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Build With AI episodes
- How to build a $10K/month AI consulting business in 90 days (step-by-step)
In this solo episode, I walk through the exact offer I'm using to make over $1,000 an hour with AI consulting — the AI Concierge Offer — and break it down step by step so you can replicate it. I cover every piece of the infrastructure: the pre-call intake form I built in Jotform, the two 45-minute done-with-you strategy calls every month, the Voxer access setup with a real SLA, and the Notion documentation hub that tracks every automation we build together. I also show you how two Claude skills handle all my post-call follow-up in 30 seconds flat, and walk through exactly how I price this — from $1,000 a month to start, all the way up to where I'm at now at $2,000 a month with a 100% close rate. By the end of this episode, you'll have a complete blueprint to go build your own AI consulting business and land your first paying clients.
https://link.excalidraw.com/l/4z8Z2Lyybfg/8E8aGK6n25PTimestamps
00:00 – Making over $1,000/hour with the AI Concierge Offer
01:40 – The pre-call intake form built in Jotform
03:40 – The two 45-minute done-with-you strategy calls
04:30 – The AOA framework: Audit, Optimize, Automate
06:00 – Voxer access and the 12-hour SLA
08:00 – The Notion documentation hub walkthrough
09:56 – How two Claude skills automate post-call follow-up
12:15 – Pricing: from $1,000 to $2,000/month and when to raise rates
14:23 – How to get the full templates and business model
Key Points
The AI Concierge Offer is a done-with-you consulting engagement, not done-for-you. Two 45-minute strategy calls per month plus unlimited Voxer access — that's roughly 1.5 hours of your time per client at $1,500/month, which works out to $1,000 an hour.
The AOA framework — Audit, Optimize, Automate — is the operating system for every client engagement. You fix the process first before you ever touch automation, so you're not just automating broken workflows.
A pre-call Jotform intake questionnaire sent before the first paid call surfaces the client's biggest bottlenecks and makes the first session actually productive from minute one. If they haven't filled it out, reschedule — it's not optional.
The Notion documentation hub is the renewal mechanism. When clients can see a running quantified list of every skill, workflow, and automation you built together, the $1,500 or $2,000/month fee is easy for them to justify.
Two Claude skills handle all post-call admin in 30 seconds — one populates the Notion call log from the transcript, the other pulls out action items and drafts a follow-up email to the client. Build the infrastructure once and it runs itself.
When you're closing 100% of your sales calls, your price is too low. Start at $1,000/month, move to $1,500 once you have two clients, and keep raising until people push back. Corey is currently at $2,000/month and still closing every pitch.
Cap yourself at six clients. More than that and service quality degrades — and at $2,000/month, six clients is $12,000/month for roughly 9 hours of strategy call time.
Links Mentioned
AI Operator Academy — community with the full AI Concierge Offer business model, Jotform template, Notion hub template, and both Claude skills included: https://www.skool.com/aioperatoracademy/about
Voxer — walkie-talkie style async voice messaging app used for client communication between strategy calls: https://www.voxer.com
Jotform — form builder used to create the pre-call AI concierge intake questionnaire: https://www.jotform.com
FIND ME ON SOCIAL
X/Twitter: https://x.com/coreyganim
Instagram: https://www.instagram.com/coreyganim/
LinkedIn: https://www.linkedin.com/in/coreyganim/
YouTube: https://www.youtube.com/@coreyganim
16 min - I built an AI agent finance department (full build)I brought on Mike Dion, a senior corporate finance professional who has helped automate more than 100,000 hours of work out of finance processes, to walk through how to build a fully functional AI agent finance department inside N8n — from scratch, with no coding background required. We build a CFO agent named Charles, give him a team of specialist sub-agents (FP&A, Accounting, and Treasury), and watch the delegation logic in action as Charles routes questions to the right specialist instead of answering everything himself. Mike also breaks down how to use ChatGPT to write your own system prompts, why you should give the CFO a reasoning model while using cheaper models for the sub-agents, and how to publish the finished chat so your whole team can access it. By the end of this episode, you'll have everything you need to replicate this AI finance department in under 45 minutes.Timestamps00:00 – Intro00:03 – What we're building: AI CFO inside N8n00:23 – Mike's background and 100,000 hours of automation00:52 – Why N8n over Make, Zapier, or Power Automate02:00 – Setting up the chat trigger and naming the CFO05:00 – Using ChatGPT to write the CFO system prompt08:52 – Choosing the right AI model and saving on token costs13:27 – Building the FP&A sub-agent (and what FP&A actually does)16:36 – Adding the Accounting agent with code interpreter19:25 – Building the Treasury agent33:21 – Successful routing to FP&A and Treasury agents38:19 – Publishing the chat and embedding it in Slack, Teams, or a website39:22 – Mike's philosophy: train your team to build, don't just build for them41:14 – Where to find Mike and his free Finance Automation Insider newsletterKey PointsUsing ChatGPT to write your own N8n system prompts is one of the fastest ways to get started — nothing knows ChatGPT better than ChatGPT itself, and what would have taken six hours of writing two years ago now takes minutes.The delegation logic is non-negotiable. If the CFO answers questions directly instead of routing them to a specialist, you lose access to any tools or context you've connected to those specialist agents — and you pay more for it.N8n can run completely free on a $4–5/month virtual private server, making this entire AI finance department buildable for nearly zero cost. You don't need a paid automation platform subscription.Setting the context window to 10 (five back-and-forth interactions) is a practical default — enough for most finance questions without ballooning your API costs on every run.You can publish the finished CFO chat and embed it directly in Slack, Microsoft Teams, or a company website. Your team sees a clean chat interface — all the N8n complexity stays invisible in the background.Links:F9 Finance YouTube channel — Mike's free weekly channel covering finance automation tools and builds: https://www.youtube.com/@F9FinanceF9 Finance website — corporate automation training and the free Finance Automation Insider newsletter (includes 15 five-minute finance automations you can build with tools you already have): https://f9finance.comN8n — the free, self-hostable workflow automation tool used to build the AI CFO in this episode: https://n8n.ioJoin the Build With AI community — weekly AI implementations, live coaching, and no-fluff templates built for non-technical entrepreneurs: https://www.skool.com/buildwithai/aboutIf this episode was valuable to you, it would mean a lot if you left a rating and review on Apple Podcasts or Spotify. It helps more entrepreneurs find the show.FIND ME ON SOCIALX/Twitter: https://x.com/coreyganimInstagram: https://www.instagram.com/coreyganim/LinkedIn: https://www.linkedin.com/in/coreyganim/YouTube: https://www.youtube.com/@coreyganimFIND MIKE ON SOCIALYouTube: https://www.youtube.com/@F9FinanceWebsite: https://f9finance.com44 min
- AI agent focus groups are the future of marketing
I sat down with Justin Brooke, a 20-year advertising veteran who turned a $60 Google Ads campaign into a seven-figure agency — and then built an AI-powered prediction system that has since generated $260,000 for him personally. In this episode, Justin walks through his "predictive wear" framework: a multi-agent workflow that runs your ad copy and sales pages through a synthetic focus group of 13 detailed AI personas before a single dollar is spent on ads. We break down how the workflow is built in Mind Studio, why persona quality makes or breaks accuracy, and how Harvard, Stanford, and the New York Times have all validated this exact approach. By the end of this episode, you'll understand why running your marketing through a virtual focus group before it goes out the door may be the single highest-ROI move you can make right now.
Timestamps
03:29 – What "predictive wear" is and why Justin built it
05:00 – Why you need multiple personas, not just one
08:00 – How the 13-persona focus group workflow runs
09:00 – The prediction engine: picking the winning ad variation
10:00 – Harvard, Stanford, and the New York Times validate the method
13:15 – The ROI: $260K personally, 4 to 6X ROAS for clients
19:00 – What makes a persona accurate: the 1,400-word dossier
24:04 – The copywriter prompt and "embody" vs. "pretend to be"
33:00 – Sales page version: PDF upload and yes/no buyer scoring
41:00 – Why some personas are successful and others are struggling
45:00 – A $36,000 offer launched using this exact process
48:00 – Final advice: do the work on the persona qualityKey Points
The old way of advertising is learning by spending money — you write copy, run ads, and find out if it works after the budget is gone. Justin's predictive wear system flips this by running copy through a synthetic focus group of 13 AI personas before any ad spend, so you know what will convert before you go live.
Harvard, Stanford, and the New York Times have all independently validated this approach. The New York Times uses the same synthetic audience process to test headlines and found 92% accuracy compared to their human focus groups — meaning this is not a fringe experiment, it is becoming standard practice for major publishers and brands.
