u/ImprovementHuge3804

DeepSeek is ridiculously good value.

I topped up another 100 RMB yesterday.

Spent almost the entire weekend building and experimenting with AI stuff, and after two days the bill was only around 20 RMB (~$3).

People talk a lot about frontier models, AGI, and billion-dollar training runs.

Meanwhile, some of us are happily living on the "poor man's AI subscription plan."

Honestly, it's hard to complain when you can spend an entire weekend coding with an LLM and pay less than the price of a coffee.

SpecKit as Code.

The idea sounds great until the number of rules starts growing.

At some point, maintaining the spec becomes a job of its own. Every new convention, workflow, edge case, and exception adds more cognitive overhead.

My takeaway is that SpecKit only becomes practical when AI is involved in maintaining the rules themselves.

Humans define the principles.

AI keeps the specifications synchronized, updated, and enforced.

Without AI, you're essentially creating another documentation system that slowly drifts away from reality.

With AI, the specs can evolve together with the codebase.

SpecKit as Code is interesting.

AI-maintained SpecKit is where it actually becomes scalable.

love mimocode

it is great， not just coding agent， but can be a common agent for any task。

Burned through my entire GPT-5.5 quota in under 2 hours.

Good thing DeepSeek V4 has my back.

Turns out the best token optimization strategy is just... being good enough at programming to get it right the first time.

Fewer iterations = fewer tokens = less money burned.

The irony?

The expensive model made me lazy — sending half-baked code and letting AI fix it.

DeepSeek forces me to think before I type. Probably healthier in the long run.

AI has taught me some hard truths:

- A bad general ruins the whole army.

- Nothing gets destroyed quite like experts being overruled by clueless managers.

- And yes — even a legendary sword becomes just a fire poker in the wrong hands.

Give a Fable 5 to someone who doesn't know what they're doing, and you've handed a laser gun to a monkey.

Give a DeepSeek V4 to someone who actually understands it, and they'll run the world.

So I've been thinking about what to call people like us who spend weekends messing around with AI coding tools. You know, Claude Code, Cursor, Copilot, all that stuff. We're not working, we're not trying to build a startup, we're just... playing.

I came up with Token Player. Hear me out.

A football player plays with a ball on weekends. A gamer plays with a controller. We play with tokens. Every time you send a prompt to an AI model, you're burning tokens. That's literally what we're doing - playing with tokens for fun.

I think there are a lot of us out there. The signs are pretty obvious:

- You've installed like 5 different AI coding assistants just to compare them

- You build random projects at 2am on a Saturday that you know you'll never touch again

- You genuinely enjoy reading changelogs for new AI models

- You've tried explaining to your non-tech friends why you spent all weekend building a todo app with AI and they just stare at you

- The debugging is actually fun because the AI handles the boring parts

The best part is there's zero pressure. If your weekend project breaks, whatever. You close the laptop and go outside. It's a hobby, not a job.

Anyway, just wanted to share the term. If you've ever stayed up too late on a weekend experimenting with AI tools, welcome to the Token Player club.

Anyone else feel like this is becoming a thing?

opencode stop all the free quota？？

as we know, the Big GPU company Nivdia is providing a list for advanced LLM free tire. but in my testing, this kind of free tire is useless , not even good as chatbot, and dont think about it for agentic loop.

the problem, the input/oupt is really slow, and not even stable.

deepseek v4 flash，the real god for poor people.

I can finish my tasks , most of the task with just free opencode with deepseek v4 flash; i dont even need to consider the v4 pro.

and the strange thing is , i dont think the v4 pro has a big gap with v4 flash, and v4 flash is really fast..

what do you think ...??

buddy，VSCODE is too heavy to me with LLM，so i want to make it lighter and faster。

here is what i did。

1. open the opencode， using the free DeepSeek v4 flash，one prompt：vscode is too heavy for ai coding，make it lighter and faster。

what happen？

the DeepSeek will scan and understand the current setting of my local vscode， analyst and give 3 options for lighting。I just pick the one i like ， and magic happens，the vscode is faster as the ZED 。。

buddy，VSCODE is too heavy to me with LLM，so i want to make it lighter and faster。

here is what i did。

1. open the opencode， using the free DeepSeek v4 flash，one prompt：vscode is too heavy for ai coding，make it lighter and faster。

what happen？

the DeepSeek will scan and understand the current setting of my local vscode， analyst and give 3 options for lighting。I just pick the one i like ， and magic happens，the vscode is faster as the ZED 。。

not sure if only me, i think the vscode is too heavy for AI now. so many no need plugins, extension, feature can be remove as we are have LLM for viber coding ..

Today, GLM released the new version 5.2, and i just try it on the ZCODE which is the coding CLI from Z-ai.

I found a free quota as 300M, which is great. I tested with some standard task , for example, improving my home page , make it look better.

The interesting part is that, it will trigger a skill called frontend design, and the final result for the home page is great.

I think the Z-ai will define the skills according the GLM LLM specifically, and that is the value of harness engineering.

What do you think about it ? do you like GLM or not ?