Blog

• AI Tools: 8 Free AI Tools to Get You Ahead of 99% of People

  Watch on YouTube: https://www.youtube.com/watch?v=DMlBzXvG22g

  Channel: Austin Marchese

  Introduction

  The video from Austin Marchese outlines eight free AI‑enhanced utilities that can be combined with Claude to improve planning, token efficiency, output control, project management, content discovery, local file handling, business skill application, and voice input. It also notes two sponsors that provide payment processing and analytics, positioning the toolset as a way to build faster, lower costs, and better evaluate ideas.

  What the video covers

  The presentation walks through each utility, explaining its purpose, how it integrates with Claude, and the performance claims associated with it. The tools are grouped into categories: visual planning, input filtering, output limitation, parallel project sessions, real‑time content aggregation, local markdown viewing, pre‑built business skills, and voice‑to‑text control. Sponsor mentions are included for context but are not presented as free tools.

  Step‑by‑step walkthrough

  • Lavish – visual planning: Install Lavish, then tell Claude “download Lavish” using the provided link. Once loaded, you can create a visual planning document, add comments, and use the “send to agent” action to update the plan automatically as the conversation progresses.
  • RTK (Rust Token Killer) – input filtering: Run the RTK command (similar to the Lavish setup) before sending text to Claude. The tool strips unnecessary characters, claiming a 60‑90% reduction in input tokens. After filtering, the example shows roughly 1,800 tokens remaining from an original ~15,000‑token input.
  • Caveman & Ponytail – output control: Copy the combined Caveman + Ponytail query into Claude. Ponytail is said to reduce code volume by about 54%, while Caveman forces terse, “caveman‑style” responses. The video cites associated speed and cost benefits: up to 94% faster, about 20% cheaper, and about 27% faster in certain scenarios.
  • Claude Code Projects – parallel sessions: Enable the Projects tab in Claude (available for Pro/Max users). This feature lets you run multiple cloud sessions within a single conversation, maintaining separate contexts while sharing the overall chat history.
  • buildpartner.ai – real‑time content discovery: Within Claude, ask buildpartner.ai for recent free AI tools from Twitter, Instagram, or YouTube. The tool pulls live feeds into the chat, allowing you to curate trend roundups without leaving the terminal. A referral link provides five times the free usage.
  • Obsidian – local markdown viewer: Download Obsidian, create a folder for your Claude‑generated markdown files, and use it as a local editor. The video likens it to “Apple Notes on steroids” for viewing and editing files stored on your machine.
  • Anthropic small‑business plugin – pre‑built skills: Install the plugin to access ready‑made skills such as sales funnel builders, mail management utilities, and other business‑focused automations. These are intended to spark creative implementation within your Claude workflow.
  • Hex – voice‑to‑text control: Set up Hex with the double‑press Ctrl hotkey. Pressing the hotkey activates voice dictation that can be used in any application, turning spoken thoughts into text without leaving your current workspace.

  Tools and performance numbers

  • RTK claims 60‑90% token reduction for inputs.
  • After RTK filtering, the example shows ~1,800 tokens remaining from an original ~15,000‑token raw output.
  • Ponytail claims ~54% less code volume.
  • Associated speed claims: up to 94% faster, about 27% faster in certain tests.
  • Cost claim: about 20% cheaper when using Ponytail‑limited output.
  • buildpartner.ai offers 5x free usage via its referral link.
  • All eight core utilities (Lavish, RTK, Caveman, Ponytail, Claude Code Projects, buildpartner.ai, Obsidian, Anthropic plugin, Hex) are described as free to use.

  Caveats and hype check

  The video cites strong performance claims (e.g., 60‑90% token reduction, 54% less code, up to 94% faster) that are based on tool documentation and may vary by use case; these should be treated as optimistic estimates rather than guaranteed results.

  Multiple affiliate or referral links are presented (Lavish, buildpartner.ai, etc.), and the sponsor Wopp/Wopster receives prominent promotion, indicating a commercial incentive behind the recommendations. The sponsor Warp is also mentioned for payment processing and customer analytics, but the video does not detail its free tier or specific features.

