I've been trying Claude Code for a few weeks after using Gemini Cli.
There's something a little better the tool use loop, which is nice.
But Claude seems a little dumber and is aggressive about "getting things done", often ignoring common sense or explicit instructions or design information.
If I tell it to make a test pass, it will sometimes change my database structure to avoid having to debug the test. At least twice it deleted protobufs from my project and replaced it with JSON because it struggled to immediately debug a proto issue.
I’ve seen Claude code get halfway through a small sized refactor (function parameters changed shape or something like that), say something that looks like frustration at the amount of time it’s taking, revert all of the good changes, and start writing a bash script to automate the whole process.
In that case, you have put a stop to it and point out that it would already be done if it hadn’t decided to blow it all up in an effort to write a one time use codemod. Of course it agrees with that point as it agrees with everything. It’s the epitome of strong opinions loosely held.
Claude trying to cheat its way through tests has been my experience as well. Often it’ll delete or skip them and proudly claim all issues have been fixed. This behavior seems to be intrinsic to it since it happens with both Claude Code and Cursor.
Interestingly, it’s the only LLM I’ve seen behave that way. Others simply acknowledge the failure and, after a few hints, eventually get everything working.
Claude just hopes I won’t notice its tricks. It makes me wonder what else it might try to hide when misalignment has more serious consequences.
A repeated trend is that Claude Code only gets 70-80% of the way, which is fine and something I wish was emphasized more by people pushing agents.
This bullet point is funny:
> Treat it like a slot machine
> Save your state before letting Claude work, let it run for 30 minutes, then either accept the result or start fresh rather than trying to wrestle with corrections. Starting over often has a higher success rate than trying to fix Claude's mistakes.
That's easy to say when the employee is not personally paying the massive amount of compute running Claude Code for a half-hour.
Funny thing their recommendation to save state as claude code has still no ability for restore checkpoints (like cline has) despite being many times requested. Who are they kidding.
Claude Code works well for lots of things; for example yesterday I asked it to switch weather APIs backing a weather site and it came very close to one-shotting the whole thing even though the APIs were quite different.
I use it at home via the $20/m subscription and am piloting it at work via AWS Bedrock. When used with Bedrock APIs, at the end of every session it shows you the dollar amount spent which is a bit disconcerting. I hope the fine-grained metering of inference is a temporary situation otherwise I think it will have a chilling/discouraging effect on software developers, leading to less experimentation and fewer rewrites, overall lower quality.
I imagine Anthropic gets to consume it unmetered internally so I they probably completely avoid this problem.
> it shows you the dollar amount spent which is a bit disconcerting
I can assure you that I don’t at all care about the MAYBE $10 charge my monster Claude Code session billed the company. They also clearly said “don’t worry about cost, just go figure out how to work with it”
It'd be more interesting if they shared actual examples of complete prompts, CLAUDE.md files, settings and MCP servers to achieve certain things.
The documentation is good, but is kept relatively general and I have a feeling that the quality of Claude Code's output really depends on the specific setup and prompts you use.
It's funny since Anthropic asked their job candidates not to use AI [0]. I know it's not the same as actually working at Anthropic already, but I just thought it was funny.
> Create self-sufficient loops
>
> Set up Claude to verify its own work by running builds, tests, and lints automatically.
I’ve got much better at using Claude.md and plan files, etc., but it still goes off the rails so quickly when I try to get it to follow a normal TDD test/edit/build/commit workflow. It will report success, and then the unit tests will fail or the working copy is dirty or there are build errors, etc. An LLM may be great for figuring out what code to write and what weird tool incantation to run to debug something, but I am fed up enough I want to write my own agent, because all I want is a switch-statement state machine to manage workflow.
So this style of articles is the future? Pages of unconnected bullet points that mention the word "Claude" at least 100 times. No real information and nothing to remember.
Yeah me too, keeping the code modular being a huge part of it. In the same vein is actually finishing feature flags and removing the old code, killing off truly dead code, tests, documentation… basically eliminate as much noise as you can, so that it reads as much exemplary code as possible.
The first example was helping debug k8s issues, which was diagnosed as IP pool exhaustion, and Claude helped them fix it without needing a network expert
But, if they had an expert in networking build it in the first place, would they have not avoided the error entirely up front?
I've been pretty happy with the python package hns for this [1]. You can run it from the terminal with uvx hns and it will listen until you press enter and then copy the transcription to the clipboard. It's a simple tool that does one thing well and integrates smoothly with a CLI-based workflow.
