📝 SUMMARY This week's call was a small but packed session (Patrick Chouinard, Ty Wells and Juan Torres, with Shah Martinez joining later), with lower attendance due to a time change and the midterm. The group covered a lot of ground: tooling and agent setups (Ty's move to Duet as a "master agent controller", Patrick's continued use of T3 Code), Patrick's "AOE API meter" dashboard for tracking API spend, quotas and resets across providers, and Juan's WaveSpeed walkthrough with per-model tracking questions and a Minimax H3 360 Orbit LoRA demo, feeding his planned photo-to-3D-style-video pipeline for AI Boot Studio. Patrick shared his training-material automation and explained the enterprise constraints around resellers like WaveSpeed and fal.ai (hosting location, no data-retention rules, no responsibility insurance), plus his liability-driven rule that suppliers must pass full evaluation, currently pointing him to the hyperscalers, with tentative picks of an Azure OpenAI image model, Google's Gemini "Omni" for avatar video (not yet GA, so VEO3 for now) and 11Lab for voice. Ty demoed CallSitter, his hold-waiting callback app, and Patrick showed his rebuilt "Community Brain" meeting-recap app using LensDB, with Juan giving a job-search update and Biggi Fraley praising both demos in chat. 💡 KEY INSIGHTS Ty switched from T3 Code and CMUX to Duet as a "master agent controller". It worked for him because his infrastructure was already in place: he only had to expose two MCPs, one for incoming signals and one for actions that run other agents. He keeps a Claude remote-control session as a fallback. Ty moved to a "fleet" system built on GitHub Issues that manages multiple subscriptions, which let Duet fill his mobile gap. Patrick still likes T3, in particular its mobile remote features. Patrick's AOE API meter aggregates monthly spend, next payment, prepaid balance, next reset and alerts across providers, and projects when an allowance will run out. Examples: Tavily, expected to run out on Nov 30 with a Dec 1 reset; GitHub Actions minutes, projected by a simple estimate from real usage against an even-pace line.

AI Developer Accelerator — Coaching Call - November 03 VIEW RECORDING - 87 mins (No highlights) Meeting Purpose A casual sync on recent AI projects and development challenges. Key Takeaways - AOE API Meter: Patrick demoed a custom dashboard tracking API spend (Claude, GitHub, etc.) with predictive alerts for budget overages, enabling proactive cost management. - AI Training Pipeline: Patrick is building a pipeline to auto-generate training videos from changelogs, but corporate liability rules force a switch from flexible resellers (e.g., WaveSpeed) to hyperscalers (Google, Azure). - Callsitter App: Ty demoed Callsitter, a new app that waits on hold for users, inspired by a 3h 46m call. It charges $0.10/min (min. $2.49, max. $8.99) after a 15-minute wait. - Community Brain: Patrick rebuilt the meeting recap tool in-house, replacing N8N to gain full control over the multi-model pipeline and reduce processing time to ~15 minutes. Topics Corporate AI Adoption: Liability vs. Flexibility - Problem: Corporate AI adoption is blocked by liability concerns, forcing a trade-off between model flexibility and legal safety. - Patrick's Use Case: An automated pipeline for generating training videos. - Goal: Watch product changelogs → auto-update training materials. - Initial Stack: WaveSpeed, 11Labs, OpenRouter. - Blocker: Corporate policy prohibits resellers due to liability gaps (e.g., WaveSpeed's $100 liability cap).

