ChatGPT Containers can now run bash, pip/npm install packages and download files

For the last 2 or 3 months we made a commitment as a team to go all in on claude code, and have been sharing prompts, skills, etc, and documented all of our projects and at this point, claude is writing a _large_ percentage of our code. Probably upwards of 70 or 80%. It's also been updating our jira tickets and github PRs, which is probably even more useful than writing the code.

Our test coverage has improved dramatically, our documentation has gotten better, our pace of development has gone up. There is also a _big_ difference between the quality of the end product between junior and senior devs on the team.

Junior devs tend to be just like "look at this ticket and write the code."

Senior devs are more like: Okay, can you read the ticket, try to explain to to me in your own words, let's refine the description, can you propose a solution -- ugh that's awful, what if we did this instead.

You would think you would not save a lot of time that way, but even spending an _hour_ trying to direct claude to write the code correctly is less than the 5-6 hours it would take to write it yourself for most issues, with more tests and better documentation when you are finished.

When you first start using claude code, it feels like you are spending more time to get worse work out of it, but once you sort of build up the documentation/skills/tools it needs to be successful, it starts to pay dividends. Last week, I didn't open an IDE _once_ and I committed several thousands lines of code across 2 or 3 different internal projects. A lot of that was a major refactor (smaller files, smaller function sizes, making things more DRY) that I had been putting off for months.

Claude itself made a huge list of suggestions, which I knocked back to about 8 or 10, it opened a tracking issue in jira with small, tractable subtasks, then started knocking out one at a time, each of them being a fairly reviewable PR, with lots of test coverage (the tests had been built out over the previous several months of coding with cursor and claude that sort of mandated them to stop them from breaking functionality), etc.

I had a coworker and chatgpt estimate how long the issue would take if they had to do it without AI. The coworker looked at the code base and said "two weeks". Both claude and chat GPT estimate somewhere in the 6-8 weeks range (which I thought was a wild over estimate, even without AI). Claude code knocked the whole thing out in 8 hours.

ChatGPT has 800 million monthly users. The fraction of those who are comfortable opening a terminal and running those commands is pretty tiny.

I think this is missing the point, These are tools that enable the LLM to do things that humans can do easily.

It stops an LLM from being blocked by the inability to do this thing. Removing this barrier might enable the LLM to complete a task that would be considerable work for a human.

For instance, identifying which files are PNG files containing pictures of birds, regardless of filename, presence or absence of suffix. An image handling LLM can identify if an image is of a bird much more easily than it could determine that an arbitrary file is a png. They can probably still do it, wasting a lot of tokens along the way, but using a few commands to determine which files to even bother looking at as images means the LLM can do what it is good at.

I disagree, in my opinion it's the exact same process, just on a much smaller scale. It's a problem, and we humans are good at solving problems. That is, until LLMs arrived, now we are supposed to become good at prompting, or something.

Hmm.. what's this?

> gmail (read-only) # gmail.search_email_ids → any # > Description: Search Gmail message IDs by query/tags (read-only).

Chat GPT App on android disavows having this... In what context does chat GPT get (read) access to Gmail? Desktop app?