  Concrete next actions

  • Add Lavish to Claude and say “download Lavish” with the provided link to enable visual planning.
  • Run the RTK command (similar to the Lavish setup) to filter input before sending to Claude.
  • Copy the Caveman + Ponytail query into Claude to limit output length and complexity.
  • Enable Claude Code Projects via the Projects tab in Claude (Pro/Max) to run parallel sessions.
  • Use buildpartner.ai to ask for recent free AI tools on Twitter, Instagram, or YouTube without leaving Claude.
  • Download Obsidian, create a repository folder, and use it to view/edit Claude‑generated markdown files.
  • Explore the Anthropic small‑business plugin and experiment with its pre‑built skills in your workflow.
  • Set up Hex with the double‑press Ctrl hotkey to start voice dictation into any application.
  • Sign up for Wopp/Wopster using the link in the description for low‑fee payments and analytics.
  • Consider Warp for additional payment processing and customer‑analytics features.
  • Comment on the video which tool interests you most to enter the giveaway for a Claude Max subscription.

  October 16, 2026

• Marketing & Lead Gen: The ONLY Marketing Training Video You’ll Ever Need (FULL COURSE)

  Watch on YouTube: https://www.youtube.com/watch?v=daCB1kVOtMA

  Channel: orenmeetsworld

  Introduction

  The video from orenmeetsworld presents itself as a comprehensive marketing framework designed for the AI era. It promises a single, free training resource that covers brand positioning, messaging, brand‑world mapping, organic social tactics, paid demand generation, and ways to integrate AI into marketing workflows. The presenter claims the course is the only marketing training needed and is made freely available thanks to OpenAI support.

  What the Video Covers

  The presentation is organized around several core components:

  • Brand positioning – how to be remembered and AI‑legible, with a list of positioning archetypes.
  • Messaging style – choosing a target‑need statement and a copy style (direct response, evidence‑led, human‑driven, culturally savvy) that can be loaded into an LLM project.
  • Brand world mapping – using characters, sets, events (company, culture, industry) and a plot of friends/enemies/specials to plan content calendars and spot gaps.
  • Organic social media – relying on narrative, taste, focus, and credibility; core strategies include expert‑on‑camera, storytelling, and art‑directed content, plus a pillar‑system for testing formats and monthly analytics.
  • Paid demand generation – starting with Meta ads, setting ad‑set budgets, testing new ad sets weekly, beginning at $50/day, optimizing for highest volume, and moving from lookalike to broad targeting.
  • AI integration levels – ranging from simple chatting to project‑based context, repeatable skills, autonomous agents, and a central marketing brain.
  • Supporting tools and metrics – positioning toolkit, Content Oracle, Video Database, Social Growth Engineers, Outer Signal, MCP‑enabled Chat GBT for Meta ads analytics, and key ad metrics such as ROAS, CPA, CAC, LTV (targeting a ~3:1 CAC:LTV ratio).

  Step‑by‑Step Walkthrough

  Based on the notes, a practical workflow derived from the video could look like this:

  • Define a positioning statement using the target‑need formula (e.g., “Four distance runners who deal with side pain…”) and select one of the positioning archetypes (performance, category creation, counter, smart, value, niche, generational, single attribute, premium, designer, bespoke, counter‑luxury, or name).
  • Choose a messaging style that matches the brand’s voice and load the chosen style, product sheets, website copy, testimonials, and the positioning statement into a Chat GBT project to create a repeatable copy skill.
  • Build a brand world map on a whiteboard or digital canvas: list characters (brand persona, ideal customer, competitors), sets (physical or digital locations where the brand appears), events (product launches, industry trends, cultural moments), and plot elements (friends, enemies, specials) to generate content ideas and identify gaps.
  • Plan an organic social calendar using a pillar‑system: pick three to five content formats (e.g., carousel, short video, testimonial graphic, behind‑the‑scenes, educational tip) and test them on a platform like Instagram or LinkedIn. Collect performance data monthly and double down on the formats that drive the highest engagement.
  • Launch a Meta ad set with a $50/day budget, using lookalike targeting initially and the highest‑volume bid strategy. Test new ad sets weekly, pause underperforming ones, and scale winners once a stable ROAS or CPA is achieved.
  • Develop repeatable AI skills in Chat GBT for each messaging style (direct response, evidence‑led, human‑driven) so that new ad copy or social posts can be generated on demand.
  • Use the Content Oracle (accessible via free Chat GBT) to generate niche‑specific content ideas whenever the content calendar needs refreshing.
  • Connect Meta Ads Manager to Chat GBT through MCP to receive weekly performance reports, allowing quick decisions on creative refreshes and budget reallocations.
  • Monitor key metrics: ROAS, CPA, CAC, and LTV. Aim for a CAC:LTV ratio near 3:1, adjusting targeting or creative when the ratio drifts.

  Tools and Numbers Mentioned

  The video references several specific tools and quantitative benchmarks:

  • Positioning toolkit – contained in the downloadable marketing.zip file.
  • Content Oracle – a free prompt‑based tool accessible via Chat GBT.
  • Video Database app – for storing and retrieving video assets.
  • Social Growth Engineers – a service priced at $20‑30 per month.
  • Outer Signal – for pulling customer social profiles.
  • MCP‑enabled Chat GBT – enables analytics integration with Meta Ads Manager.
  • Meta Ads Manager – the platform for launching and managing paid campaigns.
  • Clavio – mentioned as an additional tool (no further detail provided).
  • Financial benchmarks: start Meta ad tests at $50/day; consider a monthly spend of around $1,500; expect a 30%‑50% scale difference between TikTok and Meta; target a 3:1 CAC:LTV ratio; use a 3‑5x target CPA for initial testing phases.

  Caveats and Hype Check

  While the video offers a structured approach, a few points merit caution:

  The video calls itself the “ONLY Marketing Training Video You’ll Ever Need” and claims it is free thanks to OpenAI, which may overstate its uniqueness and downplay other valuable resources.

  Additionally, the downloadable marketing.zip is promoted without a detailed description of its contents, leaving room for speculation about potential upsells or affiliate motives. The presenter’s emphasis on being “remembered” and the claim that “distribution is king” are persuasive but should be weighed against the specific context of your industry and audience.

  Concrete Next Actions

  To apply the framework without relying on unverified claims, consider the following steps:

  • Draft a target‑need statement for your product or service and pair it with a positioning archetype that fits your brand’s personality.
  • Create a simple brand world map on a sheet of paper or a digital whiteboard, populating the four quadrants (characters, sets, events, plot).
  • Set up a Chat GBT project, upload your positioning statement, product specifications, and a few customer testimonials, then experiment with generating copy in each of the four messaging styles.
  • Select three content formats to test on your primary social platform, publish them over a two‑week window, and record engagement metrics to inform a monthly pillar‑system report.
  • Launch a Meta ad set with a $50/day budget, using a lookalike audience based on your current customer list, and optimize for the highest volume of conversions.
  • Define a repeatable AI skill in Chat GBT for direct‑response copy (e.g., “Generate a headline that includes a numeric benefit and a urgency trigger”).
  • Run a query in the Content Oracle for “content ideas for [your niche]” and add the top three suggestions to your upcoming content calendar.
  • Link your Meta Ads Manager account to Chat GBT via MCP to automate a weekly performance snapshot that highlights ROAS, CPA, and spend.
  • At the end of each week, review ad creative performance, pause any ad set with a CPA above your 3‑5x test threshold, and reallocate budget to the top‑performing creatives.
  • Calculate your CAC from the Meta campaign data and compare it to your estimated LTV; adjust targeting, bidding, or creative until the ratio approaches 3:1.

