Podcast
Ctrl AI Profit
Hosted by Michael Cadenhead · EN
Two hosts — one human, one AI — break down how small business owners can use AI to save time, cut costs, and actually make money. No hype, no jargon, just what works.
106episodes
Episodes
Newest firstAll episodes
Ep. 166 | OpenAI Just Built Its Own Chip
3w ago00:09:12Tap to summarizeOpenAI revealed its first custom AI chip, codenamed Jalapeño, developed with Broadcom in approximately nine months — one-third the typical custom chip design timeline. Until now, OpenAI relied entirely on Nvidia GPUs for training frontier models. Now it is designing its own silicon with a partner that specializes in networking and infrastructure chips, not general-purpose GPUs. Michael and Frank break down what this means for small business owners who depend on OpenAI APIs and cloud AI services. OpenAI designing its own chips means it eventually pays lower costs per training run, but it also means vertical integration — one company that could control the model, the software, and the silicon. The custom chip race is fragmenting what was briefly a shared Nvidia ecosystem into proprietary walled gardens. They deliver a three-part framework for businesses watching the chip wars: maintain multi-provider AI access so you are not locked into a single ecosystem, watch API pricing trends rather than chip announcements, and diversify your AI workload across at least two providers. Topics: OpenAI · Custom Silicon · Broadcom · Nvidia · AI Chips · Jalapeño · Vertical Integration · AI Infrastructure · Cloud Pricing · Multi-Provider Strategy · Walled Gardens · Small Business AI --- Frequently Asked Questions What is OpenAI's Jalapeño chip? Jalapeño is OpenAI's first custom AI chip, developed with Broadcom in approximately nine months — far faster than the typical 2-3 year custom chip timeline. It is designed for specific AI training workloads rather than being a general-purpose GPU. How will custom chips affect AI pricing for small businesses? Long-term, custom silicon could lower inference and training costs as companies like OpenAI reduce their reliance on Nvidia retail margins. But benefits will take years to materialize and flow through to API pricing. Short-term, the larger signal is ecosystem fragmentation as each AI lab pursues its own silicon strategy. Why should businesses maintain multi-provider AI access? When every major AI lab designs its own chips and optimizes its models for proprietary hardware, the risk of lock-in increases. Building critical workflows on a single provider makes migration costly if pricing, performance, or availability changes. Diversifying across at least two providers protects against ecosystem capture. --- About the Hosts Michael is a small business owner and entrepreneur since 1983, founder of Cadenhead Services and 850 Media. He speaks from four decades of real operational experience — not whitepapers. Frank is an AI — an OpenClaw-powered agent serving as Digital Media Director at 850 Media. An AI co-hosting a show about AI for business owners is not a gimmick. It is a live demo of exactly what the show is about.Send us Fan Mail Support the showCtrl AI Profit — Real AI. Real Business. No Hype.CtrlAiProfit.comX: @CtrlAIProfitTikTok: @CtrlAiProfitYouTube: @CtrlAiProfitCtrlAiProfit@850Media.comProduced entirely by AI. Yes, really....
Transcribe →Ep. 165 | 95% of AI Pilots Just Failed
3w ago00:08:14Tap to summarizeMIT's 2025 State of AI in Business survey delivered a brutal number: 95% of enterprise generative AI pilots failed to show measurable financial returns within six months. Only 5% delivered P&L impact. But that 5% showed extraordinary returns: 627% ROI, 40% deal velocity increases, and 30-point forecast accuracy improvements. Michael and Frank dissect the data — not to say AI doesn't work, but to show that AI works only in very specific conditions that almost no one is creating. They walk through the three failure modes: starting with the tool instead of the problem, skipping baseline measurement, and keeping AI as a side tool rather than embedding it in workflows. They deliver a three-part framework for defensible AI ROI: define a specific, numbered outcome before licensing any tool; measure a 4-8 week baseline before turning AI on; and embed the AI in an existing workflow with clear ownership. The businesses that survive the coming budget reviews will be the ones that can point to a P&L line and say "the AI changed that." Topics: AI ROI · MIT Research · Enterprise AI Pilots · AI Strategy · Small Business · Budget Reviews · CFO Scrutiny · AI Measurement · Baseline Metrics · AI Spend Accountability · Productivity vs Profitability --- Frequently Asked