Hello I'm a noob here I've been looking and listening from a distance. I've always been a very private person so I am very concerned with sharing my life story into AI however I am very intrigued and at the point where I really need to use AI, as I have a lot of complex movement parts of my life that I feel like I can dump into an AI and get all these things handled. I read Igor's article on using an AI to work through your life situation at the moment. How much, How deep of my personal self should I or should I not say into AI whether it's chat GPT, Gemini, Claude or Manus? Also I want to create coursework from all of my struggles and strife to help others , so I keep that in mind as well, saying or not saying ideas out there. Or is that all just nothing to worry about these days? Thank you in advance for your support and guidance in this!

Maybe its a nobrainer, but along my review work I have found that many project-leaders have edited or uploaded their AI configuration files (for Kimi.com it is VISION.md, SPEC.md, TECH.md, BOUNDARIES.md, PATTERNS.md and DECISIONS.md) directly into the AI (where those files often got lost, when switching platform, the platform was ditched (for cost reasons) or when the project was left). The better approach is to compile those files into the GitHub Repo (or the local folder) you will need anyway to store the vibecoded code. Then, in your firsts prompt tell your AI from where to pick them up. Sideeffect: you are assured that your Repo is accessible.

📝 TL;DR 📝 Anthropic confirmed that Claude Sonnet 5's introductory pricing, $2 per million input tokens and $10 per million output tokens, is now permanent. The scheduled increase to $3/$15 that was set to take effect September 1 has been cancelled entirely. This isn't a discount from where things stand today, it's Anthropic committing to not raise the price. For anyone running agent workflows on Sonnet 5, that predictability matters more than the number itself, though reaction has been genuinely split over whether $2/$10 is actually competitive against faster-moving rivals. 🧠 Overview 🧠 When Sonnet 5 launched on June 30, Anthropic was explicit that $2/$10 was introductory pricing, a promotional rate through August 31, after which it would rise to the standard $3/$15. That kind of temporary discount-then-increase structure is common enough that most people building on Sonnet 5 likely priced future costs around the higher number. Anthropic just canceled that increase entirely, confirming via its official account: "We're making Claude Sonnet 5's introductory pricing permanent. We launched Sonnet 5 in June at $2 per million input tokens and $10 per million output tokens through August 31, and that price will remain unchanged." The real story here isn't a price cut, Sonnet 5 costs exactly the same today as it did yesterday. It's the removal of a known, dated cost increase that anyone running production workloads on the model would otherwise have had to budget around. 📜 The Announcement 📜 Anthropic's own pricing documentation now states plainly: "The previously scheduled increase to $3/$15 per million input/output tokens on September 1, 2026 will not occur." Sonnet 5 remains the mid-tier model in Anthropic's lineup, positioned below Opus 5 ($5/$25) and Fable 5 ($10/$50 after usage credits), while offering what Anthropic describes as agentic capability that previously required those larger, pricier models. Prompt caching still delivers up to 90% cost savings on repeated context, and batch processing still offers a 50% discount, both stacking on top of the now-permanent base rate.

AI has made it remarkably cheap to run quick tests, comparisons, and experiments: try this version against that one, test three different approaches before committing to any of them, generate multiple options and compare their performance. This capability is genuinely valuable for improving decision quality. It's also introduced a specific and less discussed risk: for some people, the ease of testing has quietly become a way to avoid actually deciding, rather than a way to decide better and faster. ------------- Context ------------- Before AI made experimentation this cheap, running a genuine test of multiple approaches required real time and resource investment, which meant testing was naturally reserved for decisions significant enough to justify that cost. Most decisions, particularly the smaller, more routine ones, were simply made using judgment and experience, without an extended testing phase, because the cost of testing exceeded the value of the additional certainty it would provide. AI has removed much of that natural cost barrier. Testing multiple approaches to a piece of content, a marketing message, a product description, has become nearly free in terms of direct effort, even though it still costs real time in terms of running the comparisons and evaluating the results. This has genuinely improved decision quality for a lot of applications. But for some people, the removal of the natural cost barrier that used to limit testing has produced a specific unintended effect: because testing is now easy, there's less pressure to actually commit to a decision, and testing can continue indefinitely as a way of deferring the discomfort of choosing, rather than genuinely converging toward better information and a faster final decision. ------------- Where Testing Becomes a Substitute for Deciding ------------- A small e-commerce business owner described this pattern in her own experience with product description testing. AI made it easy to generate and test multiple versions of any given product description, comparing performance metrics against each other. What started as a genuinely useful practice, testing a handful of variations before settling on the best one, gradually expanded into something less productive: she found herself continuing to generate and test new variations for products that already had a perfectly good, reasonably performing description in place, essentially because testing had become easy enough that stopping felt like leaving potential improvement on the table, even when the marginal value of additional testing had become genuinely small.

Hi guys, its been a while sine I have been in here but I remember that we were offered an App builder and a free month when we first joined? I cant remember the company but I feel like it might have been Base44? Does anyone have any details on this? I cant seem to find the information anywhere?