I'm on the $100 Max plan and am getting better results with GPT-5.4 on the $20 Pro plan, both in terms of quality and amount of work. Could it be that the moment Anthropic started leading the LLM race, it also started enshittifying its product? I know enshittification implies a longer process, but is this the first step? Curious to hear what others are experiencing.

Comments URL: https://news.ycombinator.com/item?id=47718450

Points: 1

# Comments: 0

It's hard to say why GSD worked so much better for us than other similar frameworks, because the underlying models also improved considerably during the same period. What is clear is that it's a huge productivity boost over vanilla Claude Code.

Like an engineer overseeing the construction of a bridge, the job is not to lay bricks. It is to ensure the structure does not collapse.

The marginal cost of code is collapsing. That single fact changes everything.

https://nonstructured.com/zen-of-ai-coding/

Like an engineer overseeing the construction of a bridge, the job is not to lay bricks. It is to ensure the structure does not collapse.

The marginal cost of code is collapsing. That single fact changes everything.

https://nonstructured.com/zen-of-ai-coding/

I came to share a blog post I just posted titled: "ChatGPT Health is a Marketplace, Guess Who is the Product?"

OpenAI is building ChatGPT Health as a healthcare marketplace where providers and insurers can reach users with detailed health profiles, powered by a partner whose primary clients are insurance companies. Despite the privacy reassurances, your health data sits outside HIPAA protection, in the hands of a company facing massive financial pressure to monetize everything it can.

https://consciousdigital.org/chatgpt-health-is-a-marketplace...

Comments URL: https://news.ycombinator.com/item?id=46541533

Points: 310

# Comments: 311

I've been using Speckit for the last two weeks with Claude Code, on two different projects. Both are new code bases. It's just me coding on these projects, so I don't mind experimenting.

The first one was just speckit doing its thing. It took about 10 days to complete all the tasks and call the job done. When it finished, there was still a huge gap. Most tests were failing, and the build was not successful. I had to spend an equally long, excruciating time guiding it on how to fix the tests. This was a terrible experience, and my confidence in the code is low because Claude kept rewriting and patching it with many fixes to one thing, breaking another.

For the second project, I wanted to iterate in smaller chunks. So after SpecKit finished its planning, I added a few slash commands of my own. 1) generate a backlog.md file based on tasks.md so that I don't mess with SpecKit internals. 2) plan-sprint to generate a sprint file with a sprint goal and selected tasks with more detail. 3) implement-sprint broadly based on the implement command.

This setup failed as the implement-sprint command did not follow the process despite several revisions. After implementing some tasks, it would forget to create or run tests, or even implement a task.

I then modified the setup and created a subagent to handle task-specific coding. This is easy, as all the context is stored in SpecKit files. The implement-sprint functions as an orchestrator. This is much more manageable because I get to review each sprint rather than the whole project. There are still many cases where it declares the sprint as done even though tests still fail. But it's much easier to fix, and my level of trust in the code is significantly higher.

My hypothesis now is that Claude is bed at TDD. It almost always has to go back and fix the tests, not the implementation. My next experiment is going to be to create the tests after the implementation. This is not ideal, but at this point, I'd rather gain velocity, since it would be faster for me to code it myself.

Comments URL: https://news.ycombinator.com/item?id=45426350

Points: 3

# Comments: 0

https://consciousdigital.org/wp-content/uploads/2023/04/dece...

Years ago, I was an amazing C++ dev. Later, I became a solid Python dev. These days, I run a small nonprofit in the digital rights space, where our stack is mostly JavaScript. I don’t code much anymore, and honestly, I’m mediocre at it now. For us, AI coding agents have been a revelation. We are a small team lacking resources and agent let us move much faster, especially when it comes to cleaning up technical debt or handling simple, repetitive tasks.

That said, the main lesson I learned about vibe coding, or using AI for research and any other significant task, is that you must understand the domain better than the AI. If you don’t, you’re setting yourself up for failure.

No you don't. You charge extra for privacy and list it as a feature on your enterprise plan. Not event paying pro customer get "privacy". Also, you refuse to delete personal data included in your models and training data following numerous data protection requests.