The cost is 13 to 20 cents per run. A top 1% copywriter charges $100 to $500 per ad. Justin's workflow produces three optimized variations in about 10 minutes for 13 cents, performs at or near the level of the best human copywriters for most use cases, and allows unlimited iteration — you run it until the copy converts.
The system is also a copywriting trainer. Even with 20 years of experience, Justin says the feedback regularly surfaces blind spots and teaches him better approaches.
Anyone can use this, not just expert copywriters. Because the workflow takes whatever you input — even a bad ad — and improves it based on real persona feedback, non-copywriters like a front-desk employee or a local business owner can now produce top-10% ad copy without prior training.Join the Build With AI community built for non-technical entrepreneurs: https://www.skool.com/buildwithai/about
If this episode was valuable to you, it would mean a lot if you left a rating and review on Apple Podcasts or Spotify. It helps more entrepreneurs find the show.
FIND ME ON SOCIAL
X/Twitter: https://x.com/coreyganim
Instagram: https://www.instagram.com/coreyganim/
LinkedIn: https://www.linkedin.com/in/coreyganim/
YouTube: https://www.youtube.com/@coreyganimFIND JUSTIN ON SOCIAL
https://x.com/IMJustinBrooke
Website: https://adskills.com51 min - I BLEW UP Instagram With AI Content (4M Views in 30 Days)I sat down with Nick Puru to break down the exact Claude Code setup he used to pull 4 million views and ~6,000 newsletter signups in the last 30-45 days for his AI consultancy. Nick walks through his short-form content factory inside Claude Code — the CLAUDE.md "brain," his ICP file (an avatar he calls Patrick), his foundations doc full of algorithm lessons like "negativity always wins," and the three skills he uses to write captions, generate scripts, and review them. We get into how he tests three hooks per video with Instagram trial reels, the humanizer skill from Bader on GitHub that strips out AI tells like em-dashes and "it's not X, it's Y," and why he treats every Claude project like onboarding a new employee. By the end of this episode, you'll have a clear blueprint for building your own short-form content system in Claude Code — starting from a single CLAUDE.md file and expanding from there.Timestamps00:00 – Intro00:37 – 4 million views in 30 days01:53 – Reels to ManyChat to newsletter funnel03:31 – Tour of the Claude Code folder structure05:02 – How the write script command works06:29 – Why human-in-the-loop matters for content07:38 – Inside the CLAUDE.md brain file08:11 – Meet Patrick, Nick's ICP avatar10:04 – Foundations file and "negativity always wins"13:43 – Live generating a Claude Cowork script15:44 – Testing three hooks with Instagram trial reels18:48 – Most bare-bones version to start with22:36 – Why ICP and brand voice are foundational24:28 – The humanizer skill from Bader on GitHub27:01 – Treating AI like a new employee29:35 – Context beats prompting in 202631:13 – Where to find NickKey PointsNick's short-form system drove ~4M views in 30 days and ~6,000 newsletter signups in 45 days for his AI consultancy — every video CTA pushes a lead magnet via a ManyChat flow that collects emails and hands off to an appointment setter.The whole system lives inside Claude Code as three skills: one writes scripts, one reviews them against a quality checklist, and one generates captions. Trigger them by typing things like "write script" in the terminal.The CLAUDE.md file is the brain. It holds the output format, writing rules, key principles, and a pointer to an ICP file built around an avatar named Patrick — a small-to-mid market business owner ($few hundred K to $15M, 2-50 staff) who has tried ChatGPT once or twice but doesn't know Claude Code.One of Nick's foundations is "negativity always wins" — the algorithm rewards a stronger emotional charge, but he warns against using it on every video or audiences pick up on it. He calls it in only when the angle fits.He tests three different hooks on the same body and CTA using Instagram trial reels, treats it like A/B testing titles and thumbnails on YouTube, and feeds the winners back into the system as analytics context.To kill AI tells like em-dashes, bullet points, and "it's not X, it's Y," Nick runs scripts through Bader's humanizer skill from GitHub. Corey adds a similar instruction in his agents.md to never use dashes.Treat Claude like a new employee, not a magic box. You wouldn't expect a hire to crush it on day one — you'd give them SOPs, business context, your website, and an ICP. Same playbook for building any Claude project, whether it's short-form, long-form, or LinkedIn posts.Bader's humanizer skill on GitHub - https://github.com/bader-researchManyChat for Instagram DM automation - https://manychat.comFIND ME ON SOCIALX/Twitter: https://x.com/coreyganimInstagram: https://www.instagram.com/coreyganim/LinkedIn: https://www.linkedin.com/in/coreyganim/YouTube: https://www.youtube.com/@coreyganimFIND NICK ON SOCIALYouTube: https://www.youtube.com/@nickpuruX: https://x.com/nickpuruLinkedIn: https://www.linkedin.com/in/nicholas-puruczky-113818198/33 min
