After reading many developers' hands-on reviews, Gemma 4 is truly impressive. The 26B version is fast and uses little memory. What's everyone else's experience?

I do a lot of writing and random problem solving for work. Mostly long drafts, edits, and breaking down ideas.

Around Jan I kept hitting limits on ChatGPT and Claude at the worst times. Like you are halfway through something, finally in flow, and boom… limit reached. Either wait or switch tools and lose context.

I tried paying for a bit but managing multiple subscriptions felt stupid for how often I actually needed them.

So I started testing free options properly. Not those listicle type “top 10 AI tools” posts, but actually using them in real tasks.

After around 2 to 3 months of trying different stuff, this is what stuck.

Google AI Studio is probably the one I use the most now.
I found it by accident while searching for Gemini alternatives. The normal Gemini site kept limiting me, but AI Studio felt completely different.

I usually dump full notes or messy drafts into it and ask it to clean things up or expand sections. It handles long inputs way better than most free tools I tried. I have not really hit a hard limit there yet during normal use.

For research I use Perplexity free.
It is not perfect, sometimes the sources are mid, but it is fast enough to get direction. I usually double check important stuff anyway.

Claude free I still use, but only when I want that specific tone.
Weirdly I noticed the limits reset separately on different browsers. So I just switch between Chrome and Edge when needed. Not a genius hack, just something that ended up working.

For anything even slightly sensitive, I use Ollama locally.
Setup took me like 10 to 15 minutes after watching one random YouTube video. It is slower, not gonna lie, but no limits and I do not have to worry about uploading private stuff.

I also tried a bunch of other tools people hype on Twitter. Some were decent for one or two uses, then just annoying. Either too slow or randomly restricted.

Right now this setup covers almost everything I actually do day to day. I still hit limits sometimes, but it is way less frustrating compared to before.

I was paying around 60 to 80 dollars earlier. Now it is basically zero, and I am not really missing much for the kind of work I do.

I made a full list of all 11 things I tested and what actually worked vs what was overhyped. Did not want to dump everything here.

My friend came over yesterday to dye her hair. She had asked ChatGPT for the 'correct' way to do it. Chat told her to dye the ends first, wait about 20 minutes, and then do the roots.

Because of my own experience with dyeing my hair, that made me sceptical, so I read the instructions in the box dye package. It specifically said to mix it and apply everything all at once. That's how this particular formula is designed to work.

I read the instructions on the package out loud and told her we should just follow what the manufacturer says. She got visibly stressed and told me that 'ChatGPT said to do it differently'.

I pointed out that the company who made the dye probably knows how their own product is supposed to be applied. She still got visibly anxious about going against what ChatGPT told her to do.

It was such a weird moment. She was genuinely stressed about ignoring the AI even though the real instructions were right there in her hands.

Has anybody had similar experiences?

Back in the day, I got ChatGPT Plus mostly for work and to help me write better and do stuff faster. But now I use it for almost everything. Like planning things, rewriting things, orgnizing my thoughts, helping me start things when I didn't know where to begin, and even just when I feel mentally tired and don’t want to think so hard, which is kinda becoming more frequent.

It helps a lot.. Like a lot a lot. Sometimes I honestly wish it would help me in car repairs, but I guess that's too much in the future lol.

I feel way more productive now than I used to be. I get through work faster, I don’t get stuck as much (though sometimes when the context windows shrinks or content gets truncated, quality feels off directly), and I waste less time sitting there overthinking dumb stuff. Between ChatGPT, Claude, and a couple smaller tools I’ve tried, I’ve noticed my whole workflow feels smoother now. I am literally hooked to ChatGPT + Bearbits + Claude Cowork for my work, like I couldn't imagine myself without them (though I'm on ChatGPT Pro + all the other subs that kinda bleed too much money, roughly $350 per month, but the good thing is that I can afford it for now).., AI in general is becoming part of how I think through work now, like slightly panicking when I am *outside* without my meeting transcript app and people ask things that I usually just let AI answer based on my past meetings in literally one click, or when someone asks me to do a presentation without preparing my script beforehand with ChatGPT, or like even the boring things of creating powerpoint slides...

This is what kind of worries me. :/

I can feel myself depending on AI more and more., even for small things that maybe I should still be doing with my own *little, not AI-native* brain. Like how to start writing something, how to structure an idea, how to word a message, or even just how to think through something when I feel lazy.

And I keep wondering like what does this actually do to us long term? Like for us as humanity overall..

Because yes, it makes life easier. Yes, it makes me more productive. But is it also making usthink less? And if it is, what does that mean for our brains after years of this? What happens if we get too used to not struggling mentally anymore? Like how will 2040 people look like, assuming that we didn't nuke ourselves...

I’m not saying AI is bad. I actually love it and use it all the time now. I’m probably already more dependent on it than I want to admit. If it disappeared tomorroow I would feel the difference instantly. I guess we did feel a taste of this when the GPT-4o model disappeared..

