People.ai

People.ai AI

People.ai AI

People.ai AI

People.ai AI

People.ai AI

People.ai AI

People.ai AI

People.ai AI

People.ai AI

People.ai AI

AI Browser Game Jam 3 Submissions Closed - 85 entries!

The 3rd AI Browser Game Jam just wrapped submissions, and it went really well: 119 people joined and 85 browser games were submitted. The jam is focused on experimenting with AI-assisted game development. Any tools were allowed for code, art, music, design, sound, etc. The goal was to make something playable, share the process, and see what people could build. Judging/ratings are open now, so feel free to check out the entries and play some games! submitted by /u/Slackluster [link] [comments]

Moving people in AI first organization

One challenge I am finding in the organisations regarding how to move the work force towards AI adoption and to a point where people and AI part of the process kind of synchronous. Can someone help me with defining some sub-divisions in 'people' so that those can become the focus area submitted by /u/Distinct-Log-7239 [link] [comments]

OpenAI is building the AI fullstack, likely to match Google. And American made will receive lots of support. Great long term strategy

submitted by /u/py-net [link] [comments]

I Think People Are Completely Wrong About AI And Web Design

A client paid my $4,700 invoice yesterday for a website that took me around 2 hours to build. The web development space is moving insanely fast right now, especially with AI. Everywhere I look people are saying web design is saturated, AI is replacing developers, nobody wants websites anymore, and it's impossible to get clients. I honestly disagree. The client was a 62 year old entrepreneur who owns several cabins in the mountains that he rents out to people who want to spend weekends skiing during winter or enjoying nature during summer. His previous website was old, slow, and honestly looked like it hadn't been updated in years. Finding him was actually pretty simple. I use a tool called Swokei where I upload lists of businesses that already have websites. It analyzes their websites and finds issues related to design, layout, SEO, mobile optimization, and other areas that could be improved. Those findings are then turned into personalized outreach emails. And when I say personalized, I don't mean those generic reports that say "Your SEO score is 42." I mean actual emails explaining what could be improved and why it matters. The funny thing is that every business owner thinks I manually looked through their website and wrote the email myself. In reality, the whole process is automated. This particular business owner replied and was interested in seeing an updated version of his website. His website wasn't anything crazy. It had information about the cabins, booking information, contact details, and a few pages about the area. During our conversation he sent me a website that he liked and wanted to use as inspiration. I took his logo, brand colors, content, and the reference website and gave everything to Claude. My instructions were simple: take inspiration from the reference site, keep his branding, improve the user experience, modernize the design, and make the website significantly better than what he currently has. I genuinely couldn't believe how good the result was. About 2 hours later I had a website that looked dramatically better than his previous one. Not only that, it looked better than the reference website he originally sent me. The website was faster, cleaner, more modern, much easier to navigate, and the technical SEO score was over 90. When I showed it to him, he loved it. A few conversations later he paid the invoice. $4,700 upfront and $149 per month for hosting, maintenance, and future changes whenever he needs them. The biggest thing I've learned over the last year is that building websites is no longer the hard part. Finding clients is. AI has made building websites faster than ever. What most people struggle with today is getting conversations started with business owners in the first place. There are still plenty of opportunities in this industry. I personally wouldn't call an industry dead when I just got paid nearly $5,000 for a website that took me around 2 hours to build. submitted by /u/Murky_Explanation_73 [link] [comments]

I tried making an AI World Cup commentator. It sounds real until the game gets fast

I wanted to see if an AI commentator could work inside an actual live stream, not just as a voiceover added to a clip afterwards. So I wired up a rough version: RTMP in, live stream playback in the browser, and an AI commentator watching the feed and talking over it in real time. The video attached is a recording of that live flow. Honestly, it works better than I expected. It sounds like commentary, but sometimes it’s reacting to a moment instead of understanding the play. I’m posting this because I’m curious how far off it feels to other people. If people are interested, I might clean up the code and open source it submitted by /u/ming_calligraphy [link] [comments]

I Got Fed up with ChatGPT’s New Flatter Dark Mode, so I Restored the Original Charcoal Version

The newer ChatGPT dark mode felt a little too flat/light to me, so I put together a small userscript that restores a deeper charcoal-style palette. It mainly fixes: darker main canvas darker composer/input bar better sidebar separation readable lifted message bubbles bottom dock/footer strip cleanup light mode stays unaffected I also tried to avoid the usual “dark theme hack” problem where broad CSS overrides turn everything into blocky rectangles. The script mostly uses ChatGPT’s own theme variables, then does a targeted composer/bottom-dock cleanup. Install: Greasy Fork Source / screenshots / notes: GitHub Privacy note: it does not collect data, make network requests, store conversations, use analytics, or modify ChatGPT functionality. It only applies local visual styling on chatgpt.com and chat.openai.com. Not affiliated with OpenAI — just a visual fix for people who preferred the old darker feel. submitted by /u/TonyHMeow [link] [comments]

