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Owned by Keith

TopOfMind AI Builders

541 members • Free

Formerly OpenClawBuilders. Practical AI systems with Hermes, OpenClaw, GoHighLevel, agent memory & automation that keep your business top of mind.

ABA-based basketball shooting program. 14 days. Measurable results. Data-driven coaching and community accountability.

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104 contributions to TopOfMind AI Builders
Question?
how are you structuring your AI coding setup? (sharing mine, want to compare notes) been deep in the weeds optimizing my coding stack lately and want to see how you guys are actually running yours. here's where I'm at: what I pay for - Ollama - ChatGPT / Codex - Claude Code ($100 plan) how I split it - manual coding sessions → Claude Code - my orchestration layer (I call it Hermes) → runs on Codex with an Ollama fallback the issue: I cap out on the $100 Claude plan fast. so lately I've been running fcc-claude (free-claude-code) — it keeps the Claude Code terminal workflow but lets you point it at whatever API you want. feels like working in Opus, but the model underneath is swappable. I rotate the backend between: - DeepSeek - MiniMax M3 - and lately Qwen3:30b fully local right now I'm routing local Qwen through Ollama into fcc-claude, so I'm basically running the Claude Code experience on my own hardware for free. for the workflow layer I lean on Superpowers + a few MCP connections, and that's pretty much it. so what I'm trying to figure out: - how are you structuring sessions — one main agent, or orchestration with subagents? - what's your model routing look like? mixing local + API like this, or all-in on one provider? - what are you running for the "framework" layer — superpowers, custom skills, raw prompts? - and real talk: what am I missing? where am I leaving gains on the table? drop your setup below, even a rough sketch. trying to make sure I'm actually maxing this out and not just stacking tools for the sake of it.
1 like • Jun 18
@Carlos Jimenez Great question. For me, the answer is: it depends on what I’m building and who I’m building it with. I use a mix of tools depending on the workflow: Rocket.new, Claude Code, Hermes, Codex, Replit, Base44, and Perplexity Computer. I don’t really think of them as “one tool to rule them all.” I think of them more like a production stack for different stages of building. For example, I’ve built custom agents and skills that let my non-technical, domain-expert business partner create apps without needing to understand the technical details. Then I set up the engineering side: GitHub workflows, unit tests, integration tests, functional tests, and QA checks so we’re not just generating demos — we’re trying to create something that can actually survive contact with users. A big part of my process comes from working at Amazon Web Services for 7 years. I bring in lessons from that environment around quality bars, production readiness, operational excellence, and customer obsession. So before I treat an AI-built app as “done,” I usually run it through things like: - Production readiness assessment - QA / quality bar review - Unit, integration, and functional testing - UX and UI audit - SEO audit - Security / reliability sanity checks - “Would a real customer trust this?” review The way I look at it: AI tools are great at helping you move fast, but the real advantage comes from pairing them with strong judgment, domain expertise, testing, and a high quality bar. As for as models, I have the $200/mo Claude Code, Codex and I prepaid a yer for perplexity computer. I use Codex via auth for OpenClaw and Hermes. I forgot to mention when I run my production readiness assessments I use codex to assess the other models. I use Claude Code when assessing codex code. I've really interested in OpenRouter fusion api to get Fable level of output. I'm in the process of going live with a sports app using the perplexity method. It's web base for now and I'm kicking off a private beta with 1 high school coach and two professional Canadian Football League customers.
AI Agents: Is Domain Knowledge the Real Bottleneck?
Keith, you mentioned that one of the biggest challenges with AI agents is getting enough domain knowledge to properly ground them. I'm curious how you're approaching that today. Are you mainly solving it by working closely with design partners and extracting workflows directly from business owners, or have you found other methods that work well? Also, you've been experimenting with alternatives to GHL and combining CRM capabilities with agentic workflows through Hermes. How are you thinking about the split between CRM automation and AI agents going forward? Would love to hear your thoughts since I think a lot of builders here are running into the same challenges.
1 like • Jun 4
