MAROKO133 Breaking ai: Claude Code costs up to $200 a month. Goose does the same thing for

📌 MAROKO133 Breaking ai: Claude Code costs up to $200 a month. Goose does the same

The artificial intelligence coding revolution comes with a catch: it's expensive.

Claude Code, Anthropic's terminal-based AI agent that can write, debug, and deploy code autonomously, has captured the imagination of software developers worldwide. But its pricing — ranging from $20 to $200 per month depending on usage — has sparked a growing rebellion among the very programmers it aims to serve.

Now, a free alternative is gaining traction. Goose, an open-source AI agent developed by Block (the financial technology company formerly known as Square), offers nearly identical functionality to Claude Code but runs entirely on a user's local machine. No subscription fees. No cloud dependency. No rate limits that reset every five hours.

"Your data stays with you, period," said Parth Sareen, a software engineer who demonstrated the tool during a recent livestream. The comment captures the core appeal: Goose gives developers complete control over their AI-powered workflow, including the ability to work offline — even on an airplane.

The project has exploded in popularity. Goose now boasts more than 26,100 stars on GitHub, the code-sharing platform, with 362 contributors and 102 releases since its launch. The latest version, 1.20.1, shipped on January 19, 2026, reflecting a development pace that rivals commercial products.

For developers frustrated by Claude Code's pricing structure and usage caps, Goose represents something increasingly rare in the AI industry: a genuinely free, no-strings-attached option for serious work.

Anthropic's new rate limits spark a developer revolt

To understand why Goose matters, you need to understand the Claude Code pricing controversy.

Anthropic, the San Francisco artificial intelligence company founded by former OpenAI executives, offers Claude Code as part of its subscription tiers. The free plan provides no access whatsoever. The Pro plan, at $17 per month with annual billing (or $20 monthly), limits users to just 10 to 40 prompts every five hours — a constraint that serious developers exhaust within minutes of intensive work.

The Max plans, at $100 and $200 per month, offer more headroom: 50 to 200 prompts and 200 to 800 prompts respectively, plus access to Anthropic's most powerful model, Claude 4.5 Opus. But even these premium tiers come with restrictions that have inflamed the developer community.

In late July, Anthropic announced new weekly rate limits. Under the system, Pro users receive 40 to 80 hours of Sonnet 4 usage per week. Max users at the $200 tier get 240 to 480 hours of Sonnet 4, plus 24 to 40 hours of Opus 4. Nearly five months later, the frustration has not subsided.

The problem? Those "hours" are not actual hours. They represent token-based limits that vary wildly depending on codebase size, conversation length, and the complexity of the code being processed. Independent analysis suggests the actual per-session limits translate to roughly 44,000 tokens for Pro users and 220,000 tokens for the $200 Max plan.

"It's confusing and vague," one developer wrote in a widely shared analysis. "When they say '24-40 hours of Opus 4,' that doesn't really tell you anything useful about what you're actually getting."

The backlash on Reddit and developer forums has been fierce. Some users report hitting their daily limits within 30 minutes of intensive coding. Others have canceled their subscriptions entirely, calling the new restrictions "a joke" and "unusable for real work."

Anthropic has defended the changes, stating that the limits affect fewer than five percent of users and target people running Claude Code "continuously in the background, 24/7." But the company has not clarified whether that figure refers to five percent of Max subscribers or five percent of all users — a distinction that matters enormously.

How Block built a free AI coding agent that works offline

Goose takes a radically different approach to the same problem.

Built by Block, the payments company led by Jack Dorsey, Goose is what engineers call an "on-machine AI agent." Unlike Claude Code, which sends your queries to Anthropic's servers for processing, Goose can run entirely on your local computer using open-source language models that you download and control yourself.

The project's documentation describes it as going "beyond code suggestions" to "install, execute, edit, and test with any LLM." That last phrase — "any LLM" — is the key differentiator. Goose is model-agnostic by design.

You can connect Goose to Anthropic's Claude models if you have API access. You can use OpenAI's GPT-5 or Google's Gemini. You can route it through services like Groq or OpenRouter. Or — and this is where things get interesting — you can run it entirely locally using tools like Ollama, which let you download and execute open-source models on your own hardware.