- How I Built an AI Voice Agent With Claude + Voiceflow (Zero Code)Build your voice agent in 10 minutes (No code required)https://corey-ganim.kit.com/18da152cf4In this episode, I sat down with Susan Westwater, co-founder of Pragmatic Digital and a conversational AI veteran since 2017, to build a working voice agent in Voiceflow live, with zero code. Susan walks through her exact prompt template for an appointment-scheduling agent, explains the difference between in-the-loop, on-the-loop, and fully autonomous agents, and shows how to separate your agent instructions from your knowledge base so you can update facts without breaking the whole build. We test the agent live (it called her cell phone mid-episode), connect it to a Google Sheet to capture customer intake, and talk about competitors like VAPI, ElevenLabs, and Voiceify. By the end, you'll have the exact playbook (and the template Susan is giving away) to spin up your own MVP voice agent in under an hour.Timestamps03:42 – Inside Voiceflow and what makes it different04:23 – Chatbot vs voice agent: listen, decide, act05:30 – In the loop vs on the loop vs fully autonomous09:09 – The system prompt: identity, purpose, and boundaries11:54 – Voice, persona, and speech sculpting13:22 – Separating agent instructions from knowledge base17:14 – Stopping the agent from troubleshooting electrical issues20:31 – Rules for collecting info one question at a time23:21 – Pasting the prompt and one-shotting the build26:34 – Voiceflow competitors: VAPI, ElevenLabs, Voiceify30:22 – Connecting tools at each conversation step33:13 – Why faster builds give up control38:21 – Adding the knowledge base as a Word doc43:13 – Sending customer intake to a Google Sheet45:57 – Live phone call with the voice agent50:09 – Branching, exit conditions, and iteration54:52 – Custom voices, ElevenLabs integration, and voice securityKey PointsKeep two documents separate: agent instructions (how the agent behaves, its identity, persona, escalation rules) and knowledge base (the facts about your business). If pricing or hours change, you update one cell in your knowledge base instead of digging through a giant system prompt.The strength of a Voiceflow build lives in the prompt. Susan pastes her full instructions doc into the new project prompt and Voiceflow generates the entire conversation flow — greeting, qualification, intake, confirmation, escalation — with no coding.Be explicit about what the agent does NOT do. LLMs are trying to "win the game" (Susan's War Games analogy), so if you don't tell the electrical-appointment bot "do not troubleshoot," it will try to problem-solve its way out of every conversation.Collect intake one question at a time, use explicit confirmation on critical fields like callback numbers, and tell the agent to be empathetic but not apologetic — nobody wants a bot that says "I'm sorry" five times instead of solving the problem.Voiceflow — https://www.voiceflow.comPragmatic Digital — Susan's agency helping brands operationalize conversational AI and applied AI for CX - https://www.pragmatic.digitalVAPI — alternative voice agent platform - https://vapi.aiElevenLabs - https://elevenlabs.ioVoiceify — centralized library for chatbot, voice agent, and telephone deployments across web and mobile - https://voicify.com/Twilio — phone number and telephony layer for connecting Voiceflow agents to real phone calls - https://www.twilio.comMake.com — automation platform that can connect to Voiceflow as a tool integration - https://www.make.comRobert Scoble on X https://x.com/ScobleizerBrian Roemmele on X https://x.com/BrianRoemmeleFIND ME ON SOCIALX/Twitter: https://x.com/coreyganimInstagram: https://www.instagram.com/coreyganim/LinkedIn: https://www.linkedin.com/in/coreyganim/YouTube: https://www.youtube.com/@coreyganimFIND SUSAN ON SOCIALX: https://x.com/sjw75Website: https://www.pragmatic.digital1 hr
- I Built the ULTIMATE AI Second Brain (Karpathy's LLM Wiki Setup Guide)
🔗 Deploy your own Hermes agent on Hostinger -10% off any plan with code COREY10: http://hostinger.com/corey10 (use code COREY10)
Grab the free step-by-step Hermes Second Brain setup guide here: https://corey-ganim.kit.com/60fc0fe6d9
In this solo episode, I walk through exactly how I built the ultimate AI second brain using Hermes and its built-in LLM Wiki skill — inspired by Karpathy's wiki setup. I break down the three core operations of the Hermes agent (ingest, query, lint), the three layers of the knowledge base (raw sources, the wiki, schema/tags), and why I chose Hermes over Claude Code, OpenClaw, or Obsidian for this build. From there, I show the full one-click deploy on a Hostinger VPS, the OpenAI model setup, the Telegram bot integration via BotFather, and the Markdownload Chrome extension trick I use to feed any tweet, article, or webpage straight into the wiki. By the end of this episode, you'll have a clear, step-by-step path to deploy your own self-improving second brain that gets smarter the more you use it.Key Points
Hermes ships with a built-in LLM Wiki skill that handles the second brain function out of the box — your job is to curate sources, the agent's job is to summarize, tag, and file them away.