OpenAI's Chief Strategy Officer is on the registration list for Peter Thiel's secret $16K retreat alongside the Treasury Secretary and the co-founder of Palantir

WIRED verified the leaked membership of Dialog, a private society that operated for 20 years with no public website. 222 people registered for their August 2026 retreat near Dublin. The list includes OpenAI's CSO, Google DeepMind's head of AI global affairs, the CEO of YouTube, and sitting government officials who all used personal email to avoid FOIA. I mapped the full membership at build-a-cult.com with sourced profiles and documented conflicts of interest between regulators and the industries they're supposed to oversee. submitted by /u/TreesOfPortland [link] [comments]

I made a small MCP server for OpenAI’s Ads API

This is pretty niche, but I was playing with the OpenAI Ads / Advertiser API and wanted a cleaner way to use it from Claude or Cursor, so I made an MCP server for it. https://github.com/trakkr-aisearch/openai-ads-mcp It can read account/campaign data, create campaign structures, manage audiences, pull insights, and log conversions. The obvious scary bit is write access. I didn’t want a model casually pushing live ad changes, so anything new starts paused, larger budget changes need confirmation, and there’s a read-only mode for reporting. It runs with npx or uvx. Still early, but usable enough that I figured other people poking at the API might find it helpful. If you’ve used the Ads API already, I’d be curious what parts feel underbaked. submitted by /u/gpt-three [link] [comments]

What are the best places to learn human-in-the-loop skills for the AI era?

I’m trying to understand what skills people think will matter most as AI agents become part of everyday work. Not just prompt engineering, but things like evaluating AI outputs, supervising agents, designing workflows, knowing when to trust or override a model, and coordinating humans + AI systems. Where would you recommend learning these skills? Courses, books, communities, projects, papers, YouTube channels, anything useful. Curious what people here would suggest for someone trying to prepare for the next few years of AI-driven work. submitted by /u/willXare [link] [comments]

The Alternative

Many people seem almost eager for companies like OpenAI to fail, often pointing to their financial losses as proof that the business model is unsustainable. But very few of those critics offer a realistic alternative for the billions of people who now rely on AI. ​ If OpenAI disappeared tomorrow, what exactly is the replacement for the average person? Not for a few thousand AI enthusiasts with technical expertise and expensive hardware, but for students, workers, and ordinary people around the world. ​ Anthropic has already signaled a very different approach: if you want meaningful access to its best models, you are generally expected to pay. That is a perfectly valid business decision, but it means many people are effectively excluded. If you cannot afford $20 per month, what is your alternative? Going back to traditional search engines, where you have to sift through pages of results, advertisements disguised as content, SEO spam, and AI-generated summaries that are often less useful than a dedicated AI assistant? ​ Others point to open-source models, often developed by Chinese companies or research groups. But for most people, that is not a practical solution either. The vast majority of users do not know how to download, configure, and run local AI models. Even if they do, running them meaningfully often requires expensive hardware—typically a capable NVIDIA GPU or a modern Apple computer. For someone earning a few hundred dollars per month, spending around $1,000 or more on hardware is simply not realistic. ​ OpenAI reportedly serves close to a billion people every week. The overwhelming majority of those users are on free plans. Many are students. Many live in developing countries. Many have little or no disposable income. They cannot afford a $20 monthly subscription, and they certainly cannot afford high-end AI hardware. ​ These are the people OpenAI is currently serving while losing billions of dollars. I am not naive enough to believe that this is pure altruism. OpenAI is a business and will eventually need a sustainable path to profitability. But the fact remains that, today, they are providing advanced AI access to hundreds of millions of people who would otherwise have none. ​ OpenAI could choose a different path. It could restrict access, dramatically reduce free usage, or move toward a model where only paying customers receive meaningful service. That would likely improve its finances much faster. Yet for now, it continues to support a massive free user base. ​ If that support disappears, what is the realistic outcome? Most people will not suddenly become local AI experts. They will not buy expensive GPUs. They will not self-host open-source models. They will simply return to the most accessible option available: Google. ​ And that would mean even more dependence on a single dominant gatekeeper of information. For all the criticism directed at OpenAI's finances, the practical alternative for most people is not a vibrant open-source future. It is a return to Google's monopoly over how billions of people access information online. submitted by /u/sulabh1992 [link] [comments]

The productivity gap between "AI user" and "AI agent user" is bigger than I expected

