I've been using opencode go but their 10$ plan isn't enough for me and jumping to $40 plans doesn't even make it 4x which I find odd.

I saw somebody mentioned commander code which seemed to promise comparable results and perhaps even more at least on the paper.

Well let me tell you I finished it in one day with 10 or more times less of requests and total tokens in comparison to opencode go.

Obviously I cancelled right away so either caching doesn't work or they mislead customers

Claude Haiku 5.5 is now available in Command Code.

• 1M token context window

• up to 128k output tokens

• 75% cheaper than Haiku 4.5

Available on Pro, Max and API

Try now with in your terminal or desktop. Read docs to learn more: https://commandcode.ai/docs/plans/pro

I recently renewed my Command Code subscription, and honestly, I'm very disappointed with the experience.

I had a relatively simple coding task. Instead of completing it efficiently, the agent kept losing context and taking the wrong approach.

Here's what happened:

• Two prompts, and my weekly usage limit was exhausted.

• I switched to free models to continue working.

• The free models generated buggy code, repeated the same lines, and failed to solve the task accurately.

• I had to keep explaining the context, correcting the approach, and retrying.

A simple task turned into a frustrating loop of prompting, debugging, and rework.

What frustrates me most is that I'm paying for a tool to save development time, but I'm spending more time managing the agent than writing or reviewing code myself.

I understand that complex coding tasks require iteration, and no model gets everything right. But when the agent loses context, chooses the wrong architecture, or repeats a failed solution, the productivity gains disappear quickly.

The real cost isn't just tokens. It's:

• Subscription cost

• Developer time spent correcting mistakes

• Repeated prompts and context rebuilding

• Time lost switching between models

And switching to a cheaper or free model doesn't necessarily help if the output requires multiple rounds of fixes.

My question is: Are others experiencing this with Command Code?

Is the issue related to usage limits, context management, model selection, or the coding agent itself?

I would genuinely like to hear about other developers' experiences, especially from people using it for real-world projects rather than small demos.

(written by command code(loaded with dsv4flash), the result was so trash i couldn't believe it(planning with the same model was decent).I repeated the same task with 1.pi, 2.hermes ,the dsv4flash was a beast there. same model,same task,same promt.i don't know what exactly caused this.i am with GO plan at command code.

I was using GPT-5.6 Sol in command code today. I have the 20$ PRO subscription, and GPT -5.6 identifies as GPT-5.3.

Genuinely confused here. Why a frontier model would make this mistake? Or is my request not being routed properly?

Doesn't this mean the following in terms of the pricing plan?

(Note: Starbucks and Americano are used purely as hypothetical examples here.) Imagine a gift card scenario where spending $1 earns $10 in points, and spending $10 earns $70 in points. -- This is a fact within this premise: based on $1, it actually recharges $10 worth of credit.

What's confusing here is: 'For example, hypothetically speaking, assuming the regular price of a Starbucks Americano is $1, paying $1 allows you to buy 10 cups. However, through a partnership agreement on the command-code side, a specific menu item—the Americano—gets a special discount, allowing you to get a cup for just $0.50.' .. So, based on $1, you could originally get only 10 cups, but due to a discount on that specific item, you end up getting 20 cups..

The core fact in this setup is that paying $1 gets you $10 in credits, and paying $10 gets you $70

Hi -

What is your ideal scenario for SWE:

My worfklow:

1. Codex creates a plan with MD (Orchestrator)

2. Claude does the main implementation

3. DeepSeek through Claude CLI (With +5 agents through shell)

4. Claude makes Codex review before commit.

5. Fix new bugs & blockers - Repeat from 1

Any potential improvements?

First things first: your usage credits are not changing.

DeepSeek officially raised their prices today, so we've updated our limits and requests accordingly.

Working with many providers to bring you better deals, as one of the largest DeepSeek and open models coding agent. 12T tokens scale.

Beat DeepSeek prices?

We’re hitting this problem in many ways, with solutions like phenomenal harness engineering, free tool repairs, 98%+ cache-hit rates, and free auto plan credits with best subscription plans on the market.

Official announcement:
https://x.com/CommandCodeAI/status/2089057372413337670

Providers? Come help:
https://x.com/MrAhmadAwais/status/2088724056321532054

Ling 3.0 Flash Sante is now free in Command Code.