The practical implications are significant. With a local setup, there are no subscription fees, no usage caps, no rate limits, and no concerns about your code being sent to external servers. Your conversations with the AI never leave your machine.

"I use Ollama all the time on planes — it's a lot of fun!" Sareen noted during a demonstration, highlighting how local models free developers from the constraints of internet connectivity.

What Goose can do that traditional code assistants can't

Goose operates as a command-line tool or desktop application that can autonomously perform complex development tasks. It can build entire projects from scratch, write and execute code, debug failures, orchestrate workflows across multiple files, and interact with external APIs — all without constant human oversight.

The architecture relies on what the AI industry calls "tool calling" or "<a href="https://platform.openai…

Konten dipersingkat otomatis.

🔗 Sumber: venturebeat.com

📌 MAROKO133 Update ai: China’s electrochemical system converts coal into electrici

Traditional coal-fired power generation is typically associated with high pollution levels, significant carbon emissions, and relatively low efficiency. However, a new approach to coal-based electricity production is challenging the long-standing perception by removing combustion from the process altogether. 

Instead of burning coal, the system converts its chemical energy directly into electricity, avoiding the release of carbon dioxide that normally defines its environmental impact. The breakthrough comes from a research team led by Xie Heping of the Chinese Academy of Sciences at Shenzhen University, who have developed what they describe as a zero-carbon-emission direct coal fuel cell (ZC-DCFC). 

The concept effectively reframes coal as an electrochemical energy source rather than a fuel to be burned, potentially opening a new pathway for cleaner utilization of fossil resources.

Coal fuel cell design removes need for steam cycle or combustion 

Rather than being burned, coal in this system undergoes a multi-step preparation process before it is used for electricity generation. It is first pulverized into a fine powder, then dried, purified, and treated at the surface to optimize its reactivity. The processed coal is subsequently introduced into the anode chamber of the fuel cell, while oxygen is supplied to the cathode side, the South China Morning Post writes.

Inside the cell, the coal particles are directly oxidized through an oxide membrane, producing an electrochemical reaction that generates electricity on the spot. Crucially, this approach eliminates the need for conventional power-generation stages such as steam production and mechanical turbines, which are typically central to coal-fired plants.

At the outlet of the anode, the carbon dioxide produced by the reaction is captured directly on-site and then either catalytically transformed into useful chemical feedstocks such as synthesis gas or chemically stabilized into compounds like sodium bicarbonate. This closed-loop handling of carbon contributes to a process that is described as both silent and clean in operation.

By contrast, conventional coal-fired power plants depend on combustion to generate heat, which is then used to produce steam that drives turbine generators through a multi-stage energy conversion chain. That indirect pathway is fundamentally constrained by thermodynamic limits, particularly the Carnot efficiency ceiling associated with heat engines, which restricts how much of the fuel’s energy can be converted into usable electricity.

Breakthrough improves durability and power output limits

The conventional coal power process is inherently constrained by the Carnot cycle, which limits thermal efficiency to roughly 40 percent, according to Xie. In contrast, he argues that the zero-carbon-emission direct coal fuel cell (ZC-DCFC) avoids the energy losses associated with combustion and heat-based engine systems, allowing for significantly higher theoretical efficiency. 

Since 2018, Xie’s research group has gradually advanced the technology through successive iterations, addressing persistent challenges in materials science, cell durability, fuel processing, and the ability to maintain continuous coal feed. Earlier versions of direct carbon fuel cells struggled with limited power density and short operational lifespans, issues that the latest design aims to overcome through incremental engineering improvements.

The latest version of the fuel cell, though, improves stack scalability, long-term stability, carbon conversion efficiency, and overall system integration, according to the research team.

Xie also noted that the concept could be applied to deep coal seams located about 1.2 miles underground. Instead of mining and transporting coal to the surface – a costly and complex process – the system could convert coal into electricity in situ, transmitting only power upward. In turn, this approach could help offset pressure on supply as shallow coal reserves gradually diminish.

🔗 Sumber: interestingengineering.com