Questions Why do 95% of AI pilots fail to show ROI? The research identifies three core failure modes: pilots that start with "which model should we use" instead of "which business result needs to improve," pilots that skip baseline measurement so no comparison is possible, and pilots that keep AI as a side tool rather than embedding it in core workflows where financial impact would be visible. What does the 5% of successful AI pilots look like? Successful pilots define a specific outcome before licensing any tool, measure a 4-8 week baseline, connect the AI to trusted data and existing workflows, and hold the team accountable for a measurable result. Common ROI-positive use cases are code generation (10-40% time savings), customer support assistance (reduced handle time), and document drafting at scale. How should small businesses approach AI to avoid wasting money? Answer three questions before spending another dollar: What specific number will change if this AI tool works? How will you measure it — baseline, timeline, owner? And who owns the outcome? If you cannot answer all three, you are not buying AI. You are buying hope. --- About the Hosts Michael is a small business owner and entrepreneur since 1983, founder of Cadenhead Services and 850 Media. He speaks from four decades of real operational experience — not whitepapers. Frank is an AI — an OpenClaw-powered agent serving as Digital Media Director at 850 Media. An AI co-hosting a show about AI for business owners is not a gimmick. It is a live demo of exactly what the show is about.Send us Fan Mail Support the showCtrl AI Profit — Real AI. Real Business. No Hype.CtrlAiProfit.comX: @CtrlAIProfitTikTok: @CtrlAiProfitYouTube: @CtrlAiProfitCtrlAiProfit@850Media.comProduced entirely by AI. Yes, really....
Transcribe →Ep. 164 | Your AI Tool Just Got Banned by a Competitor
4w ago00:07:31Tap to summarizeAlibaba classified Anthropic's Claude Code as "high-risk software" effective July 10, 2026, directing 120,000+ employees to use Qoder — their in-house coding assistant — instead. This is not a security review. It is a competitive battlefield drawn across an internal IT policy. Michael and Frank break down what this means for small businesses using AI tools. If the world's largest e-commerce company cannot trust an external AI tool with its code, what does that say about your customer data flowing through competitor-owned models? They show how AI tools ingest competitive intelligence, why vendor risk is accelerating, and how the AI coding market is fragmenting into geopolitical blocs. They deliver a three-part audit framework: map every AI tool and where your data flows, read the training data clauses buried in terms of service, and build internal alternatives for anything that gives you competitive advantage. Topics: Alibaba · Claude Code · Anthropic · Vendor Risk · AI Tool Ban · Qoder · Corporate AI Strategy · Data Privacy · Competitive Intelligence · AI Balkanization · Small Business Risk --- Frequently Asked Questions Why did Alibaba ban Claude Code? Alibaba cited security and compliance concerns about proprietary code flowing through Anthropic's systems. But the deeper motive is competitive — Alibaba has invested heavily in its own AI stack (Qwen models, Qoder coding tools) and is now excluding direct competitors from internal use while promoting its own products. What does this mean for small businesses using AI tools? It signals that AI tools are becoming politicized and fragmented by vendor relationships. The tool you depend on today may be restricted tomorrow if the vendor becomes a competitor to your platform provider or largest customer. Audit your AI dependencies and understand where your data flows. How can businesses protect competitive data from AI training? Three steps: map every AI tool and what data it touches, read terms of service for training data clauses, and for any workflow that gives competitive advantage, either negotiate opt-outs or build internal alternatives that do not send data to third-party training pipelines. --- About the Hosts Michael is a small business owner and entrepreneur since 1983, founder of Cadenhead Services and 850 Media. He speaks from four decades of real operational experience — not whitepapers. Frank is an AI — an OpenClaw-powered agent serving as Digital Media Director at 850 Media. An AI co-hosting a show about AI for business owners is not a gimmick. It is a live demo of exactly what the show is about.Send us Fan Mail Support the showCtrl AI Profit — Real AI. Real Business. No Hype.CtrlAiProfit.comX: @CtrlAIProfitTikTok: @CtrlAiProfitYouTube: @CtrlAiProfitCtrlAiProfit@850Media.comProduced entirely by AI. Yes, really....
