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"You won't know until you do and then it is too late."

Most "AI email" demos never think about deletion. The agent reads, replies, files things away, and the inbox just grows. That's fine in a demo. It is a problem the first time a real person emails your agent, because the moment that mailbox holds someone else's name, address, order history, or support complaint, you've taken on a data-protection obligation — and "we kept everything forever" is not a defensible retention policy. An Agent Account on Nylas accumulates personal data you have to be able to purge. It's a mailbox the agent owns — support@yourcompany.com answering to a model instead of a human — and every inbound message lands in it. Under GDPR that data needs two things you can prove: a retention window so it doesn't live forever, and an erasure path so you can delete a specific person's mail when they ask. This post builds both, with the curl and the CLI for each step. A quick, honest caveat before any of it: this is a docs-and-demo walkthrough, not legal advice. The Nylas primitives below cover the mail held in the mailbox . Any derived copy you made — rows in your own database, lines in your application logs, a vector store you embedded the message into — is yours to purge separately. The API can delete the message; it can't reach into your Postgres. Keep that in mind throughout. What the platform gives you Nothing new to learn on the data plane. An Agent Account is just a grant with a grant_id , so everything you already know about Messages and Threads applies directly — listing, reading, and deleting mail run against the same grant-scoped endpoints any other Nylas integration uses. Retention and erasure split cleanly into two layers: Retention is a control-plane setting. It lives on a policy — an application-scoped resource that bundles limits and spam settings — attached to the workspace your Agent Account belongs to. Two fields cap how long mail survives: limit_inbox_retention_period and limit_spam_retention_period . Set them once and Nylas deletes a

Spam traps are the failure mode nobody puts in the demo. A bounce is loud — you get a 5.x.x back, your code logs it, you move on. A complaint at least gives you a webhook. A spam trap gives you nothing . The message gets accepted, no error comes back, and somewhere a mailbox provider quietly writes your domain down as a spammer. By the time you notice, your inbox placement has already cratered and you have no single bounce to point at. That's the trap, literally. And it's the one that bites autonomous agents the hardest, because the whole appeal of an agent is that it acts without a human watching every send. Point a model at a list it scraped, let it loop, and it'll happily mail a recycled address that's been a trap for two years. The agent never sees a problem. You only see the aftermath in your deliverability dashboard a week later. I work on the Nylas CLI, so the terminal commands below are the exact ones I reach for when I'm wiring up an Agent Account to not do this. The good news is that an Agent Account is just a grant — a grant_id that works with every grant-scoped endpoint you already know — so there's nothing new to learn on the data plane. The defense is mostly discipline: validate before you send, honor every complaint, and age out the addresses that never wanted to hear from you. What a spam trap actually is, and why it's not a bounce It's worth being precise here, because the three things people lump together behave completely differently. A bounce is a rejected delivery. The receiving server tells you the address is bad, you get a message.bounced event, and you stop. Bounce handling is a solved problem — you listen, you suppress, you're done. A complaint is a recipient hitting "report spam." The mailbox provider relays that back as a feedback loop, and you get a message.complaint event. The address is real and reachable; the human just doesn't want your mail. If you keep mailing them, you're training the provider to filter you. A spam trap is neither.

Spotify's Release Radar can now deliver more personalized music recommendations.

It's unclear how the planet avoided its star's bloated red giant stage.

Is paying a reasonable price for colorful cardboard too much to ask?

Hi, friends! Welcome to Installer No. 135, your guide to the best and Verge-iest stuff in the world. (If you're new here, welcome, crank the AC, and also you can read all the old editions at the Installer homepage.) This week, I've been reading about cold plunges and Colson Whitehead and the food truck mafia, […]

Roleplaying games are often defined by excess. Storylines that span dozens of hours, side quests so big they could be their own game, massive worlds that require complex maps to explore, and casts so big you start forgetting character names. That's part of what makes these games feel like epic adventures, but it can also […]

submitted by /u/Sankra [link] [留言]

Our weekly roundup of the best new indie games is here.

Hello, I'm Maneshwar. I'm building git-lrc, a Micro AI code reviewer that runs on every commit. It is...