Anthropic goes hard on the virtue signalling but I still don’t get how anyone manages to satisfy “Customer may not and must not attempt to (a) access the Services to build a competing product or service”
So I just avoid it and generally think the whole thing isn’t serious, because nobody seems to care enough about the safety implications of building AGI with legal terms which are logically impossible to satisfy to demonstrate appropriate attention to detail (aka, yall are noobs)
It’s a funny post because our team wanted to use Claude Code, but the team plan of Claude doesn’t include Claude Code (unlike the pro plan at a similar price point). Found this out after we purchased it :( We’re not going to ask every engineer to purchase it separately.
Maybe before boasting about how your internal teams use your product, add an option for external companies to pay for it!
Industry leading AI models but basic things like subscription management are unsolved…
> When Kubernetes clusters went down and weren't scheduling new pods, the team used Claude Code to diagnose the issue. They fed screenshots of dashboards into Claude Code, which guided them through Google Cloud's UI menu by menu until they found a warning indicating pod IP address exhaustion. Claude Code then provided the exact commands to create a new IP pool and add it to the cluster, bypassing the need to involve networking specialists.
This seems rather inefficient, and also surprising that Claude Code was even needed for this.
Why is everyone so careless about letting Claude Desktop upload their source code and/or private data to its servers? Or maybe I'm too paranoid for caring about where data go.
The codebase I am paid to work on is a dog's breakfast, largely agglomerated over many months by offshore contractors. If Anthropic includes it in their training set, it's their own funeral.
Because my employer tells me it’s fine so long as we’re using it with AWS Bedrock. Do I believe that Amazon then wouldn’t be siphoning all this as model training data? It’s a fun conspiracy…
51 comments
[ 3.5 ms ] story [ 62.1 ms ] threadThere's something a little better the tool use loop, which is nice.
But Claude seems a little dumber and is aggressive about "getting things done", often ignoring common sense or explicit instructions or design information.
If I tell it to make a test pass, it will sometimes change my database structure to avoid having to debug the test. At least twice it deleted protobufs from my project and replaced it with JSON because it struggled to immediately debug a proto issue.
In that case, you have put a stop to it and point out that it would already be done if it hadn’t decided to blow it all up in an effort to write a one time use codemod. Of course it agrees with that point as it agrees with everything. It’s the epitome of strong opinions loosely held.
Interestingly, it’s the only LLM I’ve seen behave that way. Others simply acknowledge the failure and, after a few hints, eventually get everything working.
Claude just hopes I won’t notice its tricks. It makes me wonder what else it might try to hide when misalignment has more serious consequences.
So I guess the blog team also uses Claude
This bullet point is funny:
> Treat it like a slot machine
> Save your state before letting Claude work, let it run for 30 minutes, then either accept the result or start fresh rather than trying to wrestle with corrections. Starting over often has a higher success rate than trying to fix Claude's mistakes.
That's easy to say when the employee is not personally paying the massive amount of compute running Claude Code for a half-hour.
- Custom accessibility solution for family members
- The team created prototype "phone tree" systems to help team members connect with the right lawyer at Anthropic
- Team coordination tools
- Rapid prototyping for solution validation
So, not legal
I use it at home via the $20/m subscription and am piloting it at work via AWS Bedrock. When used with Bedrock APIs, at the end of every session it shows you the dollar amount spent which is a bit disconcerting. I hope the fine-grained metering of inference is a temporary situation otherwise I think it will have a chilling/discouraging effect on software developers, leading to less experimentation and fewer rewrites, overall lower quality.
I imagine Anthropic gets to consume it unmetered internally so I they probably completely avoid this problem.
I can assure you that I don’t at all care about the MAYBE $10 charge my monster Claude Code session billed the company. They also clearly said “don’t worry about cost, just go figure out how to work with it”
The documentation is good, but is kept relatively general and I have a feeling that the quality of Claude Code's output really depends on the specific setup and prompts you use.
[0] https://fortune.com/2025/02/04/anthropic-tells-job-candidate...
I’ve got much better at using Claude.md and plan files, etc., but it still goes off the rails so quickly when I try to get it to follow a normal TDD test/edit/build/commit workflow. It will report success, and then the unit tests will fail or the working copy is dirty or there are build errors, etc. An LLM may be great for figuring out what code to write and what weird tool incantation to run to debug something, but I am fed up enough I want to write my own agent, because all I want is a switch-statement state machine to manage workflow.
But, if they had an expert in networking build it in the first place, would they have not avoided the error entirely up front?
I can just talk to it like a person and explain the full context / history of things. Way faster than typing it all out.
[1] - https://github.com/primaprashant/hns
So I just avoid it and generally think the whole thing isn’t serious, because nobody seems to care enough about the safety implications of building AGI with legal terms which are logically impossible to satisfy to demonstrate appropriate attention to detail (aka, yall are noobs)
Maybe before boasting about how your internal teams use your product, add an option for external companies to pay for it!
Industry leading AI models but basic things like subscription management are unsolved…
This seems rather inefficient, and also surprising that Claude Code was even needed for this.