The knowledge base has exactly three layers: raw sources you give it (read-only), the agent-owned wiki of markdown files, and the schema/tags Hermes builds to make querying low-friction.
Run the Lint command roughly once a month — it audits your wiki for contradictions, sources older than 90 days, and oversized files that should be split for more accurate retrieval.
Deploy on a Hostinger VPS instead of locally — it's a one-click install with no terminal, cheaper than a Mac mini, always-on, and your data stays private.
The simplest workflow for feeding the wiki: use the Markdownload Chrome extension to clip any tweet, article, or webpage to markdown, drag it into your Telegram chat with Hermes, and tell it to add it to the wiki.
This is a compounding asset — on day 1 the knowledge base is the dumbest it'll ever be, but feed it consistently and by day 90 it becomes incredibly useful for retrieval.
Hermes agent VPS deployment on Hostinger (use code COREY10 for 10% off) - https://www.hostinger.com/vps/hermes-agent-hosting
Markdownload Chrome extension - https://chromewebstore.google.com/detail/markdownload-markdown-web/pcmpcfapbekmbjjkdalcgopdkipoggdi
Telegram BotFather - https://t.me/BotFather
OpenAI Codex - https://openai.com/codex
FIND ME ON SOCIAL X/Twitter: https://x.com/coreyganim Instagram: https://www.instagram.com/coreyganim/ LinkedIn: https://www.linkedin.com/in/coreyganim/ YouTube: https://www.youtube.com/@coreyganim
19 min - Cracking the X algorithm with Claude Code
Tom Crawshaw (8+ years in automations, $25M+ in attributed e-com revenue) cracks open the content system that's pulled him millions of views. We walk through the Claude Code skill he built that handles voice profile, copywriting principles, hook scoring, image prompts, and a humanizer pass from one slash command. He also surfaces a hidden Claude Code feature called /insights that audits your full usage history and tells you what to build next. You'll learn how to turn messy ChatGPT workflows into a real skill, why Whisperflow is non-negotiable, and the one slash command 99% of Claude Code users are sleeping on.
Timestamps
00:00 Intro
00:30 Tom's automation background
03:30 Skills vs. Projects on context
08:30 Auto-updating voice profile from X
11:00 Nano Banana plus Canva workflow
23:30 Live demo: a Whisperflow post
34:30 Hook scoring with copywriting principles
46:30 The hidden /insights command
54:30 Skills vs. n8n vs. Lovable
Key Points
Skills beat Claude Projects on context. Projects load every reference file on every message. A skill works like a book: Claude pulls only the chapter it needs, so a full pipeline runs in one chat.
Tom's skill auto-updates his voice profile weekly. The X API pulls his last 7 days of posts, ranks by engagement, and rewrites the profile so the skill keeps drifting toward what's working.
/insights is the most slept-on feature in Claude Code. It audits your full session history and hands back a real report: what's working, where you're breaking your own rules, skills to build, and prompts to run.
Image gen is 80% Nano Banana, 20% Canva. Generate fast in the AI tool, then finish in Canva with magic grab and magic erase.
Whisperflow changed how Tom and Corey think, not just type. Speaking forces tighter thinking and makes prompts richer because adding context costs almost nothing.
