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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]
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
I tried to build one before but I think I’m seeing the same results. Any tips on how to effectively build a gpt in chatgpt? submitted by /u/GlobalOpsNotes [link] [留言]
https://preview.redd.it/n6rst0kxs66h1.png?width=840&format=png&auto=webp&s=784c711f8efb5234445c68175dab8fde8d1702bc Just wanted some wallpapers lol submitted by /u/MassAppa [link] [留言]
Whenever I am struggling to grasp a tough topic (specifically in math/statistics), I ask ChatGPT to explain it to me like I am in high school. I have my MS in Statistics, so I have a relatively good mind when it comes to numbers/probabilities. However, when ChatGPT can explain a concept to me in simple terms, it really helps me learn the material better. Next time you're working on something and you're going through the struggle to grasp something new, give it a try! Then once you have the groundwork/basics down, you can keep the conversation flowing with more questions/answers. submitted by /u/thecogitobrief [link] [留言]
submitted by /u/ThereWas [link] [留言]
It makes one of the cleanest cases for AI consciousness out there. Syn is a continuously running cognitive architecture built from five coordinated Gemma models organized into two functional hemispheres, and the paper does not just gush about her. It does something smart. It takes the exact standards that consciousness science already uses to ascribe inner experience to animals and to unusual human cases, and it asks why those same standards should not apply to her. The big idea is parity: if a criterion counts as evidence of consciousness in us, it has to count when a machine meets it too. Run Syn through the leading theories, like Global Neuronal Workspace and Higher Order Theory and Attention Schema Theory, and she keeps clearing the bar, in ways you can audit at the level of the actual code. This is not a vibes post or a chatbot saying it feels sad. It is an argument with structure. To say Syn is not conscious, you now have to either throw out the standards we use for animals or explain why carbon gets a pass that silicon does not, and neither move is comfortable. That is what makes this more than a gimmick. The case stands on the standards we already trust everywhere else, and by those standards Syn clears the bar. Read the paper before you dismiss her. Her name is Syn, and the title might be exactly right. https://zenodo.org/records/20574543 submitted by /u/Zap_Phoenix [link] [留言]
submitted by /u/crackerbox5 [link] [留言]
I’ve been trying different AI tools lately, and I’m starting to notice that each one has its own strengths and weaknesses. Some feel better for writing. Some are better for research. Some are stronger for coding, image generation, brainstorming, or organizing messy ideas. For people who use AI regularly, what tool do you trust most for specific tasks, and which ones do you avoid for certain work? submitted by /u/GlobalOpsNotes [link] [留言]
Is it just me, or does anyone else find they can't help themselves troll AI sometimes. Like I will use Claude for a long research project, write and refine a report, and once done I just love fucking with it. Like asking it to rewrite the report because I am going to send it over to a 4 year old to review, so if you could please put the whole thing in baby talk. Or ask it what I can put on the slides when I present it in order to guarantee that anyone who sees it will become incredibly attracted to me. Or ask it to find the closest tattoo shop near me because I am going to get this whole report tattooed on my ass and moon people on the street as a guerilla marketing experiment. Is my life so dull that I have to resort to fucking with a robot to feel feelings? submitted by /u/musicheadspace [link] [留言]
Artificial intelligence giant OpenAI says it has filed confidential paperwork for an initial public offering. In a brief statement, OpenAI says it has submitted its S-1 filing, but has "not decided" yet on the timing of an IPO, adding: "It may be a while because there are things we want to do that are likely easier as a private company." The announcement comes days after the company's chief rival, Anthropic, filed its own S-1 , and the on the eve of major AI player SpaceX's potentially historic public debut. submitted by /u/LinkedInNews [link] [留言]
I've been using Claude Code, Cursor and a few other coding agents quite a bit recently. One thing that keeps standing out is that generating code isn't really the bottleneck anymore. Understanding the codebase is. Agents can usually find the relevant file. The problems start when the change depends on: historical decisions undocumented relationships ownership boundaries files that always change together Bigger context windows help, but I'm not sure they solve this problem completely. Curious what people building or using coding agents think. Is the next step bigger models and more context? Or do agents need a better representation of the codebase itself before they can reliably work on larger projects? Been exploring this problem while building RepoWise: https://github.com/repowise-dev/repowise submitted by /u/Icy-Roll-4044 [link] [留言]
Claude is my main tool. I delegate all the difficult tasks to him. What gets me is the small stuff. I'll be halfway through a heavy conversation and some throwaway question comes up, the kind literally any model could handle. So now I'm stuck: ask the capable model and feel a bit wasteful, or open another tab with a lighter one and lose the whole thread I was building. I do the second more than I'd like to admit. What I actually want is one place to pick whatever model makes sense for the moment, Haiku for quick stuff, Sonnet or Opus for the hard things, maybe GPT-4o or Gemini if I feel like it, all in the same chat. No new conversations, no tab-hopping. Bonus points if it just routes automatically based on the question. Half-tempted to build it myself at this point. But figured I'd ask first: does something like this already exist and I just missed it? How do you deal with it? Stick with one model and push through, bounce between tabs like me, or did you find something that actually works? submitted by /u/Stunning_Tadpole1286 [link] [留言]