📝 TL;DR 📝 Aside is a new YC-backed AI browser that signs into your existing accounts and performs real tasks inside them, emails, dashboards, internal tools, rather than just reading public web pages. It runs locally with encryption, lets you bring your own Claude or ChatGPT subscription instead of paying for a separate AI bill, and claims top scores on agentic browsing benchmarks. The capability is genuinely impressive. It also raises real questions about agent permissions that are worth understanding before using it on anything sensitive. 🧠 Overview 🧠 Most AI browser agents today work by reading what is publicly visible on a page or relying on pre-built integrations with specific services. Aside is positioning itself differently: it logs into your actual accounts the same way you would, using saved credentials, and operates inside them directly. That means it does not need a custom integration for every tool you use. If you can log into a website and do something there, Aside is designed to be able to do it too. This is a meaningfully different category of capability than reading and summarizing web content, and it comes with a correspondingly different risk profile. The privacy framing, local processing, encrypted storage, credentials never exposed to the AI model itself, is clearly built to address the obvious concern that comes with granting an AI agent that level of account access. 📜 The Announcement 📜 Aside is a desktop browser, currently available for macOS, built by a Y Combinator-backed startup. The pitch is that it works across logged-in websites and accounts directly rather than depending on integrations, handling tasks like managing communications, replying to messages, working with documents and spreadsheets on your computer, and operating inside dashboards and internal tools. On benchmarks, Aside reports ranking first across three agentic browsing evaluations: Online-Mind2Web, BU-Bench-V1, and Odyssey. The company's own published numbers show Aside scoring 99.0% on these combined evaluations, ahead of Browser Use at 97.7%, GPT-5.4 at 92.8%, Claude Opus 4.8 at 84.0%, and ChatGPT Atlas at 70.0%. These figures come directly from Aside's own marketing materials and have not yet been independently verified by a third party, which is worth keeping in mind before treating them as settled fact.

Hello guys,am new here and I'd love to know how to start or where to start from in developing an app from scratch ,I don't know much about AI , hoping someone to guide me through

One of the biggest mistakes entrepreneurs make is confusing movement with progress. Answering emails, scrolling social media, organizing files, and jumping between tasks can make us feel productive while the work that actually grows the business gets pushed aside. Before you begin your day, ask yourself one question: What is the one activity that could move my business forward today? It might be making sales calls, following up with leads, creating content, improving your product, networking, or serving your existing customers. Identify that task and complete it before distractions take over. Successful businesses are often built through consistency, not complexity. Small actions completed every day create momentum that compounds over time. Today's challenge: • Take one action you've been avoiding. Remember, focus is not about doing more things. It is about doing more of the things that matter most. Keep building. Keep learning. Keep showing up. Your future business is being created by the decisions you make today.

There's a version of AI adoption where the tools make everything faster, the client work ships on time, and the business runs more smoothly. That version is real and it's what most of us are working toward. There's another version, less discussed, where the speed is real but the quality control didn't keep up with it, and the work that's now shipping faster is also occasionally wrong in ways that only become visible in contexts where the cost of being wrong is high. The difference between these two versions is almost entirely about what happened between generation and delivery. Not how good the AI tools were. Not how sophisticated the prompts were. What happened in the gap: the review, the verification, the check that the output actually does what the brief asked for and that the claims in it are accurate. In client-facing professional work, that gap is where professional reputation gets built or eroded. Speed that skips the gap is a liability disguised as an efficiency. ------------- Context ------------- AI errors in low-stakes contexts are recoverable. A poorly generated internal document gets caught and corrected. A draft that misses the brief gets reworked before anyone outside the team sees it. The cost is revision time, which is real but bounded. AI errors in client-facing contexts have a different cost profile. A proposal that contains inaccurate market data, a client report that misattributes findings, a legal document that includes provisions that don't apply to the specific situation, a strategic recommendation that misrepresents a competitor's position: these errors arrive in contexts where the professional's credibility is being directly evaluated. The damage they do to trust isn't proportional to the size of the error. It's proportional to the context in which it appeared. The specific risk AI introduces here is confident incorrectness. AI-generated content that contains an error doesn't come with a flag on the error. It arrives with the same confident, polished tone as the content that's accurate. The surface signal of quality is the same whether the underlying content is correct or not. This is different from the human-generated error, where the hesitation or rough phrasing often signals to the reader that verification is worth doing.

There's a counterintuitive pattern starting to emerge in the communities and conversations we follow closely. It doesn't fit the dominant narrative about AI and professional development, so it tends to get dismissed. But it's consistent enough and specific enough that it's worth looking at directly. The pattern: a growing number of professionals who use AI heavily are reporting, often with some embarrassment, that their ability to think through problems independently, to recall information from memory, to write fluently without AI assistance, feels like it has degraded. Not dramatically. But noticeably. The capability was there before. It's less reliably there now. This is the cognitive atrophy problem. It's real, it's specific, and it's something that smart AI adoption can work against. ------------- Context ------------- Cognitive capabilities are use-it-or-lose-it in a way that's well established in the research. Memory, reasoning, writing fluency, the ability to hold a complex problem in your head and work it through: these capabilities are maintained and developed through exercise and they degrade through disuse. For most of professional history, the nature of knowledge work required these capabilities regularly. Writing required sustained original composition. Research required holding a developing understanding in working memory as new information was integrated. Problem-solving required independent reasoning before any external validation was sought. The work itself was the exercise. AI tools are changing the exercise load. When AI drafts the writing, the composition muscle doesn't engage. When AI does the initial research synthesis, the information integration work doesn't happen. When AI suggests the analysis framework, the independent problem framing doesn't get practiced. Each of these is individually a small reduction in cognitive exercise. Across a day of heavily AI-assisted work, the aggregate reduction is significant. The capability doesn't disappear immediately. It degrades gradually, in a way that's invisible until a situation arises that requires it without AI assistance: a meeting where you need to think on your feet, a client situation where you need to produce analysis quickly without time to brief an AI, a creative challenge where your own perspective needs to show up rather than an AI-assisted version of it. These situations surface the gap.