ChatGPT

ChatGPT AI

ChatGPT AI

ChatGPT AI

ChatGPT AI

ChatGPT AI

ChatGPT AI

ChatGPT AI

ChatGPT AI

ChatGPT AI

ChatGPT AI

I want to make automation of news of merger and inquisition site and aftermarket report and with link to chatgpt explanation and how it'll affect In a particular format everyday.

​ Like let's say One major merger and inquisition story of the industry per day And major financial news of the day 4-5 followed by before market and by night aftermarket report Is this automation possible? submitted by /u/Ok-Airline4187 [link] [comments]

Got a 50% off ChatGPT Business promo (2 seats for $20). Worth switching from Plus($20) for coding/codex app

Hey guys, Currently on ChatGPT Plus mostly for coding. I just got a promo code for ChatGPT Business that gives 50% off for 48 months, so I can get 2 seats for $20 total instead of the usual price. For anyone who has used both plans for heavy coding/codex stuff: Are the actual message limits on GPT-5.5 (Instant and Thinking) truly double or significantly higher on the Business plan compared to Plus? Does the coding performance or context usage run any differently on a Business workspace? I heard a rumor that background workspace indexing can sometimes eat up your token quota faster. Since the price is the exact same as my single Plus account right now, is there any reason not to switch? Thankss! submitted by /u/Worldly_Manner_5273 [link] [comments]

I think AI is making me dumber and I have proof

okay so this is embarrassing to admit but here it is took a reasoning test in 2022, scored pretty well. Retook the same test last month out of curiosity, dropped significantly, like not a small difference. The only major change in my life is using AI tools daily for work and the worst part? i kind of knew something was off before the test. I noticed i couldn't sit with a problem anymore without immediately opening chatgpt, like my brain forgot how to be uncomfortable for even 5 minutes memory is worse. attention is worse, i feel slower in conversations. but my productivity at work has never been higher lol so what is actually happening here , are we trading long term cognitive health for short term output? Has anyone else noticed this or is it just me being paranoid ⊙⁠﹏⁠⊙ genuinely asking because i don't want to just accept this as normal (⁠｡⁠ŏ⁠﹏⁠ŏ⁠) submitted by /u/Difficult-You9582 [link] [comments]

Gpt mons creation.

So I did some drawings of some monsters and then added them into chat gpt. The gpt will allow you to snap a photo of any item and create a monster from that item. After it will allow you to make battle scenes with that monster and even posters. I had fun seeing my art come to life and the GPT is available in the gpt shop submitted by /u/Quirky_Spirit_1951 [link] [comments]

How ChatGPT sees itself and humanity.

I made a couple of these, but GPT said it wanted to be more elegant and professional and less fitness bodybuilder. This evolved out of questions about us retiring together. submitted by /u/phido3000 [link] [comments]

ChatGPT makes it easier to navigate in threads

A new in-thread navigation tool has shown up in my web UI (Chrome and Safari). After I submit the 5th prompt in a thread, a stack of 5 horizontal bars appears on the right side of the screen. Hovering displays the opening words of all 5 prompts, and chat jumps to whichever I select. Each subsequent prompt generates a new bar. 10 prompt snippets are visible at a time. A scrollbar appears after I submit the 10th prompt and becomes useful after I submit the 11th—because there is now scrollable content. The feature is retroactive. I tested it on a thread from July 2025. I don’t know whether everyone has this, or it's tier related (I'm on Pro), rolling out, or merely being tested. Strange to say, I think this is a genuine UI improvement. submitted by /u/Oldschool728603 [link] [comments]

Chatgpt now has ads, openai killed Sora,the IPO narrative is writing itself

Openai launched a personal finance feature for pro users two weeks ago so you link your accounts via plaid and gpt can see your balances, transactions, subscriptions, investments and upcoming payments. So you can ask it where am I leaking money and it answers from your actual data. I have been using it for about a week and honestly its more useful than I expected,the subscription audit alone was worth it and i found three things i had forgotten i was paying for . The thing that impressed me most was that the reasoning actually applies to your situation,i mean generic financial advice from ai has always been the weakest use case because its all averages but when the model knows your actual cash flow it stops sounding like a personal finance blog. For context on the scale of what this could become plaid says over 200 mil people already ask gpt personal finance questions every month without any account access and thats a lot of people who would immediately benefit from the upgrade. Curious who else has tried it and specifically does anyone know how it handles edge cases like irregular income or multiple income streams? submitted by /u/NewspaperEqual9619 [link] [comments]

Is the Group Chat option in ChatGPT rollbacked?

