation about to make the same mistake Microsoft made with Xbox One?

Debug AI agents by replaying and forking runs Discussion | Link

Available in select markets thanks to a partnership with Gigs, Motorola phone owners have one less hurdle to clear when signing up for a data-only eSIM before traveling abroad.

The goal is to start the day already briefed — not to spend the first hour becoming briefed. What follows isn't groundbreaking. It's just what pushing my own boundaries looks like in practice. The problem As a Tech Lead of a larger team, my mornings used to look something like this: open email, skim through multiple newsletters I subscribed to for staying current on AI and dev topics, switch to Slack, scroll through everything I missed, try to figure out what actually needs my attention, then check what code went into the repo in the last 24 hours. By the time I was done "catching up," a good chunk of the morning was gone. I knew there had to be a better way. Starting with Claude Cowork Claude's desktop app has a feature called Cowork, and within that, you can set up Scheduled tasks — automated tasks that run on a schedule. I set up two that run every morning: Newsletter digest: This one pulls in all the newsletters I received the day before and summarizes them for me, grouped by topic — AI-related first, then dev, then everything else. Instead of opening each email and scanning for what's relevant, I get a curated briefing in seconds. Slack summary: This gives me a full summary of yesterday's Slack conversations across channels, and more importantly, flags what actually needs my attention. No more scrolling through hundreds of messages trying to separate signal from noise. The only downside? The Claude desktop app needs to be open and running for these to kick in. It's not a dealbreaker, but worth knowing. I'll be honest — the idea wasn't entirely mine. When you set up a new Scheduled task in Cowork, a Daily Brief is literally the example they suggest. I just happened to already be poking around with something similar. A lucky coincidence. Taking it a step further with Claude Code One of the hardest parts of leading a larger team is keeping tabs on everything that changes in code. PRs get merged, features get shipped, bugs get fixed — and it's nearly impossible to

Bringing the ideas I've been thinking about for months into life has never been easier, thanks to AI agents. The basic intuition is—give it a prompt, it builds the whole feature, the result looks good. Done. It takes only minutes to build the same thing that would've taken hours otherwise. Yes, I know, everyone's doing that. Right? The reason I'm opening like this is to point out what happened afterwards. I tried to use the search bar, and it fired a request on every keystroke. Wait, what? I didn't do that. Of course I'd add a debounce here. But the agent didn't. Why? I didn't ask it to. I said—build me a search bar, and it built me one that works; but I didn't say exactly what I wanted. Also, I noticed that the search button changes color on hover, but I'd already told it not to do that. The agent forgot, it hallucinated. What's missing then? What was missing was I did not provide the agent with the exact decisions to work with the feature; or did not provide a proper reference point to fallback to, to remediate the hallucination. In other words, I did not provide it with a proper spec. Hence, it took the hidden decisions itself; even though it pulled the feature off. This is the core problem that Spec-Driven Development (SDD) solves. The Hidden Product Decisions Your AI Agent Is Making For You Here's what happens when you describe something to an AI agent and it generates code: lots of decisions get made. Let's take the search bar implementation as an example. Does the filtering happen on the client or the server? Does the URL update so results are shareable? What does an empty query show? Everything, or nothing? I tend to miss nitty-gritty details while reviewing tons of AI generated code in a short amount of time. The code works, the UI looks right, I move on… Every one of those is a decision that belongs to my product. If I don't make the decisions consciously, the agent takes them based on whatever pattern shows up most often in its training data. Take that se

With these high-tech automatic litter boxes, gone are the days of scooping and smells. Welcome to the future.

This hefty but nimble and highly customizable ebike makes the journey as important as the destination. Get where you want, and have fun along the way.

Talk to your to do list and get what's next Discussion | Link

Give Your AI Superpowers on macOS Discussion | Link