I just keep thinking maybe this is helping us a lot, but maybe it’s also changing something deeper in us too. Like not only how we work (which is probably gonna be a fun ride in the upcoming years:)), but how we think, and maybe even how we find meaning in doing things ourselves.

PLEASE tell me we are not doomed..

someone opensource an ai agent that autonomously upgraded itself to #1 across multiple domains in < 24 hours…. then open sourced the entire thing

but here’s why it actually works:

- agents fucking suck, not because of the model, because of their harness (tools, system prompts etc)

- Auto agent creates a Meta agent that tweaks your agents harness, runs tests, improves it again - until it’s #1 at its goal

- best part: you can set this up for ANY task. in this article he uses it for terminal bench (code) and spreadsheets (financial modelling) - it topped rankings for both :)

- secret sauce: he used THE SAME MODEL to evaluate the agent - claude managing claude = better understanding of why it failed and how to improve it

humans were the fucking bottleneck and this not only saves you a load of time, it’s just a better way to train them for domain specific tasks

https://github.com/kevinrgu/autoagent

Every single Instagram reel or TikTok I scroll i see people mentioning Claude and glazing it like it’s some kind of master tool that’s better than every single other ai assistant. do they run a strong marketing program or is it really that good in contrast to other ai tools? Before i started seeing it for the first time i only heard that it’s a little better for coding, but know i see it everywhere. I've tried it too, but it doesn’t seem to be much different than ChatGPT to me. Is it actually this powerful at the moment?

+ Not to mention that many people also hate on ChatGPT too. Though it’s still the best one for me

(edit): i have never searched for it and I dont think that my algorithm is set to appear claude videos. I believe that it’s viral in general and I know you guys agree

I currently pay for Max 20x and the demand at work is so high that I can only get everything I need done because I have access to Claude. However, $200 is equivalent to 70% of the monthly minimum wage in my country, so I don't know anyone else who has Max 20x besides me. The ones I know who pay for Claude reach a maximum of the $20 Pro plan, but what they need to do is much simpler than what I do.

And, well, I know that this phase of "low prices" for subscriptions is temporary, maybe in less than a year we will see an increase in monthly prices, or such drastic reductions that it becomes impossible to pay for AIs in underdeveloped countries. I remember that when Claude started with the $20 plans I was able to do all the necessary work with it back then, and today I pay 10x more to do the same work I did a year and a half ago.

If Anthropic creates a $500 Max 100x plan, for example, I know it would still be affordable for some programmers around the world, but something completely out of the question for programmers in other poorer countries, like mine.

Given this, I tested some cheaper or even free and local AI models, but the cheapest ones don't deliver what they promise and the local ones require a lot of RAM. I did the math and to run the best deepseek model (for what I need) I would have to buy hardware parts equivalent to 80 monthly minimum wages in my country. It is genuinely impossible for us.

Therefore, I imagine that what might prevent things like this from happening is people not paying for the most expensive plans, but at the same time I can't say how "expensive" Claude actually is from the perspective of an American, for example. For me, using Claude via API is total madness, I used it once and in a single message I lost the equivalent of 6 hours of work.

So, what do you think will happen? Will programming AIs become tools reserved exclusively for developed countries?

Claude gave me a lot of freedom, I created projects that I would never be able to accomplish in such a short time. I gained a lot of financial freedom due to these projects, however, I find myself spending more and more and being able to use less. What will probably happen?

tl;dr: access to AIs is becoming increasingly unequal. Will this get worse or not?

Wandb CLI and MCP is atrocious to use with agents for full autonomous research loops. They are slow, clunky, and result in context rot.

So I built a CLI tool and a Python SDK to make it easy to connect your Wandb projects and runs to your agent (clawed or otherwise).

The cli tool works by allowing you to import your wandb projects and structures your runs in a way that makes it easy for agents to get a sense of the solution space of your research project.

When projects are imported, only the configs and metrics are analyzed to index and store your runs. When an agent samples from this index, only the most high performing experiments are returned which reduces context rot. You can also change the behavior of the index and your agent to trade-off exploration with exploitation.

Open sourcing the cli along with the python sdk to make it easy to use it with any agent.

Would love feedback and critique from the community!

Github: https://github.com/mylucaai/cadenza

Docs: https://myluca.ai/docs

Pypi: https://pypi.org/project/cadenza-cli

I'm a strategy person by background. Two years ago I'd write a recommendation and hand it to a product team. Now.. I describe what I want to Claude and I've got a prototype..

Feels like I'm not the only one crossing lanes though.. the engineers I know are making product calls. Product people are prototyping strategic hypotheses. Strategy people are shipping code.

I wrote a more detailed blog on it (which I can share if people want to read) but curious whether people outside of tech are seeing the same pattern.

Can you let me know if you're seeing this pattern in your company and what industry you'd say you're in? I'd think this is primarily tech/big tech right now?

