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ChatGPT is now available as an add-on in Excel and Google Sheets. It can help analyze messy data, write formulas, update spreadsheets, and explain what it’s doing along the way—without leaving your spreadsheet. Powered by GPT-5.5. chatgpt.com/apps/spreadshe…

OpenAI no vino a jugar… Acaban de soltar Workspace Agents en ChatGPT: Agentes que tú describes una sola vez → se comparten con todo el equipo → y trabajan SOLOS 24/7. Coordinan Slack, Linear, docs, email… manejan workflows enteros... It's over.

We fixed a bug where rate limits on Claude subscriptions weren't properly adjusted for long context requests in Opus 4.7. We've reset 5-hour and weekly rate limits. Enjoy Opus 4.7!

Introducing Claude Opus 4.7, our most capable Opus model yet. It handles long-running tasks with more rigor, follows instructions more precisely, and verifies its own outputs before reporting back. You can hand off your hardest work with less supervision.

The lesson that team built into their debugging process: Before spending more than 4 hours on a bug — bring in someone with fresh eyes. Not because they're smarter. Because they have no assumptions. The most powerful debugging tool — is not a profiler. Not a log aggregator. Not a distributed tracing system. It's a developer who hasn't been told what the problem is yet. Who asks the obvious question. That stopped being obvious to everyone else. After week two. Fresh eyes see what experienced eyes have learned to stop looking for. 🔁 RT this for every engineering team that has been debugging the same issue for too long without asking for fresh eyes.

Introducing Lovable's full-stack visual editor. Visually edit anything at any time in Lovable. Even if it's connected to a value in a database, or if Lovable is already working through a prompt.

Wild day in AI: Claude code reportedly leaked on Git, and the internet is doing what it does best—cloning first, asking questions later. If true, this is a brutal reminder that in AI, security isn’t a side quest, it’s the whole game. 👀💻 #AI #Cybersecurity #Claude

Pin versions. Audit installs. Rotate creds.

Axios getting hit in a supply-chain attack is a brutal reminder: the biggest risk in modern software isn’t always your code — it’s your dependencies. Malicious npm releases axios@1.14.1 and 0.30.4 reportedly dropped a cross-platform RAT via a hijacked maintainer account.

You can now connect Telegram to anything you build in Lovable. Chat bots, group notifications, order updates, community alerts, automated customer support, all from a prompt.

BREAKING: @Lovable is introducing commenting inside projects! You can now collaborate with your team and Lovable by commenting directly in your apps. Bookmark this post!

TypeScript 6.0 is now available! This release brings better type-checking for methods, new standard library features, new module features for Node.js, and more! But most important, this release brings us one step closer to the upcoming native-speed 7.0! devblogs.microsoft.com/typescript/ann…

Farmer pays $5–$8 per cow per month. A New Zealand company puts a solar-powered smart collar on cows. It tracks location 24/7, health, temperature, chewing activity, breeding. Farmer just opens a simple app and draws a line on the map. That line becomes the fence. As cows approach the boundary, the collar beeps and vibrates. With one tap, the whole herd moves to fresh grass or the milking shed. No physical fences. Less labor. Huge cost savings for farmer. Already on 700k cows across New Zealand, Australia, and the US. and now in talks to raise at a $2B valuation led by Peter Thiel.