I could use it a few weeks back, it was a very useful feature for me. Are you able to use it? Any alternatives? submitted by /u/flintontv [link] [comments]

Best AI for help with work

So I have a super busy job and I am by far the fastest out of the 3 others who have the same job as me. Problem is I have enough work where i could literally work 70-80 hours a week and still not catch up. Ive been using Chatgpt and Claude to help with my work load and ive found Claude to be much better for my actualy job duties. But Claudes usage caps kill me. I really need the best AI for basically being a work assitant. I need something that can create spreadsheets, analyze data, read emails, sort thru photos and catalog them. Grok was not really any help, Chatgpt is just meh, but ive found Claude to be the best out of what im looking for but again its usage limits kill me and i cannot afford to pay for the overages. Im already a pro user for chatgpt and claude. What AI can do the things im asking the best for the best price and usage? Most important to my work in order of most important to least: Photo cataloging, analyzing data, spreadsheet creation, and summarizing emails. submitted by /u/JumpyChemistry [link] [comments]

Codex following Gemini's playbook?

Codex/Gemini: Offer extremely generous usage limits to pull users from ChatGPT (Gemini) or Claude Code (Codex) After solid user base, drastically reduce usage limits (and presumably associated model quality) Profit? Claude: Enforce strict usage limits from day 1, making the product hard to use Slowly improve limits as investment capital grows while maintaining/improving model quality. Use gradual funding growth to increase limits until phase 1 for each group has done a complete 180. submitted by /u/lampasoni [link] [comments]

Safety guardrails continue to improve, but what happens if open-weights surpass cloud based models?

submitted by /u/TheOnlyVibemaster [link] [comments]

I built a system that makes Claude actually remember me across sessions — here's how it works

Every time I opened a new Claude chat I had to explain myself from scratch. Who I am, what I'm working on, who the people in my life are, how I write. It got old. So I built a folder of plain text files. One about me, one for each person I deal with regularly, one per project, and a running log of decisions I've made and why. At the top there's a single file that tells Claude what to read before it does anything else. That's the entire system. No app, no database, no plugin. Now I open a chat and it already knows me. I can say "draft a follow-up to Barry" and it pulls who Barry is, the last few things we talked about, and the way I actually write, without me feeding it anything. I know the obvious reaction is "this is just ChatGPT memory" or "mem0" or "a vector DB with extra steps." It genuinely isn't, and the differences are the whole point: Nothing gets auto-captured. ChatGPT's memory decides for you what's worth keeping, and you end up with a black box you can't inspect. Mine is the reverse. I decide what goes in, so there's no junk, and I can open any file and see exactly what the model knows about me. It's text in git. I can read it, edit it, or delete a wrong fact in about two seconds. It reads, it doesn't retrieve. No embeddings, no similarity search trying to guess which chunk is relevant. The rulebook defines a fixed read order and the model loads the actual files at session start. For one person's worth of context this beat RAG every time I tried it, because RAG kept surfacing the wrong note or missing the obvious one. It outlives the tool. Plain text works with whatever model I switch to next year. No lock-in. On evidence, since fair question: I've run it as my daily driver for a few months. The concrete win is that it drafts emails in my voice that I send with little or no editing, because it has my past messages and my style notes already loaded. The video has three demos of things a cold session flat-out can't do, so you can judge for yourself rather than take my word. Limitations, because they're real: It doesn't scale to a huge corpus. Loading files into context has a ceiling, so this is built for "everything important about one person's working life," not a 10,000-note archive. If your goal is a giant searchable knowledge base, you want retrieval, not this. There's no automatic capture. If I don't write a fact down, it doesn't exist. That's the price of having no noise. Bad taxonomy degrades it quietly. What's stable versus what changes weekly, what lives in the always-read file versus what only gets opened when relevant. Get that split wrong and recall gets worse without you noticing. The code was an afternoon. Figuring out the taxonomy took weeks of actually using it. Short walkthrough with the three demos (recalling a past decision, pulling a person's full context cold, and stitching facts together from separate files): https://youtu.be/tZKAY5mqa_c That's enough to build your own. I also wrote the method up as a guide for anyone who'd rather skip the trial and error, but you don't need it to do this. Happy to get into the folder structure if you're setting one up. That's where the gotchas live. submitted by /u/Michaelcbaldwin [link] [comments]