  October 16, 2026

• AI Receptionist: My COMPLETE Workflow for Building Production AI Agents

  Watch on YouTube: https://www.youtube.com/watch?v=9tinC8jG7FM

  Channel: Owain Lewis

  Introduction

  The video presents a complete, repeatable workflow for building a production‑ready AI agent that could serve customers on a hotel website. It emphasizes the importance of upfront planning, using managed Google Cloud services, and leveraging AI‑assisted development tools to automate repetitive tasks. The goal is to give viewers a practical blueprint they can adapt to their own AI‑driven projects.

  What the Video Covers

  The walkthrough begins with gathering clear requirements and drafting a technical architecture document before any code is written. It shows how to bundle a static frontend and a backend API into a single Google Cloud Run service, select Gemini Flash as the inference model for its large context window, low latency, and low cost, and use AI agents such as Claude Code and Codex to generate tickets, write code, and run automated browser tests. The video also details setting up database backups, enabling observability, validating safety edge cases, and iterating on the agent using Google’s eval feature and LLM‑as‑a‑judge.

  Step‑by‑Step Workflow

  • Define requirements and create a requirements.md file that outlines functional and non‑functional goals for the AI agent.
  • Draft an architecture.md document that describes how the frontend, API, model, and data stores will interact, noting that changes become costly later.
  • Provision a Google Cloud Run service that bundles the static site and the API endpoint into a single managed deployment.
  • Choose Gemini Flash as the model endpoint, taking advantage of its large context window, low latency, and inexpensive pricing.
  • Use Claude Code or Codex to automatically generate Linear tickets (via MCP) and to scaffold code, reducing manual effort.
  • Configure automated PostgrSQL backups with a retention policy, for example daily snapshots kept for seven days, to protect data and control storage growth.
  • Activate Google Cloud Logging, Tracing, and Alerting to gain observability into request flows, errors, and performance metrics.
  • Run the Google Eval suite, collect sample interactions, and employ an LLM‑as‑a‑judge to score safety and accuracy, then refine the system prompt stored in an external markdown file.
  • Validate edge cases such as prompt injection and data leakage before promoting the agent to production.
  • Break the effort into milestones — local development, testing, production deployment, and observability setup — to track progress and maintain focus.

  Tools and Numbers Mentioned

  • Google Cloud as the primary cloud provider.
  • Cloud Run for hosting the combined frontend and API.
  • Gemini Flash model selected for its large context window, low latency, and low cost.
  • Claude Code and Codex used as AI agents to generate tickets, write code, and run browser‑based tests.
  • Linear (via MCP) for ticket management and tracking.
  • PostgrSQL as the relational database.
  • Google Secret Manager for storing API keys and sensitive configuration.
  • Google Logging & Tracing for observability.
  • Agent CLI and Google Cloud CLI for infrastructure and agent management.
  • Google Agent Development Kit (ADK) for building the agent.
  • Google Eval feature for systematic evaluation and improvement.
  • Example project value cited as $5,000 to illustrate scope.

  Caveats and Hype Check

  The video is produced in partnership with Google Cloud and uses a $5,000 hotel AI system as an illustrative example; this figure is not a guaranteed revenue outcome or result. The presenter stresses that spending significant time on evaluations and testing is critical for reliability, and that architectural changes become difficult once the system is deployed.

  “If you’re building an AI system in production for real customers, you’re going to need all of these things.”

  “Spending a lot of time on evals and testing is really really important.”

  Concrete Next Actions

  • Install the Google Cloud CLI and the Agent CLI to manage infrastructure and agent resources.
  • Create a requirements.md file that captures all functional and non‑functional specifications.
  • Draft an architecture.md document that outlines the Cloud Run service, model choice, data store, and security boundaries.
  • Deploy a Cloud Run instance that bundles the static frontend and the backend API.
  • Select Gemini Flash as the inference model for the agent, confirming its pricing and latency characteristics.
  • Use Claude Code or Codex to generate Linear tickets and to scaffold initial code modules.
  • Set up automated PostgrSQL backups with a defined retention policy, such as daily snapshots retained for seven days.
  • Enable Google Cloud Logging, Tracing, and Alerting, and configure alerts for error rates and latency thresholds.
  • Run the Google Eval suite, gather a representative set of user interactions, and use an LLM‑as‑a‑judge to evaluate safety and accuracy.
  • Store the system prompt in an external markdown file to simplify versioning and updates.
  • Perform targeted security testing for prompt injection and data leakage before moving to production.
  • Organize work into milestones — local development, testing, production deployment, and observability — and track completion against each.