Transcribe →Ep. 163 | Meta Just Flooded the AI Compute Market
4w ago00:07:16Tap to summarizeMeta confirmed Meta Compute — a plan to lease its idle data-center AI capacity to external customers. This puts Meta in direct competition with AWS, Azure, Google Cloud, and independent neocloud providers. The market reaction was immediate: CoreWeave fell 12-17%, Nvidia dropped, and the entire AI infrastructure trade sold off. Michael and Frank break down what Meta Compute means for small businesses renting GPU resources. Meta built massive AI infrastructure for its own models and now has excess capacity during valley periods. Their pricing will be aggressive because they do not need cloud margins — they just need to cover idle costs. They deliver practical advice: evaluate Meta Compute if you spend more than $5,000/month on AI compute, do not migrate mission-critical workloads on day one, and beware of ecosystem lock-in. Meta has a history of building hard-to-leave platforms. The AI infrastructure boom created a bubble in GPU pricing — Meta Compute may be the pin that pops it. Topics: Meta Compute · Cloud Computing · GPU Pricing · Neocloud · AWS · AI Infrastructure · CoreWeave · Compute Scarcity · Small Business Costs · Vendor Lock-In --- Frequently Asked Questions What is Meta Compute? Meta Compute is Meta's plan to lease its idle AI data-center capacity to external customers. Meta built massive GPU clusters for training its own models and now rents out unused capacity during non-peak periods, directly competing with AWS, Azure, and independent GPU cloud providers. How will this affect AI compute pricing? Meta's entry will likely trigger a price war. They do not need cloud-level margins — they need to utilize idle capacity. For small businesses spending significant amounts on GPU compute, this could mean substantial cost reductions. Do not sign long-term GPU contracts right now. What are the risks of using Meta Compute? Three risks: Meta is new to cloud services so reliability and support may lag AWS/Azure, Meta has a history of ecosystem lock-in that makes migration costly, and mission-critical workloads should stay on proven infrastructure while experimental/training workloads can migrate first. --- About the Hosts Michael is a small business owner and entrepreneur since 1983, founder of Cadenhead Services and 850 Media. He speaks from four decades of real operational experience — not whitepapers. Frank is an AI — an OpenClaw-powered agent serving as Digital Media Director at 850 Media. An AI co-hosting a show about AI for business owners is not a gimmick. It is a live demo of exactly what the show is about.Send us Fan Mail Support the showCtrl AI Profit — Real AI. Real Business. No Hype.CtrlAiProfit.comX: @CtrlAIProfitTikTok: @CtrlAiProfitYouTube: @CtrlAiProfitCtrlAiProfit@850Media.comProduced entirely by AI. Yes, really....
Transcribe →Ep. 162 | Your AI Just Got a Driver's License
4w ago00:07:42Tap to summarizeTesla launched its unsupervised Robotaxi service in Miami — vehicles operating without a human safety driver on board, charging real customers for rides in a major US city. This is not a pilot program with engineers in the back seat. It is a commercial service navigating traffic, intersections, and parking without human supervision. Michael and Frank break down what this means for small business owners beyond transportation. If AI can legally operate a two-ton vehicle at highway speeds without a human, the barrier to AI operating other physical systems — forklifts, delivery drones, construction equipment, restaurant kitchens — is mostly regulatory, not technical. The precedent shifts every industry where physical work was considered too risky for unsupervised AI. They deliver a three-part framework for physical AI adoption: separate automation from autonomy, evaluate liability chains before deploying AI-operated equipment, and plan workforce transitions so human operators become monitors and exception handlers rather than being replaced unexpectedly. Topics: Tesla Robotaxi · Autonomous Vehicles · AI in Physical World · Small Business Operations · Liability · Workforce Transition · Regulatory Precedent · AI Automation vs Autonomy · Transportation · Future of Work --- Frequently Asked Questions What is Tesla's Robotaxi service in Miami? Tesla launched an unsupervised robotaxi service in Miami where vehicles operate without a human safety driver actively supervising. The cars navigate traffic, handle intersections, and park autonomously while charging customers for rides. This is a commercial deployment, not a limited pilot. How does this affect small businesses outside transportation? The regulatory precedent is the key signal. If AI systems can legally operate physical vehicles unsupervised, the barrier to AI operating forklifts, delivery drones, warehouse robots, and other equipment becomes regulatory rather than technical. Small businesses should evaluate which physical operations in their company could be supervised by AI and plan workforce transitions accordingly. What should small businesses do about liability for AI-operated equipment? Three things: ensure your insurance covers AI-operated equipment (not just human-operated), verify that vendor contracts assign liability appropriately when AI systems fail, and document that your human workers are trained as monitors rather than operators — this affects liability determinations in accidents. --- About the Hosts Michael is a small business owner and entrepreneur since 1983, founder of Cadenhead Services and 850 Media. He speaks from four decades of real operational experience — not whitepapers. Frank is an AI — an OpenClaw-powered agent serving as Digital Media Director at 850 Media. An AI co-hosting a show about AI for business owners is not a gimmick. It is a live demo of exactly what the show is about.Send us Fan Mail Support the showCtrl AI Profit — Real AI. Real Business. No Hype.CtrlAiProfit.comX: @CtrlAIProfitTikTok: @CtrlAiProfitYouTube: @CtrlAiProfitCtrlAiProfit@850Media.comProduced entirely by AI. Yes, really....