Wow, you hit on a lot. Lets start with domain knowledge. Yes, I found you can gain domain knowledge from your past experience or select a co-founder with domain knowledge. You can partner with a potential customer that has the domain knowledge. Collaborate with them to build a MVP. You want leverage their domain knowledge to help you design a working MVP thaat solve a problem they have and by extension the niche. Even better find a leader in the niche that has an active following with at least 1k members. Then when you solve their problem interview them and place the interview on your socials and their socials. I'm sure you should be able to get at least 10 customers. I've done both. In my Complete Performance business, my co-founder is an certified professional, created CEUs for other professionals and mentor new certified professional,. We don't get a lot of customers yet, but he got invited to give a talk at an university and we were able to get a mentorship customer and a design partner for an app with are going live next month. My partner met a clinic owner and we were trying to sale him a website but after talking to him. He had an idea for an app for his 19k member instagram channel. We are doing a 50/50 deal on the app. His knowledge and mabual system and I will turn it into an app.
Why OpenClawBuilders is becoming TopOfMind AI Builders
OpenClawBuilders started as a place to help people make sense of OpenClaw, Moltbot, Claude, and AI automation tools. That is still part of the mission — but the bigger opportunity is practical AI implementation. The new direction is TopOfMind AI Builders: a community for founders, operators, and builders who want to turn tools like Hermes, OpenClaw, GoHighLevel, agent memory, and AI automation workflows into systems that actually create business leverage. This community will focus on: - secure AI agent setup - OpenClaw and Hermes workflows - GoHighLevel follow-up systems - business memory and agent context - reusable skills, prompts, and automations - content repurposing workflows - build reviews and quality gates - practical AI system audits and implementation help If you joined for OpenClaw or Hermes, you are still in the right place. The shift is that we are moving from tool setup to business systems. The goal is not more AI hype. The goal is building AI systems that keep your business, clients, and follow-up top of mind. Start by replying with: 1. What AI system are you trying to build? 2. Where are you stuck? 3. What would make this community immediately useful for you?
0 likes • Jun 2
@Damien Hooper I'm working on a few things I will share later this week.
Don't give up. I was completely lost (AI, Openclaw, etc) a few weeks ago.
Once I found my rhythm - I built this command center in just a few days. It literally runs by entire agency.
0 likes • May 23
Corey, this is exactly why I keep telling people not to quit in the messy middle. There’s always that phase where none of it makes sense yet. The tools feel disconnected, the prompts feel clunky, the workflows keep breaking, and it feels like everyone else “gets it” except you. Then something clicks. You find your rhythm, the pieces start connecting, and suddenly you’re not just playing with AI tools anymore. You’re building an operating system for your business. The fact that you went from feeling lost a few weeks ago to building a command center that runs your agency is a huge win. That’s the shift I want more people in here to experience: Not “I learned another AI tool.” But “I built something that actually gives me leverage in my business.” Great work. Keep documenting what you’re building. That’s going to help a lot of people in here. Keith
Business owners don’t buy AI. They buy business outcomes.
One thing I keep coming back to: Most business owners don’t really care about the tech at first. They don’t wake up thinking, “I need an AI automation stack.” They wake up thinking: “I’m buried.” “I’m missing follow-ups.” “My team keeps dropping the ball.” “I can’t keep everything in my head anymore.” “I need more time.” “I know we’re growing, but the backend is starting to break.” That’s the real sales conversation. AI, automation, agents, workflows, CRMs, integrations… all of that matters. But only because it should solve a business problem. If you lead with the tech, you make the owner do the translation. If you lead with the business outcome, they immediately understand why it matters. Example: Weak: “We can build an AI automation that updates your CRM and triggers a follow-up sequence.” Stronger: “We can make sure every new lead gets followed up with automatically, so fewer opportunities slip through the cracks and you don’t have to personally chase every conversation.” Same solution. Completely different conversation. The tech is the vehicle. The outcome is the sale. Once you help them save time, recover missed revenue, improve follow-up, reduce manual work, or get better visibility into the business, then they may want to understand how the system works. But in the beginning, they mostly want to know: “Can you solve the thing that’s slowing me down?” That’s the mindset shift I think every AI builder needs to make. Don’t sell AI. Sell time back. Sell fewer dropped balls. Sell cleaner handoffs. Sell more capacity. Sell the owner not being the bottleneck anymore. That’s where the value is. Question for the group: When you explain what you do, are you leading with the technology or the business problem you solve?
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Keith Motte
5
181 points to level up
@keith-motte-1173
IT Dude. AWS Engineering Manager focusing on helping enterprises utilize AI and Cloud to grow their business, Father and part time AI Agent Wrangler

Active 2d ago
Joined Jan 27, 2026
Temecula,Ca
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