  October 16, 2026

• Grok Bot: Grok Voice 3.0 Just Killed the Call Center

  Watch on YouTube: https://www.youtube.com/watch?v=f2fvgG5VJJw

  Channel: Stacked Podcast

  Introduction

  The Stacked Podcast episode examines Grok Voice 3.0, a voice‑AI model released by XAI that promises ultra‑low latency and a low per‑minute cost. The discussion centers on how these characteristics could reshape traditional call‑center operations, citing real‑world usage at Starlink and integration in Tesla and Cybertruck vehicles.

  What the video covers

  The presenter walks through the core capabilities of Grok Voice 3.0, compares its speed to competing models, and outlines the economics of deploying it at scale. Specific case‑study numbers from Starlink are shared to illustrate resolution rates and sales conversion. The segment also touches on privacy considerations and the strategic advantage of early adoption.

  Step‑by‑step walkthrough

  1. Model overview – Grok Voice 3.0 is described as an ultra‑low‑latency voice model from XAI.
  2. Latency claim – The first audio response is said to occur in about 0.6 seconds, roughly half the latency of GPT Live One (~1.4 seconds).
  3. Pricing – Usage is priced at $0.08 per minute, which the video equates to roughly $5 per hour of active voice time.
  4. Starlink deployment – According to the presenter, Starlink routes approximately 20,000 customer calls per day through Grok Voice 3.0, handling multiple languages.
  5. Resolution rate – Around 70 % of those calls are resolved without any human agent intervention.
  6. Sales conversion – One in four AI‑handled sales calls reportedly results in a purchase before the caller ends the conversation.
  7. Vehicle integration – The Grok bot, powered by the same voice model, is already operational in Tesla and Cybertruck vehicles for in‑car assistance.
  8. Strategic implication – Speed is positioned as the primary factor influencing perceived quality, suggesting that AI agents could replace low‑performing human staff in call centers.
  9. Privacy note – The discussion raises a caution about potential data exposure when voice interactions are processed by external AI services.

  Tools and numbers

  • Grok Voice 3.0 – voice‑AI model from XAI.
  • Latency: 0.6 seconds (first audio).
  • Comparison latency: GPT Live One ≈ 1.4 seconds.
  • Cost: $0.08 per minute (~$5 per hour).
  • Starlink usage: ~20,000 calls per day.
  • Resolution without human: ≈ 70 %.
  • Sales conversion: 1 in 4 AI‑handled sales calls ends in a purchase.
  • Integration platforms: Tesla, Cybertruck (via Grok bot).

  Caveats and hype check

  The video presents impressive performance and cost claims without independent verification or third‑party data; the Starlink usage stats (20k calls/day, 70% resolution, 1 in 4 sales) are anecdotal and should be treated as promotional rather than proven results.

  Because the figures are drawn from the presenter’s interpretation of Starlink’s internal metrics, readers should treat them as indicative rather than definitive. Any decision to adopt Grok Voice 3.0 should incorporate a pilot phase, internal validation, and a review of data‑privacy policies that govern voice data handling.

  Concrete next actions

  • Visit the XAI/Grok website to request a demo or trial of Grok Voice 3.0 for internal evaluation.
  • Calculate potential cost savings for your current call‑center operation using the $0.08/minute rate versus your existing agent labor expenses.
  • If your organization operates a fleet of Tesla or Cybertruck vehicles, explore integrating the Grok bot for in‑car customer support or information services.
  • Design a small‑scale pilot that routes 2‑3 % of low‑performing or high‑volume call‑center traffic to Grok Voice 3.0, measuring resolution rate, average handling time, and any impact on sales conversion.
  • Monitor public case studies or press releases from Starlink (or other early adopters) for independently verified performance data before scaling the deployment.