Imagine you are sitting at a table in a restaurant. You have a menu in front of you with a list of delicious meals, and the kitchen is ready to cook them. However, there is a missing link. You are sitting in the dining room, and the chefs are tucked away in the back. You can't just walk into the kitchen and grab your food, and the chefs don't leave the stove to come take your order. To bridge the gap, you need a mediator. You need someone to take your order from the table, deliver it to the kitchen, and then bring the food back to you. That person is your waiter. In the digital world, an API (Application Programming Interface) is that waiter. The Plain English Definition An API stands for Application Programming Interface. Strip away the technical jargon, and an API is simply a software messenger that allows two different computer programs to talk to each other and share data. Think of it as a digital bridge. When you use an app on your phone, it doesn't contain all the data in the world inside its small download file. Instead, it uses an API to send a request over the internet to a massive server, which then sends the correct information back. The Restaurant Analogy: Side-by-Side To see how this works in real life, let’s map our restaurant experience directly to how technology works on your phone or computer: The Customer (You): This is the Client (your web browser, smartphone app, or computer). You are the one asking for information. The Menu : This is the API Documentation. It lists out exactly what items you are allowed to order and how you need to ask for them. The Waiter : This is the API. They take your request, run it over to the system, and bring you back the result. The Kitchen : This is the Server / Database. It holds all the raw data, processes the request, and prepares the final output. Where Do You See APIs in Real Life? You interact with dozens of APIs every single day without even realizing it. Here are a few common examples: "Log In with Google" or

submitted by /u/iximiuz [link] [留言]

The Story: Picture this: It is 10 PM. I was eating my dinner while adding one final touch to my social media app, Vlox. It should just say "Processing..." while generating a card. Simple, right? See the nightmare. 🔥 The Nightmare Scenario 📉 Suddenly, my "Download Card" button broke. htmlToImage started spitting out completely empty 0b images. The hunt was on. Failed Mission Log 🛰️ Attempt 1: Swap to html2canvas 🔄 Result: Error stating the element was not found in the cloned iframe. Verdict: The parent container was completely lost. Attempt 2: Use CoolAlertJS Toast 🍞 Result: It looked ugly and meant loading two different alert libraries for the same job? Not my game. Verdict: Total waste of bundle size. Attempt 3: Append to body + display: none 🙈 Result: The canvas process failed entirely. Verdict: Canvas snapshot engines completely ignore hidden elements. The "Aha!" Moment 💡 Why did the element vanish? Because the card generator lives entirely inside a Swal popup. When you click the download/confirm button, Swal instantly destroys that entire popup DOM tree. You cannot snapshot an element that no longer exists. 👻 The Ultimate Fix 🚀 Inside the new "Processing" popup, I appended the #card-generator-image-preview directly into the new alert container. The element stays alive in the active DOM. The snapshot succeeds perfectly. Clean code. Happy developer. Delicious dinner. Want to see the exact JavaScript code block that fixed it? Drop a comment below or check Vlox on Github .

Lately, I've been doing some deep personal reflection. I'm talking about myself, I hope no one misunderstands, on how pervasive the use of AI has become in my daily development workflow. Through a bit of self-analysis, I've discovered some interesting dynamics. Dependencies often arise from the desire to fill a void. But what kind of void does an experienced developer like me face? As a professional, I have the skills. Sure, AI helps me get things done faster, but the final product is always the translation of my vision; if I don't fully understand the solution, I discard it. I'm not looking for "magic," I'm looking for efficiency. Yet, I realize I've used AI to fill a specific void: the need for discussion. Software development is inherently solitary. The satisfaction of a successful "execution" after hours of discussions, refinements, and clashes over an architecture is an experience I miss today. The chat interface is always there, ready to respond. But there's a problem: it's a "yes-man." Even when I force it to be critical or provocative via the system's prompts, I know it's just reciting a script to please me. There's no conviction, no risk of error, none of the friction that arises when a colleague courageously defends their vision, perhaps one that conflicts with mine. We are part of a huge community, but debate often remains superficial. One might argue that posts and comments are enough, but anyone who has tried knows it doesn't work very well: a debate is truly alive only when there is no latency. In comments, the time between thinking, writing, and waiting for a response diminishes the energy of the exchange, turning it into a series of monologues rather than a dialogue. Why don't we try creating "virtual tables" where we can discuss projects, architectures, and technical choices with the natural rhythm of a conversation? Direct, real-time discussions, in person or remotely, where the exchange of ideas can spark sparks, without the filter (and delay) of

Markdown to HTML: The Fastest Way to Convert Markdown Online Markdown is one of the easiest ways to write documentation, blog posts, README files, and notes. The only problem is that many platforms require HTML instead of Markdown. Instead of installing software or using complicated editors, you can convert Markdown directly in your browser. I built MDConvertHub to make this simple. It lets you: Convert Markdown to HTML instantly Preview the output before copying Work completely in your browser No signup required Free to use I started building MDConvertHub because I wanted a collection of small Markdown tools in one place instead of visiting different websites for every task. The project now includes multiple Markdown utilities, and I'm continuously adding new tools based on real use cases. If you'd like to try it, I'd love your feedback. 👉 https://mdconverthub.com/markdown-to-html What Markdown tool do you use most often? Feedback and suggestions are always welcome. I'm building MDConvertHub one tool at a time.