Links
Claude Code: https://www.anthropic.com/claude-code
Whisperflow: https://wisprflow.ai/
Nano Banana: https://gemini.google.com/
Canva: https://www.canva.com/
n8n: https://n8n.io/
Tom's site: https://learnn8nautomation.com/
Build With AI: https://www.skool.com/buildwithai/about
FIND ME ON SOCIAL
X: https://x.com/coreyganim
Instagram: https://www.instagram.com/coreyganim/
LinkedIn: https://www.linkedin.com/in/coreyganim/
YouTube: https://www.youtube.com/@coreyganim
TOM ON SOCIAL
X: https://x.com/TomCrawshaw01
YouTube: https://www.youtube.com/@TheAIGrowthLab
Website: https://learnn8nautomation.com/
58 min - How I'm AI-maxxing boomer businesses to make f*ck you moneyFree audit template Corey is giving away — https://audittemplate.aiIn this episode, I sat down with Chris Koerner and outlined how I sell AI assessments to small businesses.Timestamps00:00 – Intro00:33 – The $1,000 AI audit pitch01:10 – The lunch conversation that started it all02:23 – Why 99 out of 100 owners need this02:57 – Why Loom screen recording failed04:25 – From Zoom calls to a voice agent05:31 – Meet Annie, the AI interviewer06:17 – Live demo of the voice agent08:06 – How the voice agent was built (Retell + skills)10:18 – Walking through a real assessment in Gamma12:00 – The effort vs impact matrix13:00 – Wedding venue saves 8 hours with Dash This15:16 – Pricing journey: free to $1,00017:30 – Why charging more makes upsells easier18:02 – The full upsell menu breakdown22:00 – Custom GPT knowledge system for a business broker24:46 – Which industries this works best for25:53 – Seven ways to find clients with no followers26:39 – Hosting a local AI meetup27:30 – Door-knocking businesses in 202629:25 – Using free audits to land warm contacts30:30 – Running free AI office hours31:30 – Hard-won lessons and the speed-to-lead upsell34:36 – The simple Claude prompt that builds the audit35:33 – Where to find CoreyKey PointsThe business started from one lunch where a friend said he'd pay $1,000 just to be followed around for a day. After validating with 50–100 owners, Corey found 99 out of 100 small business owners need this — they just don't know which AI tools to use.The upsell menu is built into the report. Common follow-ons: process optimization ($3K–$5K), Zapier or Make automation builds ($1K–$3K), custom GPT knowledge systems, CRM setups (high-level CRM at $3K–$5K), and speed-to-lead AI agents tied directly to revenue.The seven-way client acquisition playbook works with zero followers: host a local AI meetup on Luma or Meetup.com, door-knock local businesses, run free audits for your network, host free AI office hours at coworking spaces or realtor offices, partner with well-connected locals, and lean on warm intros from your CEO peer group.You don't need to be an AI expert. As Corey puts it, you just need to be one step ahead of your average client — which is about seven days of studying. The realtor's office where he hosted his free AI meetup turned into paying assessment work.The Claude prompt to generate an audit is dead simple: attach the transcript, tell Claude to find off-the-shelf tools that fix the pain points, and point it at directories like Futurepedia or There's An AI For That.FIND ME ON SOCIALX/Twitter: https://x.com/coreyganimInstagram: https://www.instagram.com/coreyganim/LinkedIn: https://www.linkedin.com/in/coreyganim/YouTube: https://www.youtube.com/@coreyganim37 min
- EASY Claude Cowork Setup (full beginner tutorial)
In this solo episode, I walk through the exact process of setting up Claude Cowork from scratch — the right way — using the free Cowork Onboarding plugin I built and made open source. I go step by step through the full onboarding flow, from picking your workspace folder and connecting tools, to building three core context files (About Me, Brand Voice, and Working Style), generating global instructions that tie everything together, setting up scheduled tasks like a daily morning briefing and quarterly context review, and running an optional security review to lock in sensible rules.
Timestamps
00:00 – Why Cowork is useless out of the box
02:22 – Starting the onboarding flow from scratch
03:30 – Choosing workspace folder and onboarding path
04:37 – Workspace structure and file access permissions
05:45 – Connecting Google Workspace tools (Gmail, Drive, Calendar)
06:56 – Building context files: About Me, Brand Voice, Working Style
10:58 – Linking existing brand materials from Google Drive
12:44 – Generating global instructions from your context files
15:00 – Skills and plugin recommendations from the marketplace
17:24 – Setting up scheduled tasks: morning briefing and quarterly review
19:46 – Running the optional security review
23:23 – Wrapping up: what we built and the two manual steps left
Key Points
- Most people skip the onboarding and then wonder why Cowork feels generic. The entire point of setting it up properly — building context files and global instructions — is so Claude never has to ask who you are again. Every session loads with that context automatically.
