oldnewthing
One argument is that the AI "feature" is forward looking and can bring more customers into the platform. Agreed. And then what? They are also stuck on the resiliency feature right?
The problem with every platform team is that, impact is hard to nail down. Does X using your platform Y to generate revenue mean your platform Y has indirect impact same as X? Most companies don't think so and end up destaffing their platform teams. Until, the destaffing ends up in much more inefficiency because everyone is inventing their own crooked wheel, spending time on the same capabilities and detracting from product development.
For context, I use Claude and Codex (side projects, Max and Pro plans respectively) and Gemini at work.
The key takeaway I have is: These tools have let me climb up the value chain ladder.
Even with Claude (Max plan, Opus 4.8, High Effort), it makes tons of mistakes, assumes a lot, misses nuance and doesn't really think through every aspect of the problem from every angle. Limited memory, lack of full context and a lack of experience with real world distributed systems means that the initial solutions they offer need a lot of iteration and refinement. Just like any junior engineer would need to do.
So, you might feel that with a LLM, "this should just be an hour" but it usually becomes a 2-week exercise for me.
Which brings me to what I tell my team repeatedly: "the only person with the big picture is you." I ask them to focus on thinking, ideating, refining. Do quick PoCs, talk to customers, discern what they are trying to achive, and what you can do to solve those problems. Work with Gemini (we can only use Gemini at work) to iterate until you are comfortable with the full solution end to end with all the nuances. Then let the agent code.
This moves you up the value chain from being a programmer to a problem solver. That's what software engineering has always been about: solving problems. Don't be discouraged. In fact, I am having more fun, am more energized and loving my craft even more now with LLMs. I am able to write down my thoughts, iterate on them and create a one-pager for ideas fast and get them to my team for them to think about. Sure, probably half of them we discard because it's usually not a "now" problem but we put that in our backlog to dust off when the first customer asks for it.
export CLAUDE_CODE_MAX_OUTPUT_TOKENS=64000 export MAX_THINKING_TOKENS=31999 export DISABLE_AUTOUPDATER=1 export CLAUDE_CODE_DISABLE_ADAPTIVE_THINKING=1
"effortLevel": "high",
"autoUpdatesChannel": "stable",
"minimumVersion": "2.1.34",
"env": {
"DISABLE_AUTOUPDATER": 1,
"CLAUDE_CODE_DISABLE_ADAPTIVE_THINKING": 1
}
I also had to:1. Nuke all other versions within /.local/share/claude/versions/ except 2.1.34. 2. Link ~/.local/bin/claude to claude -> ~/.local/share/claude/versions/2.1.34
This seems to have fixed my running out of quota issues quickly problems. I have periods of intense use (nights, weekends) and no use (day job). Before these changes, I was running out of quota rather quickly. I am on the same 100$ plan.
I am not sure adaptive thinking setting is relevant for this version but in the future that will help once they fix all the quota & cache issues. Seriously thinking about switching to Codex though. Gemini is far behind from what I have tried so far.
Show HN: Agent Instructions and Bootstrap Components
Hello,We started using AI tools intensively about 1.5 years ago. Initially, we used Gemini and Claude for creating specifications, generating concept mocks and UI mocks. That was an OK experience. Then we subscribed to Claude Code (Pro plan) and started building applications. Quite quickly, we realized that Claude (or Gemini or Codex) are quite adept at creating a lot of code quickly but they...
I have found that the initial specs only go so far; as I use, "what's missing" becomes clearer.
Workflow is build -> checkin to git -> build container -> deploy to Cloud Run. I have a number of instructions for Claude for logs, frontend, backend, logging etc. based on my past experience. Note that I am mostly a backend developer (AWS, Azure, GCP); I can't code frontend to save my life and on that front, the agents are helping me realize ideas rapidly.
1) Software Engineers should follow structured processes and methods to solve problems. They might look different: state charts, sequence diagrams, formal methods, SDLC etc. However, they often don't because expediency wins over correctness. Where it does matter such as process control systems, embedded systems, they do follow these processes rigorously.
2) That said, there are a lot of folks who may not be aware of these methods because they didn't receive formal training. That is the beauty of our field; you don't need somebody to certify you if you can invent solutions and solve problems. I will refer you to what happened to the author of strongtowns.org. https://www.strongtowns.org/journal/2023/1/30/lawsuit-update.... So, no, I beg to differ. We don't need a board of wise old men lording it over the rest of us.
3) We are conversing on, reading the article via, accessing content over the Internet. This is public infrastructure. Without the software engineers who invented/built BGP, TCP/IP, SNMP, etc., we would not be able to do this.
http://www.bitsavers.org/components/intel/80386/231499-001_8...