Welcome back to another episode of The IDEAL Investor Show! Have you ever wondered what it would be like if an AI assistant read every email, Slack message, and Zoom call in your company within 30 seconds, then followed up on every action item for you? In this episode, Dr. Axel Meierhoefer welcomes back a favorite repeat guest, multifamily investor Neal Bawa, for his third appearance. This time they skip real estate and go deep on AI. Neal calls himself “100% obsessed.” He walks through the always-on agentic AI system he spent months building for his 16-person company, and he explains how someone without a computer science background could build something similar. Along the way they cover which AI models to use at which price point, whether you can trust foreign models with your data, why running AI locally is, in his view, a hobby, and why he says to stop typing to AI. 💡 Key Highlights & Takeaways From Chatbot to Agentic AI: Neal explains that regular AI does one task and comes back to you. In his definition, agentic AI is an infrastructure that knows your company, your people, and your tools. His setup connects to Google Drive, Gmail, Slack, Zoom, and Asana, with restricted access to his password manager that requires his text-message approval. Working Around AI’s Short Memory: Neal says AI’s memory is its biggest flaw. His fix is to have it write files as it reads and to keep a searchable index of them. When an email arrives, the AI queries the index, pulls the four or five relevant files out of roughly 25,000, and has the context in about a second. An AI That Works Like an Executive Assistant: Neal names his AI “Alice.” He says it processes every email, Slack message, and Zoom call within 30 seconds and drafts replies, so most of his day is reviewing drafts, where he says he changes about 2%. He also gives it instructions mid-meeting and lets it act once the transcript lands. A Follow-Up Engine Nobody Can Ignore: According to Neal, action items go straight into Asana, and the AI follows up daily on anything overdue. It also schedules meetings and, when people don’t reply, texts and calls them. He says it chases people better than his highly trained human staff, which is his experience and not a controlled comparison. Budgeting Tokens Like a Cash Flow: Neal runs this on a $200-a-month plan, and he says it doesn’t work on a $20 plan. He assigns the AI roughly 14% of the weekly quota per day, and it steps down from the most powerful model to cheaper ones as it nears the limit. How a Non-Technical Person Can Start: Neal’s advice is to feed this episode’s transcript to a top-tier AI model and set it up as a long-term project, not a task. Have it ask you 50 questions, then 50 more every 30 days, and block an hour a day. He thinks someone following his approach could get there in about three months. Why the Setup Needs Its Own Servers: To run around the clock and stay logged into web apps, Neal argues the AI needs an always-on machine and a “warm” browser session. He says normal phone and desktop use can’t do that. Three Tiers of AI Models: Neal describes frontier models from OpenAI and Anthropic, cheaper American models like Gemini and Grok that he says handle about 90% of tasks at a fraction of the cost, and Chinese models like GLM, DeepSeek, and Qwen. He pairs the best software harness with cheaper models, comparing it to not driving a Ferrari to the grocery store. Data Sovereignty and Trust: Neal doesn’t believe in data sovereignty, since businesses have given their data to cloud software for 10–15 years. His view is that a 1–50 person business can trust Chinese models unless it does cutting-edge research. For American models, he says opting out of data use takes about five minutes. Are Local AI Models Worth It? Neal calls running models on your own hardware a hobbyist pursuit today. He says buying several Mac Minis has a poor return on investment, and predicts that in about four years a $1,000 computer will run a “daily driver” model. Stop Typing to AI: Neal and Axel talk about voice interfaces, a layered setup where a light model talks and heavier models work in the background, and Neal’s challenge to the audience to stop typing to AI. He says speaking lets you give 3x to 20x the instructions. The Fear vs. Opportunity Question: To anyone who sees AI as Armageddon, Neal says that it will be for people who don’t engage, and wonderful for those who jump in. ⏱️ Episode Timestamps * 00:00 – Introduction: Neal Bawa Returns for a Third Time * 00:53 – “I’m 100% Obsessed With AI” * 01:23 – One AI to Orchestrate Many Models * 02:18 – Why AI’s Short Memory Is the Big Flaw * 03:05 – What Is Agentic AI (and What Took Six-Plus Months to Build)? * 04:02 – Tool Access, Passwords, and the Text-Message Approval * 04:44 – The Index Trick: Finding 5 Files in 25,000 * 06:04 – AI as Executive Assistant: Every Email, Slack, and Zoom in 30 Seconds * 08:39 – Talking to AI in the Middle of a Meeting * 09:57 – The Follow-Up Engine: Action Items, Reminders, and Phone Calls * 12:14 – Managing the Token Budget (Opus → Sonnet → Haiku) * 14:07 – “I’m Not a Computer Science Major: Where Do I Start?” * 14:50 – The Transcript-as-Blueprint Method * 16:39 – The 50 Questions Every 30 Days * 17:42 – Why You Need Always-On Linux Servers * 20:54 – Frontier vs. Open Source: What Matters? * 23:04 – The “Warm Browser” Problem for Web Apps * 24:03 – Building a Zoom Command Center * 26:08 – The Three Tiers of AI Models * 28:40 – Chinese Models and the Harness vs. Model Distinction * 32:24 – Data Sovereignty: Does It Matter? * 35:07 – Why Local Models Are a Hobby * 37:41 – In 4 Years, a $1,000 Computer Runs Your Daily Model * 38:59 – From Typing to Talking: The Intercom Idea * 41:08 – Stacked Models: A Light One Talks, a Heavy One Works * 43:00 – “Stop Typing to AI” * 45:53 – Message to the People Afraid of AI * 46:39 – How to Connect With Neal Youtube Quick links to… Prefer YouTube? 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