Most people use AI reactively open tab, type question, get answer, close tab. That saves maybe 20% of your time. Autonomous agents are different. You define a goal. The AI executes it browsing, connecting tools, chaining tasks without you managing each step. I've been using OpenClaw for this. Email management went from 40 min/day to 8 min/day. Research workflows run in the background while I write. The catch: vague instructions produce vague results. Specificity is the skill that makes agents actually useful. What's the highest-leverage AI workflow running in your business right now? submitted by /u/avinash_gove [link] [comments]

How To Get Web Design Clients

Running a web agency is honestly a lot harder than most people think. I've talked to a lot of web designers and agency owners over the years, and everyone seems to have a completely different way of getting clients. Some swear by paid ads, others rely on referrals, SEO, cold calling, LinkedIn outreach, email marketing, and so on. What surprises me is that I rarely hear anyone talking about the strategy that has worked best for me. The biggest challenge with running a web agency as a solo founder is that you're wearing every hat. You're building websites, maintaining websites, handling support requests, fixing bugs, making client changes, managing hosting, answering messages, and dealing with everything else that comes with running a business. The question is, when are you supposed to do outreach? That's why I prefer email outreach. The reason is simple. It works for me in the background while I'm doing everything else. I don't have to spend hours every day cold calling businesses or manually searching for leads. The system keeps working while I focus on servicing existing clients. But I don't do email outreach in the traditional way. Most people are blasting generic emails through tools like Instantly or Klaviyo. The problem is that business owners get those emails every day and can spot them immediately. What I do instead is use a tool called Swokei. I simply upload a batch of business websites, and the tool analyzes each one individually. It looks at things like design issues, SEO problems, mobile optimization, layout weaknesses, and other things that could be hurting conversions. It then generates a personalized outreach message based on the specific problems it finds on that business's website. The result is that I can run highly personalized outreach campaigns without spending hours manually reviewing websites and writing custom emails one by one. Another thing I like is that before running the analysis, you can choose the offer you want to lead with. You can start conversations, try to book meetings, or offer a free draft. I always choose the free draft option. When a business owner replies and says they're interested in seeing what their website could look like, I never build the site and send it over email. Instead, I reply with something like: "Sounds great. When are you free for a quick 10 to 15 minute Google Meet so I can show you what I have in mind?" Then I book the call. Before the meeting, I use AI tools to create a redesigned version of their website. It usually takes a very short amount of time. Most of the businesses I'm reaching out to have outdated websites, so even a solid AI assisted redesign looks significantly better than what they're currently using. Then I present it live during the meeting. This is where the real selling happens. They're seeing a better version of their business online, customized specifically for them, and you're there to answer questions and handle objections in real time. If they're interested, I close them on the call with a one time website fee plus a monthly hosting, maintenance, and support package. For hosting, I mainly use Hetzner and Cloudflare. They're reliable, affordable, and make it easy to scale when you start getting more clients. One thing I've learned is that you should never send the redesign over email. The meeting is where you have the highest chance of closing the deal because you can walk them through the improvements, explain the reasoning behind the changes, and answer any concerns on the spot. So my stack is pretty simple. Hetzner and Cloudflare for hosting. Swokei for website analysis and personalized outreach. Claude for building website drafts and speeding up development. That's basically it. No paid ads. No cold calling. No spending hours writing personalized emails manually. Just finding businesses with weak websites, showing them a better version, and having a conversation. submitted by /u/Murky_Explanation_73 [link] [comments]

Anthropic Said This AI Was Too Powerful for Public Release. Now Anyone Can Use It.