Last week we watched a $6 AI avatar video, a six-day autonomous "Fable" run, and a Rust-based Adobe Fireworks clone — and somehow the biggest debate was whether one "monster" machine beats a cluster of smaller Proxmox nodes. (Patrick says: get a hybrid NAS and scale out.) If you missed it, you missed a lot — so let's make this week even better. 📞 HOW THE CALLS WORK The calls can run 2+ hours. We want to make sure we're respecting everyone's time. Especially those of you who actually show up. Here's the structure: 👉 Reply to this post with your questions before the call 👉 If you submit a question and you're on the call, you go first 👉 We work through questions in the order they came in 👉 Then we open it up for everyone else If you can't make the call but want your question answered, drop it in the comments. We'll get to it. But priority goes to people who are there. The goal is simple: if you're taking the time to show up, you shouldn't have to wait behind questions from people who aren't even on the call. Plenty of threads still open from last week: Brandon's digging into "Potato"-style smaller PR techniques and a possible second Claude subscription, Paul's sharing his Blacksmith CI results after jumping ship from GitHub Actions, and Scott's still weighing whether Stack Sentinel becomes a SaaS (liability questions pending). If any of that sparks a question — or you've got your own — drop it below and we'll dig in together. 🔗 ZOOM LINK (save this) https://us06web.zoom.us/j/81995207847?pwd=Xe6u6LmIQOmCP5VTnOwWYjDBfZNKGB.1 📅 WHEN Tuesday November 3rd at 6PM ET Looking forward to seeing you on the call!

📝 SUMMARY This week's call packed an unusually wide range of member updates into one session. After some casual catch-up — including token-spend jokes and members comparing personal AI assistants like "Dot," "Hermes," and the newly-released "Duet" — Brandon Hancock led an extended infrastructure discussion on scaling parallel AI coding work-trees, covering compute, storage, and CI/CD cost bottlenecks (~$600/month in GitHub Actions) and trading ideas with Patrick Chouinard on NAS-based shared storage, multiple smaller Proxmox nodes, and hybrid NVMe-plus-spindle designs. The middle of the call turned into show-and-tell, with Patrick sharing an internal Claude "support skill" pipeline (97% opt-in in two weeks), a six-day autonomous "Fable" run, and a ~$6 AI avatar training video; Ty Wells, Paul Miller, Scott Rippey, and Juan Torres each demoed projects ranging from a Rust-based Adobe Fireworks clone to a "Stack Sentinel" monitoring app and a photo-booth AI image pipeline. Later segments covered Ryan C's rebuilt digital-signage business, Shakur Abdullah's CRM rebuild and FOIA/public-records workflow, a tip on reverse-engineering SaaS tools via GitHub, and a philosophical thread on AI-driven code review, before Brandon closed with an update that his company remains pre-revenue, awaiting acquisition or investment. 💡 KEY INSIGHTS Patrick Chouinard reported extreme token usage polarization among go-live users. He recommended separating storage on a shared NAS from compute on multiple smaller nodes rather than using one "monster" machine. Patrick built a FinOps dashboard spanning Claude, Codex, OpenAI API, Wavespeed, Tavily, 11Labs, FireCrawl, and GitHub. Patrick's agents use a base personality prompt nicknamed "Clara" and store API keys on a physical secret-manager server. Patrick uses Sonnet 5.5 for heavy transcript ingestion and GLM 5.3 Flash for cheap bulk chunk-processing. Brandon Hancock uses "Dot" as a co-pilot for managing GitHub issues, travel booking, and cancelling unused subscriptions.

🧠 THIS IS A BRANDON WEEK!!! 🧠 Last week, we debated whether self-hosted inference could ever beat a commercial API, and the consensus was surprisingly clear! If you missed the deep dive into VLLM vs. GPT-6, you missed some serious insights on where the real value lies in AI deployment. 📞 HOW THE CALLS WORK The calls can run 2+ hours. We want to make sure we're respecting everyone's time. Especially those of you who actually show up. Here's the structure: 👉 Reply to this post with your questions before the call 👉 If you submit a question and you're on the call, you go first 👉 We work through questions in the order they came in 👉 Then we open it up for everyone else If you can't make the call but want your question answered, drop it in the comments. We'll get to it. But priority goes to people who are there. The goal is simple: if you're taking the time to show up, you shouldn't have to wait behind questions from people who aren't even on the call. We still have some fascinating threads open, from Andrew's forensic psychiatry AI work to the practical application of decision models. Daniel is also preparing to share his Canadian AI governance guide, and Patrick is continuing to document his T3/Hermes orchestration architecture. Come discuss these next steps! 🔗 ZOOM LINK (save this) https://us06web.zoom.us/j/81995207847?pwd=Xe6u6LmIQOmCP5VTnOwWYjDBfZNKGB.1 📅 WHEN Tuesday October 27th at 6PM ET Looking forward to seeing you on the call!