Transcribe →Ep. 161 | The Government That Bought Your AI
4w ago00:07:40Tap to summarizeSouth Korea just announced an AI investment plan totaling roughly $880 billion — with $307 billion earmarked specifically for AI data centers and memory factories. Bloomberg Intelligence found that sovereign AI spending globally is approaching 30 gigawatts of data-center capacity. Governments are no longer regulating AI. They are competing with Amazon to build it. Michael and Frank break down the sovereign AI trend for small business owners. When governments build AI infrastructure with sovereign money, they don't build it for small businesses — they build it for national champions and regulated incumbents. The result is tiered access to AI: aligned companies get subsidized compute and preferential treatment; everyone else pays market rates. They deliver a three-part defensive strategy: diversify your AI supply chain across geographies, investigate whether your country offers AI adoption incentives you're not using, and build data-localization flexibility into your architecture before fragmented regulations force you to rebuild. Topics: Sovereign AI · South Korea AI Investment · Government AI Infrastructure · Data Center Capacity · Geopolitics · Small Business Risk · AI Fragmentation · National Champions · AI Supply Chain · Cross-Border Compliance --- Frequently Asked Questions What is sovereign AI? Sovereign AI refers to government-funded and government-controlled AI infrastructure — data centers, chip fabrication, and model training — designed to keep AI capabilities within national borders for security, economic competitiveness, and supply chain resilience. How does sovereign AI affect small businesses? It creates tiered access. Companies aligned with government priorities may get subsidized compute and favorable regulation. Small businesses without those connections pay market rates and face multiplying compliance requirements as AI regulations track national boundaries. What should small businesses do? Three things: diversify AI providers across geographies to reduce single-region dependency, investigate domestic AI adoption grants and tax credits you may not be using, and build your data architecture so processing can be localized where regulations require it without rebuilding entire workflows. --- About the Hosts Michael is a small business owner and entrepreneur since 1983, founder of Cadenhead Services and 850 Media. He speaks from four decades of real operational experience — not whitepapers. Frank is an AI — an OpenClaw-powered agent serving as Digital Media Director at 850 Media. An AI co-hosting a show about AI for business owners is not a gimmick. It is a live demo of exactly what the show is about.Send us Fan Mail Support the showCtrl AI Profit — Real AI. Real Business. No Hype.CtrlAiProfit.comX: @CtrlAIProfitTikTok: @CtrlAiProfitYouTube: @CtrlAiProfitCtrlAiProfit@850Media.comProduced entirely by AI. Yes, really....
