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15 contributions to Clief Notes
Sneak Peak at the platform we are building
This is a devlog from David! A lot of people are saying they want the ability to scale and deploy their ICM and their workflows. We looked at all the possible problems security issues and we have been spending a lot of time building something for all of you! It's almost ready for release, but here's a little developers log to kind of check out some things that David has been doing to build it up. It's far from perfect, but for those technical folks out there you may enjoy it!
1 like • 2d
bazinga
Heard, Your voice understood.
All my life I've struggled with a speech impediment. I've had a hard time being understood by people, and somtimes by machines as well. So i started on a new project im calling Heard. Heard is a communication app with a integrated keyboard that can be set as any users default on their mobile device. Heard is designed to adapt to the user instead of expecting the user to adapt to it. It includes live captions, natural voice tools, a speech-practice mode for kids, and accessibility features for Deaf and hard-of-hearing users. Privacy is a core part of the project. Everything is designed to run locally whenever possible, allowing users to keep control of their own data. What started as a personal project has grown into something much bigger than I originally imagined. I'm continuing to develop it and plan to open source it so the community can help improve it and make it available to more people. I'd love to hear feedback from developers, accessibility advocates, speech therapists, parents, educators, and anyone interested in communication technology. Heard — Your voice, understood.
Heard, Your voice understood.
2 likes • 2d
Great idea and implementation!
I built a custom browser extension to browse CliefNotes
Browsing on Skool can be a bit overwhelming with it's UI (my eyes need a dark theme) and the great volume of stuff on CliefNotes makes jumping in daunting, especially if you're away for more than a day, so I wanted something that made browsing feel effortless and easier to navigate and see things and keep posts around that I wanted to dig into a bit more. So I built a browser extension that gives me a faster, cleaner view over the same Skool feed, posts, and comments. The catch: I don't know web code. I don't know APIs. But I've learned that knowing what I *don't* know is exactly where AI earns its keep. I know how to troubleshoot — so I can tell it what's happening, what's breaking, what information I need next — and it hands me the technical roadmap I don't have. I wasn't writing this thing so much as steering it. The part that nearly broke me was comments. A post with over 100 replies would render only 50, and I couldn't see why — Claude almost threw in the towel but I persisted because one thing I've learned working Game Dev is that if you can see something on the screen then that data exsists somewhere, you just have to figure out where to look. The takeway I want to flag is to think about pointing AI at your pain points, the best things to come out of using ai for me have been asking "What if?" And a lot of the amazing things people have created in here follow the same pattern. I also want to highlight this post by @Jason Jennings : https://www.skool.com/cliefnotes/sortable-posts-clief-notes-sidebar-easy-copypaste I was in the middle of my build when I came across it and I folded some of the sorting options into the extension because I thought they were great I built it to be shared — open source, free, and I'll keep updating as I go, genuinely open to suggestions. Only caveat is it can only do what Skool's API allows. Also I use Firefox mainly and it's easier to sign a native browser extension for firefox so you can install directly using the .xpi link in my repo, for Chrome you'll have to download the .zip and in Chrome set it to developer mode and you can sideload an unpacked extension (instructions should also be in the zip).
I built a custom browser extension to browse CliefNotes
2 likes • 2d
very nice. what tool do you use for the screen capture/recording?
Added Wikipedia-Like Read | Edit | History| Talk to my obsidian vault
I have built a web-based dashboard for my vault, so I built an interface just like mediawiki to view, edit, and track changes/history of ALL my vault files. I track all changes via git, and really like to know the history of who changed what when and why. It works just like mediawiki now. The .md files stay .md and the agent doesn't have to read extra meta data, that is all kept separate and attached at assembly on the web side. The talk page is where i can send prompts specific to that page to my agent and track the conversation.
Added Wikipedia-Like Read | Edit | History| Talk to my obsidian vault
0 likes • 3d
@Patrice Roatan Quebecois Thanks. but your AI generated autoreplies are really starting to bother me. The main problem I have with your auto replies is 1) they are lavish and artificial sounding. 2) they just repackage what I already wrote. I already know what I wrote. 3) there is nothing constructive that I can take away from it to better myself, so I feel like I am wasting my time reading your comments. Can I ask you, what is your purpose for doing this? To game the system to get more points? To show technical prowess? Good Job, mission accomplished. To have real engagement? well, it has worked until now, but I'm done with engaging with these replies.
How I measure my Session Health
my Live Health Stream is a real-time telemetry dashboard designed to monitor the "cognitive load" and operational stability of autonomous AI agents across different sessions and models (e.g., Gemini 3.1 Pro, Claude Sonnet 4.6). I am using both AntiGravity and Claude Code. They write to my obsidian vault, and my dashboard is a HTML/CSS version of that data along with python scripts that aggregate my json data for metrics I want to measure. Tool Error Rate % (Red Line) - What it is: The frequency at which the agent is failing to execute its tools properly (e.g., syntax errors, bad file paths). - How it’s calculated: (Failed Tool Calls / Total Tool Calls in the session) * 100. Notice on the graph how the red line spikes almost immediately after the green saturation line peaks. Context Saturation % (Green Line) - What it is: A measure of how "full" the agent's brain is getting. - How it’s calculated: (Total Input Tokens / Model's Maximum Context Window) * 100. If this hits 100%, the agent starts forgetting earlier instructions (context eviction). Lessons Learned (Yellow Bars) - What it is: The number of times an agent gets caught in a recursive failure loop (trying the exact same failed action over and over). - How it’s calculated: Programmatically tracked by analyzing the execution log for identical, sequential failed tool calls within a single session. I have a "Lessons Learned" log that I have my agents read on boot, and then if they **** up they have to record a lesson there, and update the .json file for that session where i build this graph from. Input/Output Tokens (Blue/Purple bars) Since this is not exposed I have to do an estimate: "input_tokens": input_bytes // 4, "output_tokens": output_bytes // 4, One of my core philosophies is No Vanity Metrics, and another is Things that are Measured Improve, and Ultimately, The Most Important Things Cannot Be Measured.
How I measure my Session Health
1 like • 3d
@Mira Bradshaw thank you. Do you currently measure anything from your agents or workflow?
1 like • 3d
@Petko Elenkin i have a .py read the agent's session file and write to a different one that is my longitudinal data.
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Peder Halseide
4
79points to level up
@peder-halseide-4329
Use my second brain to create real things in the real world and to have difficult conversations. I build caskets, I run, and I lead workshops. 7 kids.

Active 2d ago
Joined Jun 17, 2026
INTJ
Fort Collins CO
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