@HaoStudioCC Yeah agree. I usually have iOS text replacement to reuse prompt , then at some point (when it becomes repetitive) move it to CI. But when you can over- engineer everything with one prompt it’s so tempting to automate for the sake of automation!!!
Repeating question in my head when I’m trying to setup my Mobile App development pipeline with AI was always should I automate with CI or just ask Claude Code do that thing.
This time it was marrying release job and release notes. I already have 2 separate jobs to write notes
almost 100% sure nothing will be lost in between, I can easily plug in release notes reviews (from other models).
And these 2 options today have the same price in terms of setting it up/building. But I think
Caught myself yesterday prompting Gemini to create script that I planned to run periodically to collect some data manually but then naturally proceeded to ask Gemini run it.
Now trying to decide how I leave this in my neural net as Laziness and degradation or Efficient behavior?
You’ve been putting off your e2e tests cause need to deliver feature code. Cutting corners on design doc to leave time for coding. Getting Code coverage to 90% is waste of time. Guess what now it’s more important cause coding time is won back.
WDYT?
As soon as your team really starts to adopt AI to write code you hit the wall of “more code than eye ball time” - engineers are overwhelmed with generated code. Code reviews started to be unfair, cause it’s generated.
IMO code is “disposable” asset now.
Cost of writing it is low, so it can be rewritten. Verification should become the most valuable part: against spec, against guidelines, constraints, against environment. As engineers we freed up our time from writing code to write proper verification pipelines and processes.
Is there a value in oneshooting a large complex task or should it be split immediately into lots of small ones?
Tried to oneshot a complex task with 3 pages PRD, my config limits Claude with 90 turns and job failed, so went asking Opus to play architect and subtask it.
Got me thinking would there be any benefit in one shooting it waving all limitations even hitting context window at some point, then probably get unsatisfying results. But then ask Claude to learn from output and only then subtasks it and execute.
Vibecoded in 1 hr of glm 5.2 and ClaudeCode from a single prompt.
Calisthenics coach right in your browser with local CV.
😮
Want a link to try? I’ll deploy quickly
Explore new paths for you and suggest them on Mondays. Claude will PROMPt YOU as an expert in field and ask permission to execute.
WDYT? Aren’t people ready and need to linger on micromanaging AI?
Claude Tag - new feature from Anthropic. Tag Claude in Slack to delegate work & it will execute - researching , breaking down to tasks , implement, raise PRs.
I have mixed feelings, on one hand it’s very useful & close to real workflow but on other it feels like wrong direction.
If it does why would it need your input, should not it be a “ProActive Employer” instead? Constantly researching problems that business is working with, proactively suggesting solutions (just cap amount of tokens to not be surprised with weekly bills)…