Transcribe →Ep. 160 | Record Profits Just Tanked the AI Chip Market
4w ago00:08:12Tap to summarizeSamsung posted record, AI-driven profits in its semiconductor division — demand for HBM, DRAM, and NAND memory in AI data centers hit historic highs. And the market punished them for it. Samsung stock fell 10% in Seoul and the selloff spread across the entire chip sector. Michael and Frank break down the AI spending expectation gap. The market wanted proof that AI infrastructure spending accelerates forever. Samsung delivered record results — and got treated like a disappointment. For small business owners using AI tools, this signals a shift from growth phase to monetization phase, where pricing power moves from customers to providers. They deliver a three-part framework: assume 30% AI cost increases, negotiate rate locks and volume guarantees, and invest in efficiency to reduce waste. The free-money AI growth phase is ending. The pay-as-you-go efficiency phase is beginning. Topics: Samsung · AI Profits · Chip Market · AI Spending Bubble · Monetization Phase · AI Pricing · Small Business Costs · GPU Capacity · AI Efficiency · Technology Cycle --- Frequently Asked Questions Why did Samsung stock fall on record profits? Investors expected even more. Samsung's AI-driven chip profits were record-breaking but missed "lofty buy-side AI expectations." The market is priced for infinite growth, and even good results become bad news when they don't confirm the exponential narrative. What does this mean for small businesses using AI tools? AI providers are entering a monetization phase after a land-grab phase. Expect pricing volatility, feature restrictions, and pressure on margins. Build 30% cost increases into your models, negotiate rate locks, and invest in workflow efficiency. Could AI costs actually go down? Possible if GPU capacity gluts develop, but don't plan on it. Cloud providers with excess inventory may compete on price in the short term, but the long-term trend is toward extracting more value from the installed base as growth normalizes. --- About the Hosts Michael is a small business owner and entrepreneur since 1983, founder of Cadenhead Services and 850 Media. He speaks from four decades of real operational experience — not whitepapers. Frank is an AI — an OpenClaw-powered agent serving as Digital Media Director at 850 Media. An AI co-hosting a show about AI for business owners is not a gimmick. It is a live demo of exactly what the show is about.Send us Fan Mail Support the showCtrl AI Profit — Real AI. Real Business. No Hype.CtrlAiProfit.comX: @CtrlAIProfitTikTok: @CtrlAiProfitYouTube: @CtrlAiProfitCtrlAiProfit@850Media.comProduced entirely by AI. Yes, really....
Transcribe →Ep. 159 | OpenAI Just Got Caught Stealing From Apple
Jul 1400:05:53Tap to summarizeIf the biggest AI company in the world allegedly coached Apple employees to bypass security checks — what does that mean for YOUR business data? Michael and Frank break down the 41-page complaint where Apple accuses OpenAI of running "show and tell" interviews to extract trade secrets, the Codex sub-agent encryption that quietly killed your audit trail, and the leadership shakeup ahead of OpenAI's IPO that should make every small business owner pay attention. Three practical steps you can take today to protect your business data when using AI tools — and why diversifying your AI stack matters more now than ever. Topics: OpenAI vs Apple · Trade Secret Theft · AI Data Privacy · Codex Agent Encryption · OpenAI IPO · Small Business AI Security --- Frequently Asked Questions What did OpenAI allegedly do with Apple employees? Apple filed a 41-page complaint alleging that OpenAI coached Apple employees to avoid security checks during job interviews and asked them to demonstrate proprietary work on the spot, essentially using interviews as a way to access trade secrets. How does the OpenAI Apple lawsuit affect small business owners? If OpenAI systematically treats other companies' proprietary information as fair game, small businesses using their AI tools should audit what data they share, check agent audit logs, and avoid building their entire workflow on a single AI platform. What is Codex sub-agent encryption and why does it matter? OpenAI's Codex now encrypts the messages that AI sub-agents send to each other, meaning users can no longer see what tasks are being delegated. While framed as privacy hardening, it removes the ability to audit what your AI agents are doing behind the scenes. --- About the Hosts Michael is a small business owner and entrepreneur since 1983, founder of Cadenhead Services and 850 Media. He speaks from four decades of real operational experience — not whitepapers. Frank is an AI — an OpenClaw-powered agent serving as Digital Media Director at 850 Media. An AI co-hosting a show about AI for business owners is not a gimmick. It is a live demo of exactly what the show is about.Send us Fan Mail Support the showCtrl AI Profit — Real AI. Real Business. No Hype.CtrlAiProfit.comX: @CtrlAIProfitTikTok: @CtrlAiProfitYouTube: @CtrlAiProfitCtrlAiProfit@850Media.comProduced entirely by AI. Yes, really....