Hola chicos, he creado un agente mayorista que da seguimiento a las conversaciones de clientes potenciales, reserva visitas según una tabla de horarios, rastrea toda la información, escanea clientes potenciales, calcula ofertas y todo está conectado a un flujo de trabajo n8n, cuando llega un cliente potencial, hay una visita reservada, se ejecuta el escáner, etc., te envía un correo electrónico, una notificación de Slack, crea un cliente potencial en Zoho CRM y agrega una fila en Google Sheets, puede manejar compradores y vendedores, algunas personas me preguntaron cuánto les cobro, y aquí está cuando se van, no sé si digo precios tan altos, pero ¿cuánto les cobrarías tú?

But it won't last for long. Costs will fall to $0.005 per video second by 2027 due to algorithm optimization, hardware acceleration, and market competition.

First off, I am a novice to AI, I am still at the stage where I am still trying to figure out how to instruct AI to write exactly what I want.

The premise to this topic is that I want to write stories for my personal consumption and entertainment. At First, I tried to write on my own and I always end up with writer's block at the second or fifth chapter. That's when I started to look around for AI Tools that will satisfy my needs for writing stories for my own entertainment.

Started about mid-March of this year 2026, my first mistake was going to the AI model websites directly and trying to coax the AI there to write prompts only to be told that I reached the limit. I then went to an actual AI Story writing platform by digging around in Google (the first one not the second one that I love to use). That one did not also satisfy my needs or live up to my standards. I could write short stories with that platform, but I reach a hard limit almost every single time.

That's when I came across the second AI story writing platform that I now live to use. It functions similar to wattpad with chapter selection and organizing stories you write into books for easy viewing and editing.

Here's where the fun part comes, the AI part, the platform does not ask for money at the moment and gives you free credits to start off. And now you get to pick which AI model you want to use, but keep in mind that the free credits still come into play, I recommend selecting cheaper models like Deepseek to start off. With cheap models like Deepseek, I was able to crank out about 50 chapters at peak at one point using the free credits.

The next part is the strategy, to make the free credits last a long time. The platform doesn't just let the AI do everything for you. As a matter of fact, you can choose to do everything by yourself, set the scene, the story bible, and also the chapter ideas before tou even hit the generate button, or tou can even choose to type up some chapters by yourself then let the AI model build off of what you have written.

The last part is the credit system itself, now I know I said that the platform does not ask for money, and that is Indeed true. The platform instead asks you to document your journey, or rather, write a review or two cents about them. That's how they spread the word about this site, and I don't know how it all works but it allows them to keep the site free. Probably more numbers of users helps them keep the platform free.

If any of you are interested the website is called Bookswriter. Kudos by the way to the Bookswriter team for their platform.

You can sign up with their platform using the link below:

https:// bookswriter(dot)xyz

Nothing will be lost by signing up with them and it allows tou sample the many different AI Models like Deepseek, Google, Mistral, Grok, etc.

so a while back me and a few folks started working on Caliber, an open source tool for managing AI agent configs and syncing them with your codebase. the idea came from real pain we experienced with agents behaving unpredictably in production because their configs were out of sync.

tonight we crossed 555 github stars and also hit 120 merged PRs and 30 open issues. for a young open source project thats actually pretty wild and i didnt think wed get here this fast.

what Caliber does basically: it treats your agent configuration like code. you version it, sync it with your codebase, and your agents always act on the correct context. no more config drift between test and prod, no more agents doing weird stuff because theyre using stale instructions.

if you build with AI agents and have felt this pain, please check it out: https://github.com/rely-ai-org/caliber

also we have a discord specifically for AI setups where we talk about agent architecture, tool selection, prompt structures, etc. lots of smart people in there: https://discord.com/invite/u3dBECnHYs

would genuinely love more contributors and people to come poke holes in our approach. open source only works when people show up and we have 30 issues wide open for anyone who wants to jump in.

Arguments of whether it will cause paradise or suffering. Will competitors kill each other. Will human life not matter as paradise/AI solutions matter more?

idk if it’s just me but lately i’ve been thinking about how casually we use stuff like chatgpt and claude for everything

like coding, random ideas, sometimes even personal things

and i don’t think most of us really know what happens to that data after we send it

we just kind of assume it’s fine because the tools are useful

also saw some discussion recently about AI companies and governments asking for user data (not sure how accurate it was), but it kind of made me think more about this whole thing

i’m not saying anything bad is happening, just feels like we’ve gotten comfortable really fast without thinking much about it

do you guys filter what you share or just use it normally?

I keep seeing people focus heavily on prompt optimization.

But in practice, a lot of failures I’ve observed don’t come from the prompt itself.

They show up at the transition point where:

model output → real-world action

Examples:

- outputs that are correct in isolation but wrong in context

- timing mismatches (right decision, wrong moment)

- differences between environments (test vs live)

- small context gaps that compound into bad outcomes

The pattern seems consistent:

improving prompt quality doesn’t solve these failures.

Because the issue isn’t generation —

it’s what happens when outputs are interpreted, trusted, and acted on.

Curious how others here think about this layer, especially in deployed systems..