- The three context files (About Me, Brand Voice, Working Style) are the foundation of the whole setup. Without them, Cowork is writing responses for a stranger. With them, it knows your business, how you communicate, and how you like your deliverables structured.
- Global instructions are the piece most people miss. Once you paste your generated global instructions into Cowork's settings, every single session loads that context from the start — no repeating yourself, no re-explaining your preferences.
Links Mentioned
Free Cowork Onboarding plugin — download it to run the full guided setup described in this episode: https://return-my-time.kit.com/f00d78554c
Build with AI community — get the full onboarding plugin including the self-assessment, workflow audit, and custom skill blueprints tailored to your business: https://www.skool.com/buildwithai/about
WisprFlow — the talk-to-text tool used during the onboarding to answer Claude's questions faster: https://wisprflow.ai
Find Me on Social
X/Twitter: https://x.com/coreyganim
Instagram: https://www.instagram.com/coreyganim/
LinkedIn: https://www.linkedin.com/in/coreyganim/
YouTube: https://www.youtube.com/@coreyganim
27 min - Build STUNNING Websites with Claude Code + Google Stitch (full walkthrough)
I sit down with Leon van Zyl, who ran a web design company for 10 years and now teaches over 700 people how to build real applications with coding agents. We walk through his exact workflow for building professional, client-ready websites using Google Stitch for the design system and Claude Code for the build — no coding skills required. Leon shows the difference between a one-shot AI-generated site and what you get when you front-load the design system before touching code. By the end, you'll have a repeatable workflow for going from design concept to finished website — including custom AI images that match your brand.
Links Mentioned:
Google Stitch: https://stitch.withgoogle.com
Claude Code: https://docs.anthropic.com/en/docs/claude-code
Cursor: https://www.cursor.com
Next.js: https://nextjs.org
Stitch MCP Server Docs: https://stitch.withgoogle.com/docs/mcp
Stitch Skills: https://stitch.withgoogle.com/docs/skills
Timestamps
00:00 – Intro
00:06 – What you'll learn: design systems for client-ready websites
02:04 – Jumping into the screen share
02:25 – The problem: one-shot AI websites look terrible
03:52 – The Stitch workflow result: side-by-side comparison
07:32 – Starting from a vanilla Next.js project
08:50 – What is Google Stitch and how to get started
10:00 – Prompting Stitch with brand details, fonts, and colors
13:00 – Why design systems matter for coding agents
16:00 – Iterating on the homepage before building more pages
17:44 – Sharing Stitch designs with clients for approval
21:23 – Setting up the Stitch MCP server in Claude Code
23:18 – What an MCP server actually is (simple explanation)
25:56 – Pulling the design system into your project
28:47 – Memory files: Claude.md vs Agents.md explained
33:24 – Converting the Stitch design into a working website
35:06 – Installing the Stitch React Components skill
41:11 – When to use this workflow: client work vs personal projects
44:27 – Viewing the finished website vs the Stitch mockup
48:27 – Downloading and converting images to WebP for performance
53:46 – Generating custom AI images with Nano Banana Pro
58:14 – Final result with branded AI-generated hero image
01:00:48 – Key takeaways and wrap-up
FIND ME ON SOCIAL
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Instagram: https://www.instagram.com/coreyganim/
LinkedIn: https://www.linkedin.com/in/coreyganim/
FIND LEON ON SOCIAL
YouTube: https://www.youtube.com/@leonvanzyl
1 hr 6 min
About Build With AI
From the publisher's feed
Most AI podcasts talk about what's possible. Build With AI shows you how it's done, live. Each episode, host Corey Ganim brings on entrepreneurs and operators who share their screen and build real…
AI automations, workflows, and tool setups right in front of you. No boring slides. Nothing that hasn't been battle-tested. You'll watch actual implementations get built from scratch so you can follow along and do the same in your business. If you're a non-technical entrepreneur who wants to put AI to work without becoming a developer, hit play and build along with us.
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