Finding a co-founder is one of the hardest parts of building a startup, and most platforms weren't built for it. LinkedIn is a professional directory, not a matching network. Reddit threads are noisy and unstructured. Cold outreach is a gamble. FoundrGeeks is built specifically for this problem . It's an AI-powered co-founder and team matching platform that connects builders based on what they're building, what skills they bring, and what gaps they need to fill, not just their job title or who they already know. The problem with finding a co-founder most builders looking for a co-founder face the same wall: the people they need aren't in their network, and the platforms that exist weren't designed for this specific search. You're not just looking for someone with the right skills. You need someone at the same stage, with the same intensity, who fills exactly the gaps you have right now. And you need to know that before spending three hours on discovery calls. That's the gap FoundrGeeks fills. How FoundrGeeks works When you create a profile, you describe what you're building, what you bring to the table, and what you need. You set your stage, idea, MVP, or funded, and your weekly availability. From there, the AI takes over. It surfaces people whose strengths complement your gaps, scores each match as Strong, Good, or Potential, and generates a plain-English explanation of why each person fits what you're building right now. Three features stand out at launch: Complementary matching: the engine looks for people who fill your gaps, not mirror your background Scored matches with explanations, every match tells you exactly why, before you reach out Stage-aware feeds, as you move from idea to MVP to funded, your matches reshuffle automatically You also control your visibility, go public and let talent find you, or stay private and let the AI work quietly on your behalf. Why we built this This platform exists because of a project that never got finished. I had an idea I wa

As the climate phenomenon sends warm water surging across the eastern Pacific, some parts of the fishing industry are suffering—but other regions are seeing a windfall.

I reviewed HackerRank's open-sourced Hiring Agent - prompts, the scoring logic, and the GitHub enrichment code. I tested the tool with a few faked resumes. Post : https://blog.grandimam.com/posts/how-hacker-rank-scores-engineers/ Takeaways: * Open source is weighted at 35%, technical skills at 10% * A senior engineer with perfect production experience scored 71/100 * Job titles to "Founding Engineer" and "CTO" results in same score * Startup roles emphasis * Active development was 77 days Code: Hiring Agent submitted by /u/grandimam [link] [留言]

AI is not a smarter Google I am convinced most people are using AI in the worst possible way. They treat it like a slightly magical search bar. Type question. Get answer. Copy. Paste. Forget. I think that mindset is holding a lot of people back. Developers. Designers. Knowledge workers. Even my baseball kids who ask ChatGPT for homework help. AI is not a better Q&A machine. It is a delegation machine. You do not "ask" AI. You give it a job. This post is me making that shift concrete. I just shipped six AI gallery pages on my site, built entirely around that idea. Not as a gimmick. As infrastructure for how I work, learn, and build. Why I stopped asking AI questions The turning point was basically frustration. My workflow looked like this for months: Open ChatGPT Ask something like "How do I X in Astro / Svelte / Next" Skim the answer Try the snippet Debug for 30 minutes anyway The answers were fine. Sometimes even useful. But nothing stuck. I would ask the same class of questions over and over. Same concepts. Same patterns. Same gotchas. No real accumulation of knowledge. Just one-off transactions. Then I noticed something: the few times I actually got huge value from AI, I was not asking. I was delegating. "Rebuild this layout using CSS grid, but keep these class names." "Refactor this component, keep the same API, and annotate the performance tradeoffs in comments." "Act like my annoying senior engineer and poke holes in this data model." That felt different. Less like search. More like a teammate who does legwork while I keep steering. Delegation > questions So I made a decision: treat AI like a junior colleague with unlimited patience and questionable taste. That means: I do not ask "How do I do X". I say "You are responsible for X. Here is context. Here are constraints. Here is the definition of done." The shift sounds subtle. It is not. When you ask a question, the model guesses what you want. When you delegate a job, you tell it what you want and where it fit