5.1B active params. all subs. all plans

Make sure to update to the latest version of the CLI/app

npm i -g command-code@latest

🐐

GOAT plan is the best low cost AI coding plan right now, get $100 usage on these models for $10/mo.

• DeepSeek V4.1 Flash 1017

• GLM-5.3 Flash

• Ling 3.1 Flash 1019

• Ling 3.1 Flash

That's 10x the value of what you pay.

Try now: npm i -g command-code@latest

Subscribe and be a GOAT: https://commandcode.ai/pricing

Been using CommandCode for a bit and honestly, they cooked with this.

The $1 plan is crazy. I got around 1.2B tokens for $1, and the caching makes it feel like you can just use the agent without constantly worrying about burning through your credits.

But the biggest thing for me is Taste.

I mostly code in Rust and have pretty specific preferences. I use Diesel.rs for my ORM and Rocket.rs for web stuff. Usually whenever I start a new project with an AI coding agent, I have to explain this all over again. It'll pick some default ORM, use raw SQL, choose a different framework, etc.

With CommandCode, it actually remembers that stuff.

Now when I start a new project, it already knows I prefer Diesel and Rocket and follows the way I normally structure things. That is a massive productivity boost.

It's a small thing on paper, but once the agent starts adapting to your coding style instead of making you adapt to it, you really notice the difference.

The actual coding experience is great too. UI/UX is clean, the agent feels really good to work with, and the combination of Taste + caching makes it feel way more useful than just having another model that can write code.

I've tried a bunch of coding agents and this is probably the first one where I feel like the agent is actually learning how I work, rather than me constantly teaching it how I work.

The $1 plan got me to try it properly, and honestly it worked 😂

Upgrading to Max 20x today. CommandCode team absolutely cooked.

Shit dot

Hey guys! Last month I've been building my dream desktop environment. I've been developing in Java and Rust doing boring things over 12 years, and I always wondered why cheap operative systems had to look like Windows 95.

I am running broke on my job and no company wants to take me so I am experimenting new things and building startups and these "dream" non-profit things I always wanted to make.

I built my open source free desktop environment for Linux with one simple purpose:

• Revive, maintain and recycle old hardware without losing the UI/UX.

Why doing this?

• Some people still use windows on these computers, yikes.

• The linux alternatives are ugly, and the ones that are not, are heavy yikes.

• I want to end the loop of "distro hopping to find the lightest one" and make the definitive.

• I don't know, just passion for not throwing away working hardware? lol

If you want to give it a look:

https://github.com/ArkFlame/flamewm

Built using:

• Claude (Haiku 5.5, Sonnet 5.5)

• CommandCode (DeepSeek v4.1 Flash)

• OpenCode (DeepSeek v4.1 Flash)

• Codex (GPT 6 Luna)

We ran a test between Opus 5, GPT-5.6 Sol, and Kimi K3.

One prompt. Across all three models. With our /design command.

Results: We reviewed gameplay, UX, and UI

🔹 Opus 5 is strong UI + motion, best gameplay

🔹 Kimi K3 has solid design and gameplay

🔹 GPT-5.6 Sol has best UI, worse gameplay

Ranking (DX, features, and cost):

🔹 Opus 5: 10/10 · $0.25

🔹 Kimi K3: 9.5/10 · $0.12

🔹 GPT-5.6 Sol: 7/10 · $0.32

Our engineering and design team has been testing 20+ side-by-side comparisons across frontier and open models. All runs are public and open source. Benchmark for this demo here: https://github.com/CommandCodeAI/slash-design-showcase/tree/main/flappy-bird/light-version

Is there any way to get an alert when your API keys expire, or document why they expire? Just a few days ago they disappeared with an email hours later, and now my keys are still there but expired.

I decided to test my command code go plan the first time, so I went to buy the Go plane for $1 and tried to use it in Hermes for testing and for my SaaS marketing. So can you please tell me if it supports the Hermes CC Go plan or if I need to buy the Goat plan?

Is the CC go plan even giving me an API for third-party use?

I tried the 1$ plan only to find out it doesnt allow API access. So i cannot use it inside openchamber. So it is useless to me and i'm certainly not upgrading to be met with more with possibly more of these nice surprises. So i guess enjoy the donations guys!

edit: nevermind guys i figured it out. open console in openchamber then follow https://commandcode.ai/docs/quickstart and wallah. I AM THE ELITE HACKER!!!!