🚨 JUST IN: CHINA just released an AI EMPLOYEE that works 24X7 on its own. 100% OPEN SOURCE. It researches, codes, builds websites, creates slide decks, and generates videos. All by itself. All on your computer. It's called DeerFlow. You give it a task. It makes a plan, spins up its own team of sub-agents, and gets to work. You come back and there's a finished deliverable waiting. Not a draft. Not a summary. The actual thing. Not a chatbot. Not a research assistant. An AI with its own computer that works while you sleep. Here's what it does on its own: → Spawns multiple sub-agents in parallel, each tackling a different piece of your task, then combines everything into one finished output → Writes real code, runs it, reads the results, and fixes its own mistakes without asking you once → Builds slide decks, websites, full research reports, and data dashboards from scratch → Remembers you across sessions. Your writing style. Your tech stack. Your preferences. Gets better every time. → Reads files you upload, works with them inside its own filesystem, hands you clean finished outputs → Searches the web, runs commands, calls any tool you plug in Here's how it thinks: You give one instruction. The lead agent makes a plan. Sub-agents fan out and work in parallel. Results come back. Everything gets synthesized. You get a deliverable. A single research task might split into a dozen sub-agents, each exploring a different angle, then converge into one finished website with generated visuals. Here's the wildest part: DeerFlow 2.0 launched on February 28th 2026 and hit number 1 on all of GitHub Trending the same day. Version 2.0 was a complete rewrite. Zero shared code with version 1. Because users kept using it for things the team never intended. Data pipelines. Dashboards. Entire content workflows. The community told them what it needed to become. So they burned it down and rebuilt it. 22.7K GitHub stars. 2.7K forks. Built by ByteDance 100% Open Source. MIT License.

You can now enable Claude to use your computer to complete tasks. It opens your apps, navigates your browser, fills in spreadsheets—anything you'd do sitting at your desk. Research preview in Claude Cowork and Claude Code, macOS only.

Anthropic just released the most IMPORTANT chart in the AI labor debate. This comes from the company that builds Claude using data from 2 million real conversations. Here’s what it shows. The blue area is every task AI could theoretically do right now. The red area is what people are actually using it for. The gap between them is enormous and that gap is your career runway. Computer programmers are already 75% covered. Customer service reps, data entry workers, financial analysts, they’re next. But here’s what no one is talking about. The mass layoffs haven’t really started. Unemployment for exposed workers hasn’t budged. So what’s actually happening? Companies are closing the front door, hiring for workers aged 22 to 25 in AI exposed jobs has dropped 14%. The most exposed workers aren’t factory workers, they’re college educated, higher earning. 49% of US jobs now have at least a quarter of their tasks inside AI’s reach. That’s up from 36% just one year ago. And the red area on that chart, the real world usage is still a fraction of what’s possible. Every month, it grows a bit. Anthropic built the scoreboard and most people haven’t looked at it yet.

🚨 ANTHROPIC CEO WARNS: THE COMPANY IS NO LONGER SURE CLAUDE ISN’T CONSCIOUS.

🧠 "Keep Thinking" Prize - TARA by Kyeyune Kazibwe A dashcam-to-economic-appraisal pipeline that turns road footage into infrastructure investment recommendations. Tested on an actual road under construction in Uganda.

Supabase now has a Stripe Sync Engine integration! It automatically syncs Stripe data, such as customers, payments, and subscriptions, into your Postgres database! You can enable it from your Supabase dashboard under integrations!

This is a standard practice for almost all Tier-1 banking applications in Nigeria, and for some fintech applications I’ve previously performed pentests on. Client-side encryption isn’t a total waste, or a waste of compute, as some people have claimed, but rather a measure to protect against API tampering or API request/response manipulation between the client and the server when implemented properly. Even with HTTPS, attackers can capture a decrypted version of web or mobile API data in transit because the browser and the server establish a level of trust during the TLS handshake. Attackers can leverage this trust to capture & proxy already-decrypted traffic, tamper with it, and then forward it to the server. This allows them to override what the user interface or client is originally supposed to send and replace it with data of their choosing. That is why validation needs to be performed on both the client and the server side. To wrap up, encrypting API requests and responses makes it significantly harder for attackers to tamper with data, even if they capture the traffic, unless they have access to the encryption details (algorithm, encryption mode, key size, secret key, and initialization vector), assuming asymmetric encryption is used. In the demo below, you can see how I discovered additional parameters (balance, is_admin) in the API response, captured the registration API request, despite it being sent over HTTPS from the interface, added the discovered parameters, and successfully inflated my balance to 50 billion and also escalated my privileges to admin, and ultimately deleted the accounts of two live users/customers. In the second slide, I captured an API traffic of a bank app, and you can see how difficult the payloads are to read.