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AI Developer Accelerator

9.9k members • Free

7 contributions to AI Developer Accelerator
Who needs sleep when it's launch day!?!?!?!
Guys! I'm so excited! 15 more hours till shipkit.ai officially goes live! I'm doing a final round of tests just to make sure that every template works perfect for you! So far, everything is going smooth as butter! If you're thinking about building your own AI application for your own start or to start AI freelancing, shipkit is perfect for you. You are going to be blown away with how easy it is to setup, build, and deploy your own AI application. Over 150 developers have signed up for the prelaunch to jump start their AI Development journey! We'd love to have you as a part of the shipkit fam! Make sure you don't miss out on the $100 prelaunch discount that goes away as soon as shipkit launches here in 15 hours! You can grab shipkit here: 👉 https://shipkit.ai
Who needs sleep when it's launch day!?!?!?!
2 likes • 4h
@Brandon Hancock I think this awesome project begs for a bit of gamification, why not have a little friendly challenge amongst the early adopters to post their first shipkit built application and the community vote for the top pick?
🤔 Quick poll…
Do you find it easier to explain AI with words or by showing visuals?
0 likes • 24d
I always prefer to use AI to explain AI. I provide AI the information I want to communicate and let it structure it for which ever audience I target. After I always like to inform my public that the explanation they just receive was co-created with AI to strengthen the point.
Ruler: move your rules between AI coding assitants
I have been kicking the tires on a few different coding agents, but it's a pain to move the rules around. This utility is super handy for that: https://github.com/intellectronica/ruler Supports: - Github Copilotf - Cursor - Windsurf - Claude Code - Jules - Kilo - Aider And on and on and on. You can can make a global starter config to easily create global rules for all projects, and populate them into your project with `ruler init --global`
0 likes • Aug 12
Thank you this is awesome.
Fun use case for OpenAI Agent
I asked OpenAI Agent the following question: "Based at everything you know about me, browse all the thread in the community "https://www.skool.com/ai-developer-accelerator" and list the top 10 I could be able to participate something interesting and propose what I would reply (but DO NOT POST ANYTHING YOURSELF) just propose what I could post." After 10 minutes here is the result: "Understood. I’ll explore the community at https://www.skool.com/ai-developer-accelerator to identify the top 10 discussion threads where your expertise might add value and prepare proposed responses for you. I’ll not post anything without your confirmation. I’ll begin by accessing the site and reviewing the threads. Here are ten discussion threads from the AI Developer Accelerator community that align well with your interests in AI architecture, new tools and pragmatic development. For each, I’ve included a short description and a suggested angle for your reply. # Thread (with context) Why it might interest you & proposed contribution 1 Gemini CLI: Free Coding Agent – Real World Coding Test & First Impressions – Brandon Hancock reviews Google’s new Gemini CLI, a free coding agent you can run entirely in the terminal and puts it through several real‑world coding challenges. As someone who experiments with new AI tooling, you could share your own impressions of Gemini CLI. Perhaps mention how you measure its productivity gains versus tools like Cursor or Claude, any integration challenges you faced, and whether it lives up to the hype in a professional workflow. 2 Kimi K2 is on par with OpenAI $20 models, but free – a community member shares that the new Kimi K2 model (with both chat and API versions) appears competitive with paid OpenAI models. Given your experience evaluating LLMs, you could discuss your tests of Kimi K2, highlighting strengths (e.g., long‑context handling) and weaknesses compared with paid models. You might also mention latency or API reliability and how pricing factors into tool selection for proof‑of‑concept work.
1 like • Aug 6
@Shakur Abdullah I was trying to find a use case different then asking it to shop for me 😜What can I say, I like to shop for myself. But going through hundreds of messages on a discussion board, that I do not have time for, so here we go.
Exploring Agent Access Control with Identity Providers!
Hey everyone! 👋 Coming from a cybersecurity background (CIAM/IAM/PAM), I’ve been diving into the AI space and experimenting with secure access patterns for AI agents. Use Case: I'm exploring how to authorize AI agents at a fine-grained level using OAuth/OIDC-based identity providers like Auth0 The goal is to ensure that every tool or capability an agent uses is gated by specific scopes or permissions tied to the user's identity. Example: A user with the read: weather scope should only be able to access weather-related tools, while someone with write: finance can perform financial operations — all enforced at the token level during agent execution. Why This Matters: As AI agents become more powerful and autonomous, we need strong access boundaries ,just like in traditional microservices or APIs. I'm trying to bring those same identity-driven controls into the agent world. If you’re working on something similar or thinking about access control for AI systems, I’d love to connect, swap ideas, or just hear your thoughts.:)
2 likes • Aug 2
Hey! This is actually a really interesting problem - I've been thinking about similar patterns lately. You're spot on about bringing microservices-level security to AI agents. The thing that clicked for me is that MCP servers are basically just fancy API clients, right? So why not treat them like any other API client when it comes to auth? What I would be doing is handling the OAuth at the MCP server level. User gets their token with scopes (read:weather, write:finance, whatever), I would then pass that to the MCP server, and it just validates scopes before making downstream calls. The LLM doesn't even know about tokens - it just says "hey, get me the weather" and either the MCP server has permission or it doesn't. It's actually cleaner than I initially thought it would be. You get the same fine-grained control you're used to from microservices, but the LLM stays blissfully unaware of all the auth complexity. I was initially overthinking this and considering pre-configured environments and all sorts of complex patterns, but honestly? Just treat your MCP server like you'd treat any API gateway. Same OAuth flows, same scope validation, same patterns you already know. Have you started prototyping anything with Auth0 integration yet? I'm curious how you're planning to handle token refresh and session management on the agent side. The identity-driven controls you're talking about are definitely the right direction - we can't have agents running wild without proper boundaries!
1-7 of 7
Patrick Chouinard
3
39points to level up
@patrick-chouinard-8756
AI strategist & IT generalist building local LLM stacks, RAG chatbots & automation pipelines. Pragmatic, future-focused, and debate-ready.

Active 27m ago
Joined Jun 27, 2025
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