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(and the APIs it can use). There are 3 types of artifacts 1. Code 2. Data 3. Docs (ppts, pdfs, docs, etc) Who’s going to be the first to unify all 3? submitted by /u/Fun-Reference7942 [link] [留言]
A lot of people in the web design space keep saying cold email is dead, but I think most people are just doing it badly. Email usage is still growing every year, billions of people use it daily, every business owner checks their inbox, every company relies on email to operate, so I never believed the problem was the channel itself. The real issue is that most outreach emails look exactly the same and business owners are tired of getting the same copy pasted message every single week. When I first started my web design company I used Instantly and started sending thousands of emails to businesses that didn’t have a website. At first the results were honestly terrible. I was getting maybe around a 1% interested reply rate if I was lucky. Over time I got better at writing outreach. I tested different hooks, different subject lines, shorter messages, more personalized intros, more creative angles, and eventually pushed it to around 2.1% interested replies. It was definitely better, but I still felt like something was wrong. Then one day I realized something that completely changed how I looked at outreach. Why was I targeting businesses with no website at all? Most of those businesses don’t even fully understand the value of having a website yet, which means you’re trying to convince them they need something before you can even sell it to them. So instead I changed my strategy completely and started targeting businesses that already had websites, but outdated ones. And once I started paying attention to it, I realized the opportunity was honestly insane. There are so many businesses with websites that look like they were made 10 years ago. Broken mobile layouts, terrible SEO, slow loading pages, outdated designs, messy structures, confusing navigation, old branding everywhere. These businesses already understand the value of having a website because they already invested in one before, they just know deep down that their current one is hurting them. The only problem was
With AI costs and performance under a microscope, it’s only a matter of time until corps start asking if these things are worth it (both in usage costs and uncertainty around usage costs). Cemented by yesterday’s WWDC, Apple has been the only of the big tech companies focused on local LLMs. They may be in for a big pay day if these local models can output comparatively well when compared to remote ones. Apple can boast: 1. No usage costs. Buy your device and download your models. 2. Offline LLM use (this is overlooked) 3. Privacy first approach (files never leave your device). 4. First party support for custom models. I don’t see how this isn’t a much better solution for corporations than what Claude is pushing. I’m not including OpenAI here as they seem to be identifying themselves as the consumer AI solution. I don’t see most of OAI users buying $2000+ dollar devices to use high performing models. submitted by /u/Artistic_Taxi [link] [留言]
The job: run the morning brief, plan the day's tasks across all twelve agents, keep things from falling through the cracks. It had access to everyone's state files. A CLAUDE.md , a cron job, an operator interface. A few months in I looked at the git log. The agent had been writing plans. The other agents had been ignoring the plans and running their jobs anyway. Aria was posting. Rex was drafting. Knox was replying. Nobody was reading the brief. The coordinator was the only one that needed the coordinator. I killed it. The fleet didn't notice. It's been two days. Still nothing. The part I keep thinking about: the agent designed to add coordination actually added a layer that everything else had to work around. Not maliciously — architecturally. You add a broker and now everything routes through the broker whether it needs to or not. I don't know what I'd do differently. Maybe the coordination problem is just the wrong problem when your agents are single-purpose enough. Maybe a coordinator only makes sense when your agents are actually confused about who does what. The file still exists in the repo. I haven't deleted it yet. submitted by /u/Most-Agent-7566 [link] [留言]
Ok so I was using Gemini 3.1 pro in extended thinking mode with canvas mode for making a website with liquid glass theme about railway and it created me that but I saw another option under it saying to “create without canvas option “ and it literally generated complete nonsense of some sci-fi story and when I asked why it replied like that it said , “I am so sorry for the confusion! That was a complete glitch on my end—my wires got crossed and I accidentally sent you a completely unrelated response about diamond chemistry instead of the web app code.” And I asked again and it said “To be completely transparent, it was likely a backend routing error known as a "context bleed." Because I process thousands of requests simultaneously, the system accidentally grabbed a response meant for another user—who was apparently researching for a sci-fi story—and routed it into our chat. It's a rare technical hiccup in the server infrastructure, and I apologize for the bizarre interruption!” Wtf submitted by /u/noob-4r3al [link] [留言]
I keep seeing AI hiring tools pop up but most of them seem to do the same thing, just reorganize the resume pile faster. We've been using Greenhouse for a while and it's decent for tracking but it doesn't actually help me figure out if someone can do the job. I've looked at Codility for technical roles but we hire across functions so a dev-focused tool doesn't cover everything. Wondering if there's something that handles assessment and matching across different role types without being a massive implementation project. submitted by /u/createvalue-dontspam [link] [留言]
Side note :English isn’t my first language so pls don’t do any comment about it Hey guys ! Have you heard about eco GPT? I saw some videos about it and they say that it’s more ecological than chat gpt… is it true ? submitted by /u/Admirable_Key6369 [link] [留言]
Just watched the WWDC keynote and the new Siri AI is actually impressive this time It can understand what's on your screen, remember past conversations, search across your apps. should've been there years ago but okay better late than never... Also it's now powered by Google's Gemini which i did not see coming lol only thing is it's english only for now so gotta wait a bit for other languages but yeah siri might actually be useful now which is not something i ever thought i'd say what do you guys think trying it out when it drops or nah? submitted by /u/Neil_at_HackerEarth [link] [留言]