A few months ago, Anthropic did something unusual. While most AI companies were racing to release bigger and more capable models, Anthropic was doing the opposite. It introduced a new model family called Mythos and then immediately restricted access. The reason? The company believed the model’s capabilities were powerful enough to create real security concerns. That decision sparked a lot of discussion in the AI world. Some people praised the caution. Others argued that Anthropic was exaggerating the risks. Either way, Mythos quickly became one of the most talked about AI projects of 2026. Now Anthropic has changed course. The company has officially released Claude Fable 5, a Mythos-class model that it says exceeds the capabilities of any model it has previously made generally available. And honestly, I think most people are focusing on the wrong part of the announcement. The biggest story is not that Claude got smarter. The biggest story is that Anthropic now believes a Mythos-level model can be safely placed in the hands of the public. That is a much bigger signal about where AI is heading. What Is Claude Fable 5? According to Anthropic, Claude Fable 5 is the first generally available model from its Mythos family. The company describes it as a Mythos-level system designed for ambitious long-running projects, autonomous work, software engineering, research, and complex problem solving. The model sits above the existing Opus family and is positioned as Anthropic’s most capable publicly accessible AI system. That alone would have been major news. But the backstory makes it far more interesting. Why Mythos Was Restricted in the First Place Back in April, Anthropic introduced Mythos Preview under a program called Project Glasswing. Unlike normal Claude releases, Mythos wasn’t available to everyone. Access was limited to a small number of organizations and security researchers. The reason was simple. Anthropic’s internal testing suggested Mythos had unusually strong capabilities in areas like: software engineering vulnerability discovery advanced reasoning cybersecurity research During testing, Mythos reportedly identified vulnerabilities across major operating systems and software environments. That immediately raised concerns. If a model becomes exceptionally good at finding security weaknesses, the same capability that helps defenders can also help attackers. That created a difficult question: How do you release a model this powerful without creating new risks? Anthropic’s Solution: Fable 5 Instead of releasing Mythos directly, Anthropic created Claude Fable 5. Fable 5 uses the same underlying model architecture as Mythos 5 but introduces additional safeguards designed for public use. When users enter certain high-risk domains, the system can: refuse the request limit responses redirect the task to Claude Opus 4.8 This happens particularly around areas such as: advanced cybersecurity biological research chemistry model distillation according to Anthropic’s public documentation and reporting from multiple outlets. Essentially, Anthropic is attempting to make Mythos-level capabilities available while restricting the areas it considers most sensitive. It’s one of the largest real-world experiments in frontier AI safety we’ve seen so far. Why Developers Are Paying Attention The reason developers are excited isn’t because of the safety story. It’s because of what Fable 5 can apparently do. Anthropic claims the model is state of the art across most internal benchmark categories and particularly strong in: coding long horizon reasoning autonomous work knowledge tasks vision workflows The company specifically highlights its ability to handle projects that unfold over hours or even days rather than minutes. That’s important because most AI systems still struggle with very long projects. They can solve individual tasks. Managing dozens of connected tasks over an extended period is much harder. Anthropic believes Fable 5 moves that frontier forward significantly. The Controversy Started Almost Immediately Not everyone is happy with the rollout. Within days of release, developers started criticizing some of Anthropic’s restrictions. Reports emerged that the model was refusing even basic biology-related questions because of aggressive safety filters. Others criticized Anthropic for initially rerouting certain requests without clearly informing users. After backlash, the company adjusted its approach and began providing clearer explanations when requests are redirected to older models. There are also enterprise concerns. Microsoft reportedly restricted employee access to Claude Fable 5 while legal teams evaluate data retention policies associated with the model. None of these issues are unusual for a frontier model release. But they show how difficult it is becoming to balance capability and safety at the highest levels of AI developme

8 things about using Claude for writing that took me embarrassingly long to learn

Most writing tips for this thing are surface level. Here's the stuff I actually use daily after about a year, mostly non-code work. It rewrites better than it writes. Give it your ugly draft and say "tighten this", dont ask it to start from nothing. The blank page is where it goes generic. "Make it sound less AI" does nothing. "Cut any sentence that sounds like writing, use shorter words, leave one rough edge" does a lot. Tell it who's reading, not who it is. "Explain this to a skeptical CFO" beats "you are an expert." The audience does the work. It agrees with you if you let it. I stopped asking "is this good" and started asking "what's the strongest case this is wrong." Night and day. Give it a reason to be short, not a word count. "this goes in a text" gets brevity that "under 50 words" never does. Paste the doc, dont describe it. It reads files. I wasted months pasting walls of text when uploading worked better. Ask for the version it avoided. "what's the riskier take you didnt write" surfaces the better answer maybe a third of the time. The first reply is the start, not the answer. The good stuff is turn 2 or 3 after you push back. People who judge it on one paste are reviewing a first draft. none of these are clever, they just took too long to become automatic. what crossed over from "trick I read" to "thing I do without thinking" for you? drop yours below submitted by /u/Several_Function_129 [link] [comments]

how i use Claude for B2B partnership outreach without my emails sounding like AI wrote them

partnerships lead at a series A SaaS. ~1 cold partner outreach per week, ~3 follow-ups per week. three months ago every email i wrote with claude got 0 replies. switched my workflow. now im running ~16% reply rate which is healthy for cold partner outreach. the change: i stopped asking claude to "write a cold email" and started asking it to "edit my draft." specifically: i write the first draft myself. 4 sentences, ugly, fast. paste it in claude. ask: "what's the one thing this email is doing that makes it sound like a cold email." claude usually flags ONE thing. always something different. opener too generic, ask too soft, name-drop felt forced, calendar link too early. i fix that one thing myself. send. the framing matters: "what makes this sound like a cold email" anchors claude to identify the AI/template tells. asking it to "write a cold email" produces exactly the AI/template prose i'm trying to avoid. also: never ever ever let claude rewrite the whole email. the rewrite ALWAYS sounds like claude even when the diagnosis was good. other people doing outbound: what's your "anti-AI" workflow when using AI? submitted by /u/TrueParty3054 [link] [comments]