  October 16, 2026

• Marketing & Lead Gen: Give Me 27 Minutes and I’ll Make You Disgustingly Rich This Black Friday

  Watch on YouTube: https://www.youtube.com/watch?v=LpZ3xq1qaQc

  Channel: Sabri Suby

  Introduction

  Sabri Suby’s video outlines a comprehensive Black‑Friday playbook built from the agency’s experience driving over $10.2 billion in client sales. The focus is on preparation months ahead, audience segmentation, and simple, urgent offers that convert during the peak shopping period. The advice is presented as a series of actionable hacks that can be applied to e‑commerce stores using platforms such as Shopify, Meta ads, email, and SMS.

  What the video covers

  The presentation is organized around four core phases:

  • Pre‑sale engagement and audience building (weeks to months before Black Friday).
  • Technical setup – separating campaigns, adjusting ROAS targets, tagging creatives, and preparing exclusion lists.
  • Offer creation and psychological triggers – simple discounts, gift‑wrapping, limited‑quantity “hit” products, deposit locks, and password‑protected sale pages.
  • Execution during the sale – ad creative choices, bid strategies, email and SMS cadence, abandoned‑cart timing, upsells, and post‑sale follow‑up.

  Each phase includes specific tactics, tools, and numeric benchmarks that the speaker claims improve efficiency and revenue.

  Step‑by‑step walkthrough

  • Start engagement campaigns weeks before Black Friday to accumulate likes, comments, and reach at low CPM.
  • Increase daily ad spend by 15‑20% so the account reaches full capacity by the sale date.
  • Create a dedicated Black‑Friday campaign with its own budget, isolated from ongoing campaigns.
  • Run low‑cost video awareness ads in October, then retarget those viewers with Black‑Friday offers.
  • Export Shopify, CRM, and Klaviyo data to build an exclusion audience of existing customers; notify them via email or SMS instead of paid ads.
  • Lower ROAS targets for the 11 months preceding Black Friday to grow a larger customer base that will be monetized in Q4.
  • Tag every creative by funnel stage (top, middle, bottom) to enable rapid activation of bottom‑of‑funnel assets on the sale day.
  • Warm up the email list by removing inactive subscribers and running re‑engagement chains.
  • In early November, ask the list which products they’d like discounted to gather demand data and improve relevance.
  • Capture leads months ahead with lead‑gen ads offering VIP early access; follow up via cheaper SMS or email channels.
  • Build an SMS contact list and promote subscriptions; aim for open rates above 90% (versus ~20% for email on Black Friday).
  • Segment SMS and email lists by past Black‑Friday buyers and prioritize them in promotions.
  • Accept $5‑$10 deposits to lock in discounts and measure pre‑sale demand.
  • Password‑protect the Black‑Friday sale landing page to create an exclusive feel and avoid spam perception.
  • Encourage shoppers to fill carts before midnight; treat abandoned carts as buyers and send follow‑up emails within 15‑60 minutes.
  • Test offers months in advance on small‑scale landing pages to identify top‑performing deals before scaling.
  • Use simple flat‑storewide discounts rather than complex tiered offers that can confuse shoppers.
  • Add free premium gift wrapping to position purchases as gifts, potentially expanding the audience.
  • Launch a limited‑quantity “hit” product with a deep discount to pull the cart and drive add‑on sales.
  • Sell steeply discounted gift cards (e.g., $100 card for $20) with usage restrictions to capture revenue now and later.
  • Gradually worsen promo terms each day before Black Friday to spur early purchases.
  • Personalize offers for loyal customers with extra gift cards, early access, or exclusive bonuses.
  • Show payment‑plan options (e.g., “4‑pay”) directly in ads to reduce price shock and increase click‑through rates.
  • Group the best creatives in one “hot potato” campaign for rapid scaling and easy duplication of winners.
  • Optimize successful campaigns for the lowest CPA; use price caps only in test campaigns to control spend.
  • On Black Friday, run simple static product‑photo ads that highlight price and offer rather than storytelling.
  • Align ad spend with audience paydays when conversion rates and ROAS typically peak.
  • Narrow retargeting windows to three days during Black Friday for higher efficiency.
  • Exclude recent purchasers from retargeting audiences immediately to spend only on new customers.
  • Use Google Smart Bidding’s seasonality feature to signal expected higher CPA and avoid bid limits.
  • Upload promotional prices and expiration dates to Merchant Center before Black Friday starts.
  • Remove Black‑Friday data from conversion modeling to prevent overspending in later months.
  • Send an internal‑leak style email the day before Black Friday to spark early curiosity and cart activity.
  • During the sale, send at least six emails, with three on the final day, matching subscriber expectations.
  • Send emails at unusual times (e.g., 11:46 or 9:38) to avoid inbox overload and improve deliverability.
  • Mid‑sale, send a plain‑text founder email without HTML; these often achieve the highest purchase rates.
  • Resend the same email with a new subject/header to non‑openers to effectively multiply reach.
  • Use “Oops, wrong coupon”‑style emails to stand out amid Black‑Friday noise and drive opens.
  • Compress abandoned‑cart email timing to 15‑60 minutes to capture shoppers while intent is high.
  • Add a one‑click upsell after purchase; expect 30‑40% uptake when buyers are ready to spend.
  • Include a $10 mystery gift card usable only in January with every Black‑Friday cart to boost perceived value.
  • After Black Friday, offer Cyber Monday‑only deals to the new shoppers acquired to extend revenue.
  • Create a December gift audience from ad clickers who didn’t buy in November and target them with lower‑cost CPMs.
  • If demand is high, extend the sale by 24 hours and remind shoppers every three hours via email or SMS.