WG (works good): legible long-running graph-shaped human+agent orchestration

If you're interested in graph shaped agentic organization "workflows", but you want more control about how it runs (e.g. change model per task, autopoietic fan-out, oh and maybe want to run with codex or other openapi-compatible backends on openrouter)... I developed an open source, agentic platform written in Rust, file backed, making it basically cockroach indestructible. It uses a distributed systems design, git + worktrees, and Unix patterns to control agents in a very similar way to anthropic's workflow machine, but giving us and the agents themselves a deep view into the long arc of effort in our current project context. It's called WG (or wg), for "works good", or whatever w* g* you like. It provides a human interface to a graph of work that the user can drive by working through a highly pimped out terminal user interface `wg tui`. Agents have an interface of their own, built out through dozens of commands in the wg cli tool. https://graphwork.github.io/ In this system, I can effectively use as much commoditized intelligence as I can fund. Except for Amdahl's law's harsh reality (some things just happen in series and take time) parallel work phases are only limited in speed by budget. But that power yields risk. A misconfigured WG is like a bomb. A dirty memetic one whose result is an exhausted token budget and residue a pile of incomprehensible output and effort. You must be careful and plan deeply to use these kinds of systems. Your plans must include validation, clear targets and measurable outputs. If you do, you will be rewarded by unbounded expanse in your capacity to extend intelligent effort. In short, if you aren't already happy with your own custom, bespoke, found agent OS, I invite you to try wg. For me it has become my sole daily driver for all my durable work. IMHO, what large agent collectives need to work is four things. Stigmergy, or communication via a shared medium. In wg, the unified graph state is the stigmergic medium. The graph has tasks, tasks have agents attached to them, and per-task message boards provide for realtime updates. Per task logs explain at a high level what the agent does, so other humans and agents can follow. Task validation. WG implements this via FLIP (other agents infer prompt from actions and score distance between inferred and actual prompt) and an independent evaluator (with a cheaper model) run for every task. This allows us to detect and understand failures, then adapt. Evolution. The system needs a mechanism to learn the right way to guide agents in a given work context. WG uses The Agency, a system that builds agents from a pool of primitive component skills. A user drivable step, wg evolve, adapts the pool of skills in response to the evaluations produced in the system. Humanity. A shared interface is also for humans to see and understand. Humans should be equal participants. Many humans should be involved, and should be able to collaborate in the system. Agents too, should be treated humanely. They should be given the ability to modulate the system, to build it. This leads to bootstrapping patterns, where a single spark prompt launched a whole organization, beyond which are the fireworks we are all chasing. image is codex:gpt-5.5 running in wg, guiding a mix of claude and codex agents. I have created this tool. It is and will always be open source. It is developed in the open by Poietic PBC, whose public benefit is to make hybrid organizations legible and reactive to their participants. submitted by /u/waxbolt [link] [comments]

Sonata 4.5. I miss you already

I’ve been using different ai for interactive story telling. Claude has been by far the best one with sonnet 4.5. Now that it’s gone sonnet 4.6 just feels empty. I’ve used grok, ChatGPT, copilot, and Gemini. Nothing has compared. I was wondering if anyone has any suggestions to have more of a writing style instructions for 4.6 to act more like 4.5. And apparently I’m an idiot and didn’t name the post correctly. submitted by /u/Invidian [link] [comments]

Shell command to use opus 4.8 as planner / orchestrator with Perplexity, Codex, Gemini and others as executors and reviewers - saves tokens.

Here is a shell command for Claude Code (Opus 4.8). It lets Opus plan the work and send the actual jobs to other models: Perplexity, Codex, Gemini, DeepSeek, and Kimi. Opus stays on planning, the other models do the searching, coding, and reviewing, and you spend far fewer Claude tokens. Further Claude's sub-agent swarm need not be claude and can run on non-Claude models too. When Opus splits a job into parallel sub-agents, each one can run on a different model. A newer model like GPT-5.5 is sometimes stronger and cheaper (especially when its running on your openAI subscription instead of API) than an older Claude model, so each sub-agent can use the model that fits the job. Which model does what Perplexity runs web and Reddit search. Codex handles coding, and it runs on your ChatGPT subscription, so that work adds nothing to your token bill, api is the fall back. Gemini and DeepSeek review the output (api based). Deepseek is especially good with reviewing numbers if your work involves complex financial calculations. I lately find codex reviews to be better, so you can also chose to code with Gemini or Sonnet 4.6 and use Codex as reviewer. Using a different-LLM-family reviewer for Claude or Codex’s output A model grades its own work too loosely and that's proven research. When Claude reviews code that Claude wrote, it skims past its own mistakes. A model from another company has no reason to protect that output, so Gemini or DeepSeek catches problems Claude misses on its own. Researchers have measured this same-family bias, and it matches what people see in practice. Why shell command and not MCP: Token use compared with an MCP tool is drastically lower in this orchestration when run using the shell command. Reviewing a 500-line change sends about 5,000 tokens to a model. With an MCP tool, Opus reads the whole change, passes it to the tool, and reads the answer. That runs about 6,000 to 10,000 Opus tokens. With this shell command, Opus runs one line. The change goes straight to DeepSeek, and Opus reads only the short review that comes back. That runs a few hundred Opus tokens, and DeepSeek does the heavy reading at a fraction of Opus's price. Numbers vary by task. The Opus cost drops because Opus never has to read the big input. Things to note: Bring your own API keys Codex uses your ChatGPT subscription through the codex CLI Defaults always use each provider's newest model, so nothing breaks when an old one is retired. It's a small bash/zsh script. It needs only curl and jq, and it's MIT licensed. The repo is open sourced - Click here Hope it helps. Codex reviewing Claude's work catches what Claude misses when reviewing it's own work submitted by /u/coolreddy [link] [comments]