Quick context: I'm the technical co-founder at an AI focus-group moderation startup (voice-based, live multi-participant — think a research platform, not a chatbot). This is actually my first hands-on build. I spent 15+ years as a Petroleum Engineer before doing a Master's in Applied AI, and while the program was great for the ML/AI side, it didn't cover much in the way of software engineering fundamentals or system design — so a lot of this is me learning architecture by doing, in real time, on a live product. I've been heads-down on the actual moderation engine (LiveKit + STT/TTS + an AI avatar) and just finished a client-facing frontend for my non-technical co-founders using Claude Design. Now I'm at the classic solo-founder fork: the frontend looks real, the backend (FastAPI + Postgres) is running but mostly unwired, and I'm trying to figure out the right order of operations before I just start bolting things together. Specifically wrestling with: 1. Auth-first vs. feature-first. Nothing downstream — user records, engagement data, analytics — means anything until real auth exists. Feels obvious in hindsight, but it means the "foundation" work is invisible to stakeholders who just want to see features ship. 2. What to actually track. I want to know where users drop off in a multi-step workflow (signup → contract → study setup → audience → instrument → session → report) without over-engineering a custom analytics stack before I even have real users. Self-hosted PostHog vs. just a Postgres events table vs. something else? 3. How much "systems design" to front-load. I'm working through Designing Data-Intensive Applications and the System Design Interview books to make better architecture calls now instead of paying for them later — but at 10 hrs/week solo, I can't read either cover to cover before shipping. Curious how others have picked their battles here (I landed on: data modeling + transactions + event/stream processing chapters now, replication/partitioning/consensus later).

Last night I built a cyberpunk coding game with Kimi K3 (prompt below) (sponsored video coming to my YouTube channel next week. this post is not sponsored) Here's what you should know about K3: - 2.8T parameter open weights model (largest ever) - 1 million token context window - Openly published architecture (kimi delta attention, attention residuals, etc..) The game ended up being pretty fun, so I wanted to share it. You can skip to the second half of the video to see me demo it. I used kimi code for this. Very capable agent harness and fun to use. I basically one-shotted the game. The secret was to include "Godot 4" in the prompt. That's the game engine I used. I've attached the full prompt if you want to check it out!

I joined

I made this so I can run commands in the terminal with less copy and pasting https://github.com/zazencodes/aicmd I'm looking for early users to test it out. Please help me out guys! 1. give the repo a star on GitHub ⭐ (thank youuuuuu) 2. install it and try it out curl -fsSL https://github.com/zazencodes/aicmd/raw/refs/heads/main/install.sh | sh I built this for myself and it works great on my system but I need your feedback It works with ollama, llama.cpp, APIs (openai, claude, gemini) and CLIs (codex, claude code, antigravity)

I feel like there’s so much waste right now when I’m using something like openclaw to do a very simple specific task. For example I’ll get it to “add a quote “ to my quote collection in Obsidian Or to “add an expense” to my bookkeeping system These should be specialized workflow-oriented agents. I think I could easily spin up an app with a pi backend system to do this. Might make it into a course. What do you think? Would you be interested? Also let me know if you have (a) advice or (b) questions