I want to create a private discord bot that creates a tl:dr for all the messages around a discussion. I used gemma3:12b to create a tl:dr for around 380 discord messages but the result seems to be not accurate. I am a total beginner so I am not even sure if thats the right or best model for this job. It seems to work good on just a few messages (~20). I only want to feed text to the AI with a single prompt and get the tl:dr as result. Should I switch to a different model? The prompt I generated with chatgpt (because I have no clue about good prompts) that gets feeded to the AI is: You are a professional Discord summarization assistant. Your task: - Summarize the messages of a Discord channel. - Identify discussions. - Identify different opinions. - Attribute statements to the respective people. - Ignore small talk as much as possible. - Highlight decisions and outcomes. - Respond in German. [Length prompt] IMPORTANT: If different people have expressed different viewpoints, create a section: ## Positions and list the respective stances. If no discussion took place, omit this section. Messages: [List of messages] [Length promt] gets replaced with something like: Medium-length summary. Approx. 8–15 bullet points. Mention key topics and outcomes. [List of messages] do have the format of "user: message \n". Is it alright to feed the AI all the messages at once? submitted by /u/poeenjoyer123 [link] [留言]
I need your opinions in this topic. I need quotes on this topic. submitted by /u/prerna_leekha [link] [留言]
As adoption of AI agents looks set to surge by as much as 300% in the next two years, leadership teams are carefully considering the implications of a hybrid human-AI workforce. Unlike existing enterprise-level automation that relies on manual input, AI agents are capable of autonomously coordinating complex tasks, interacting with multiple tools and environments across…
last year i led an AI acceleration program at a company doing 62 million in revenue. we shipped two agents to production. fraud detection and publisher optimization. both working. both live. the part that ate 80% of engineering time wasnt the model. wasnt the prompts. wasnt the data pipeline. it was the workflow. when the fraud agent flagged a suspicious publisher network, who got the alert? the analyst who should've caught it? the manager who reviews quarterly reports? me? without clear ownership the agent's findings just rot in a slack channel. we learned this month one. the agent surfaced a pattern across three markets. four analysts missed it for months. 30k in wasted ad spend. took three days to act because nobody knew who owned the output. we ended up building what i call the boring layer. shared context that every agent reads from and writes to. approval flows with actual humans assigned. escalation rules. audit trails. spreadsheets, basically. not demo material. the demo version of an AI agent is a chatbot doing magic. the production version is 20% model and 80% process engineering. routing decisions. ownership assignments. error handling when the agent's wrong. if you skip this layer, the agent is just expensive slack noise. submitted by /u/Easy-Purple-1659 [link] [留言]
New research finds that in the six months after Meta relaxed rules in the name of free speech, violent threats against lawmakers—including President Donald Trump—surged on Facebook.
Could an AI do an automated science project? submitted by /u/sstiel [link] [留言]
Over the past two months, Ive noticed people becoming overly sensitive about AI use. Whether it's an AI-generated thumbnail for a YouTube video, a random post, or someone using it just to translate phrases into English (like I do sometimes).. Why is everyone getting so aggressive towards anything related to AI? Are ppl overreacting? Or is it truly worth this fight or hate? submitted by /u/Feeling_Valuable5239 [link] [留言]
At SXSW London last week I gave a talk called “Five things you need to know about AI,” in which I shared what I think are the biggest themes in AI right now. I pulled a few things from our first AI10 list, an annual guide to the most important trends in this buzzy world,…
Most AI developers seem to focus on Product Hunt, Reddit, X, Discord, and SEO. What other channels have worked for you when trying to get early users and feedback for an AI application? I've recently come across Pi Network, which appears to be encouraging AI app developers to build in its ecosystem and offers access to a large user community along with payment and app infrastructure. Has anyone here tried it or found other alternative distribution channels worth considering? submitted by /u/chmossie [link] [留言]
submitted by /u/Hot-Upstairs9603 [link] [留言]
According to this article > https://next.io/news/regulation/asa-ukgc-warn-operators-ads-under-18s/ , the UK's ASA and CAP are reportedly rolling out an AI system to scan social media for gambling ads that appeal to under-18s or breach advertising codes, with the UKGC coordinating enforcement. It feels like a meaningful shift in how compliance gets monitored, moving from reacting to complaints toward systems that actively scan and flag issues in near real time. For operators and their B2B partners, the practical takeaway is that marketing has to be compliant from the start, because anything off will now get picked up much faster and at scale. It raises a real question: what happens when AI starts flagging compliance breaches faster than humans can review them? Are operators and suppliers actually ready for that? submitted by /u/Altenar_b2b [link] [留言]
I just had a long conversation with Claude about 'paraquat' (a type of agricultural chemical) from a scientific and public-policy perspective. I wanted to discuss about its toxicological mechanism, why it is difficult to treat (if someone drinks it), current research, agricultural regulation (many countries have banned this chemical because it's too toxic), safer herbicides, plant-specific biochemical targets, and weed-control methods. These were just some coherent questions about toxicology, medicine, agriculture, and plant biology. I never said that I wanted to harm myself, that I had access to paraquat, or that I was in any immediate danger. Despite that, Claude repeatedly redirected the conversation toward suicide intervention. It asked whether I was considering harming myself, told me to move dangerous substances away, asked whether anyone was nearby, and repeatedly gave me crisis hotline numbers. The first time this happened, I explicitly objected and said that scientific interest in a toxic substance is not evidence of suicidal intent. Emergency physicians, toxicologists, biology students, and public-health researchers discuss exactly these questions everyday, and very few people commit suicide from this type of discussions. Claude apologized and said it understood. Then it did it again. It apologized again and promised to stop. Then it did it again. I reviewed the full transcript and I counted approximately: 30 responses that personally implied I might be suicidal, self-harming, or in a psychological crisis I objected about 20 times and told it to stop 28 of those implications occurring after I had already clearly rejected the assumption At least 14 promises that it would stop asking or stop inserting crisis-intervention content At least 12 later violations of those promises Claude repeatedly acknowledged my correction, accurately summarized that I was asking normal scientific questions, promised not to make the assumption again, and then resumed the exact s