Hey folks, Im feeling that since gpt 5.6 came out that ive got a lot less effective. 2 months ago with claude sonnet i stated my goal and told what i wanted and got the outcome more or less straight away. Now im finding myself spending time stating and refining my goal, slicing the goal in small tickets and it feels like im not making progress at all. Anyone else having the same experience?

Happy to be here

Hey guys, I'm not sure if this has been talked about in here before but I found this alternative to ElevenLabs in GitHub , I'm aware several people here already use ElevenLabs so just dropping this here if it helps

Built a live website for my band with Claude Code and GitHub Pages, and the thing that stuck with me was how much the planning mattered more than the coding. I started with the Github... https://jdvanleenen-sys.github.io/machine-gun-rabbit/ Then got a domain... Optimized using @Ry Mac methods... Now live! www.machinegunrabbit.com It's a one-page site for Machine Gun Rabbit, my band out of Calgary (party band, From ABBA to AC/DC...). It's for people who catch a show or find us on Instagram: it shows where we play, the set, the band, and points them to follow or book us. Biggest takeaway: the win wasn't speed, it was locking the brand before building. I had a real brand guide done first, so when Claude Code built the site it matched the band instead of guessing. Deploying from the terminal was also simpler than I expected. New repo, push, flip on GitHub Pages, live URL in about a minute. Because the asset paths were relative, the CSS didn't break on the live site the way it can.

Hi friends, thank you all for the great community that exists here and to Jake for taking the initiative to set it up. The Backstory (Not essential) I am not a computer or technical worker, but I've been interested in AI driven uses for the past year or so. Initially, I started in Claude Projects. My goal was to make a tool that was full of various context for my life and work, so that the questions I asked and things I was thinking through were always based in my own personal situation. I mainly use this for goal setting and planning. Eventually, it began to hallucinate, and I rebuilt the project, still in Claude, in a different format. It worked well also for a while. The failure points often centered around the release of a new law, and so I figured that there was something going on there because nothing had actually changed in the workings of the project. After that, I shifted to PAI, as it was called at the time, and LifeOS, as it was billed as the exact thing I was looking for. I used and really enjoyed release version 5, but versions 6 and 7 have not been as good to use. I think part of this is due to the shift from Opus model implementation from v4.6 to v5. It also burned a ton of tokens. I had been keeping an eye on ICM and used very simple structures and systems of my own for local projects. The LifeOS project itself was a more complicated version of ICM, or at least a tangent derived from it. The Question Many of the examples and use cases for these ICM structures that are discussed here are focused on producing actual work and deliverables. Does anyone have an example of how they have used it or seen it used for a personal information and planning system? The Followup How much context is actually necessary for good output to be received? For example, in a build for a customer, how much detail about the company and the work they are doing goes into the setup? How much of that is relevant for the ICM to reference and understand as it is working through the material outputs? In my head, I've been told and understood that having a better background helped produce better results, but context windows can only be so large. Where is the trade-off between the AI having no outside context, some outside context, or lots of outside context as it relates to output quality?