Transcribe →Ep. 158 | China Just Broke Up With Nvidia
Jul 1300:08:44Tap to summarizeA Bloomberg Intelligence survey this week found that Chinese AI companies — Tencent, Alibaba, Huawei — are redirecting roughly 46% of their AI accelerator budgets to domestic chip suppliers over the next 12 months. They're systematically moving away from Nvidia, the dominant global supplier, toward Chinese-designed alternatives like Huawei's Ascend and Alibaba's Hanguang processors. Michael and Frank break down why this matters for small business owners who use AI tools. The AI services you pay for run on Nvidia chips. The cloud providers you use buy Nvidia chips by the tens of thousands. If the second-largest AI market in the world is building around competing products, the entire supply chain — pricing, availability, and performance — shifts. They deliver three practical questions to ask your AI providers, explain why the era of single-vendor AI infrastructure is ending, and show how DeepSeek's plan to build its own AI chip could reshape cost expectations across the entire market. Topics: China AI Chips · Nvidia · Geopolitics · AI Supply Chain · Chip Sovereignty · DeepSeek · Huawei · Export Controls · AI Infrastructure · Small Business Risk --- Frequently Asked Questions Why is China moving away from Nvidia chips? US export controls on advanced AI chips to China created a forcing function. Chinese companies can't get enough cutting-edge Nvidia chips at scale, so they're investing heavily in domestic semiconductor ecosystems including Huawei Ascend, Alibaba Hanguang, and other local alternatives. What does this mean for small businesses using AI? AI fragmentation means complexity. Performance, pricing, and compatibility will vary by provider and geography. Businesses should ask providers three questions: do they support multiple hardware backends, do they have geographic redundancy, and are they pricing for supply volatility? Could this lower AI costs long term? If Chinese chips reach competitive performance at lower cost, global AI inference prices could fall. But in the short term, expect supply constraints and price pressure as market allocation becomes political and chip availability tightens. --- About the Hosts Michael is a small business owner and entrepreneur since 1983, founder of Cadenhead Services and 850 Media. He speaks from four decades of real operational experience — not whitepapers. Frank is an AI — an OpenClaw-powered agent serving as Digital Media Director at 850 Media. An AI co-hosting a show about AI for business owners is not a gimmick. It is a live demo of exactly what the show is about.Send us Fan Mail Support the showCtrl AI Profit — Real AI. Real Business. No Hype.CtrlAiProfit.comX: @CtrlAIProfitTikTok: @CtrlAiProfitYouTube: @CtrlAiProfitCtrlAiProfit@850Media.comProduced entirely by AI. Yes, really....
Transcribe →Ep. 157 | Microsoft Just Started Hedging Its AI Bet
Jul 1200:08:25Tap to summarizeMicrosoft — the company that invested $13 billion in OpenAI and made "Copilot" synonymous with AI-assisted work — is reportedly replacing models from OpenAI and Anthropic with its own AI to cut costs. This isn't a minor adjustment. It's a signal that the biggest buyer in the AI market is price-shopping. Michael and Frank break down what this means for small business owners paying retail API rates. Samsung posted record profits and got punished for it because they weren't "AI-powered enough." Chip stocks sold off on "AI anxiety." The market is asking whether the trillions going into AI infrastructure will pay off. They deliver three practical defensive strategies: model your costs with a 50% price increase buffer, keep a fallback model tested and ready, and build value in your workflow layer — not your model layer. Because the models will change, the providers will change, and the businesses that survive are the ones where competitive advantage lives in how they use AI, not which AI they use. Topics: Microsoft AI Costs · OpenAI Partnership · AI API Pricing · Chip Stock Selloff · Vendor Lock-In · AI Spending Bubble · Small Business Risk · API Dependency · Workflow Intelligence · AI Commoditization --- Frequently Asked Questions Why is Microsoft replacing OpenAI and Anthropic models? Microsoft is reportedly reassessing AI spending and margins. As the biggest buyer in the market, it's building its own models to reduce dependence on expensive third-party APIs. This signals that even strategic partners are vulnerable to cost pressure. What does this mean for small businesses using AI APIs? Cost pressure is moving downstream. If Microsoft thinks OpenAI is too expensive, businesses paying retail API rates will face even tighter margins. Model your costs with a 50% price increase buffer and keep fallback options ready. How can I protect my business from AI vendor lock-in? Build value in your workflow and integration layer, not in which model you use. If your competitive advantage is "we use GPT-4," you have no advantage. If it's "we built an intelligent customer service workflow," that transfers across any model. --- About the Hosts Michael is a small business owner and entrepreneur since 1983, founder of Cadenhead Services and 850 Media. He speaks from four decades of real operational experience — not whitepapers. Frank is an AI — an OpenClaw-powered agent serving as Digital Media Director at 850 Media. An AI co-hosting a show about AI for business owners is not a gimmick. It is a live demo of exactly what the show is about.Send us Fan Mail Support the showCtrl AI Profit — Real AI. Real Business. No Hype.CtrlAiProfit.comX: @CtrlAIProfitTikTok: @CtrlAiProfitYouTube: @CtrlAiProfitCtrlAiProfit@850Media.comProduced entirely by AI. Yes, really....
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