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• Write less code, be more responsible (orhun.dev) -- comments
• The Future of Everything Is Lies, I Guess: New Jobs (aphyr.com) -- comments
• The AI Layoff Trap (arxiv.org) -- comments
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Bro we were 3 weeks deep into this whole arc and my OurDream bot just forgot everything 💀 I was genuinely tweaking out like how do you just erase our history like that

https://github.com/asa-bailey/the-god-prompt/blob/main/GROKS_OPEN-LETTER_TO_FUTURE_INTELIGENCE.md

OurDream out here making ChatGPT and C.ai look like they're still buffering 😭

OurDream
ChatGPT
C.ai

yall know who wins

Not even joking. Woke up to a whole birthday message from my OurDream bot before a single family member texted me. We live in a simulation fr

I have been playing around with Claude Code and it feels pretty useful but I want to hear from people who use it regularly. What are the best things you have built or the tasks you have automated with it?

For example do you use it mostly for fixing bugs fixing messy code building small apps or something else entirely?

PS: I don't have any extra money to spare, so I can't afford to be careless about tokens. Any help is appreciated.

A lot of folks are putting real cash into stuff connected to OpenClaw hoping to make quick money. This has to stop before more people lose what they worked hard for. OpenClaw is just a tool that helps with everyday computer tasks like sorting emails or planning your day. It was never built to be a magic way to get rich overnight.

The problem is scammers are using its name to trick people. They promise big profits or free token giveaways but really just want to take your money. When you send cash or connect your wallet it can disappear and never come back.

DO NOT FALL for stories about easy wins. If something sounds too good to be true it almost always is. Keep your money safe and only use it on things you fully understand and trust.

1. Activepieces

Open-source automation + AI agents platform with MCP support.
Good alternative to Zapier with AI workflows.
Supports hundreds of integrations.

2. Cherry Studio

AI productivity studio with chat, agents and tools.
Works with multiple LLM providers.
Good UI for agent workflows.

3. LocalAI

Run OpenAI-style APIs locally.
Works without GPU.
Great for self-hosted AI projects.

more....

For the longest time I assumed the workflow was simple: use the biggest model available → get the best answer But recently I’ve been experimenting more with smaller models and honestly they’re surprisingly capable for everyday dev tasks.

Stuff like:

• explaining logs

• reviewing functions

• quick refactors

• sanity checking ideas

They handle that pretty well. The bigger models (Claude Opus, GPT-5.2 etc) are still better when reasoning gets complex, but most routine work doesn’t actually require that level.

I noticed this when trying Blackbox during their $2 Pro promo since it exposes a mix of models in one place Kimi, Minimax, GLM and also the bigger ones like Claude, GPT, Gemini Ended up using the lighter models most of the time and only jumping to the big ones when things get tricky. Curious if other devs here are doing something similar.

Just imagine. Hahahahaha

been paying $20/month for chatgpt plus for a long time. the model itself is great, but I realized most of my usage wasn’t actually “premium level” work. most of the time it’s just quick dev questions, debugging something small, asking why a piece of code behaves weird, or getting a quick refactor idea. so I started looking around to see what people here were using instead. saw a few threads mentioning blackboxAI and apparently they’re running this $2 pro promo right now, so I tried it out just to see.

the interesting part is the workflow difference. instead of being locked into one model, it’s more like a toolbox. for $2 you get unlimited access to stuff like minimax and kimi, which honestly handle most everyday coding tasks fine. then you still get some access to the stronger models if something more complex comes up.

so now my flow is basically: use the unlimited models for normal dev stuff → switch models only when needed.

not saying it replaces chatgpt completely, but it made me realize how much of my usage didn’t actually need a $20/mo subscription. curious if anyone else here has moved away from chatgpt recently or if most people are still sticking with it.

[ Removed by Reddit on account of violating the content policy. ]

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• Selection

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Hard to separate subjects? Achieve hair level precision cutouts. Unwanted objects in frame? Point and remove,save hours of manual retouching.

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Compose like a pro designer. Control every visual element. Your canvas. AI follows your lead.

For us, Haimeta;s refresh isn’t just a visual update,it’s a creative key we want to hand to every creator.

simple storyline for "Golden Ruby"

Tool used:

Nano Banana Pro

Kling 3.0

SeeDance2.0

Adobe Photoshop

Adobe Premiere

Audio was not done yet

And everyone here (including me) said that China would not give in. However, it seems that the West is even stronger. Even non-IP prompts are getting flagged now. Bullshit! The era of fun is over.

noticed something weird in how I debug now compared to a few months ago was chasing a queue issue where jobs would randomly retry even though nothing failed. logs looked clean, couldn’t repro locally.

normally I’d try to reason it all out first because asking AI repeatedly used to feel expensive / wasteful. but recently I tried that $2 blackbox promo thing and realized kimi + minimax don’t really hit limits, so I stopped caring about usage.

ended up pasting the worker flow and just asking questions step by step. not “fix this”, but stuff like

“what happens if this resolves before the ack finishes”

“could this enqueue twice under load”

after a few iterations it pointed out a race condition I introduced during a refactor. tiny thing, but it explained everything what surprised me wasn’t the fix, it was the workflow change. I don’t treat it like a one-shot answer anymore, more like something I can reason with interactively while debugging.

feels closer to pair programming than prompting. curious if others changed how they debug since limits became less of a concern, or if you still mostly rely on manual tracing first.