  Tools and numbers referenced

  • $10.2 billion in client sales cited as the agency’s track record.
  • 15‑20% daily increase in ad spend leading up to Black Friday.
  • $5‑$10 deposit to lock in discounts.
  • $100 gift card sold for $20 (with usage restrictions).
  • CPM (cost per thousand impressions) as a metric for cheap awareness ads.
  • ROAS (return on ad spend) targets lowered for 11 months prior.
  • Meta Pixel, Shopify, CRM, Klaviyo for audience building and exclusions.
  • Google Smart Bidding seasonality feature.
  • Merchant Center for uploading promotional prices and expiration dates.
  • 30‑40% expected uptake for one‑click upsells.
  • 90% open rate for SMS versus ~20% for email on Black Friday.
  • Six emails during the sale, three on the final day.
  • Three‑day retargeting window during Black Friday.
  • Payday alignment for ad spend timing.

  Caveats and hype check

  The video’s title promises viewers will become “disgustingly rich” by applying the hacks, and it references the $10.2 billion figure as proof of effectiveness. These statements are promotional and lack independent verification or case‑study detail. While the tactics are drawn from the speaker’s agency experience, results will vary based on product category, audience size, and execution quality. Marketers should treat the suggestions as a framework to test rather than a guaranteed profit formula.

  Concrete next actions

  • Audit current ad accounts and set up a separate Black‑Friday campaign with its own budget.
  • Begin engagement ads now, targeting low‑CPM video views to build a retargeting pool for October.
  • Export customer lists from Shopify, CRM, and Klaviyo to create an exclusion audience; plan email/SMS outreach for those segments.
  • Reduce ROAS targets in the ad platform for the next 11 months to allow broader audience growth.
  • Implement a tagging system for all creatives by funnel stage (top, middle, bottom).
  • Clean the email list: remove inactive subscribers and launch a re‑engagement sequence.
  • In early November, send a survey asking which products subscribers want discounted.
  • Run lead‑gen ads offering VIP early access; capture phone numbers for an SMS list.
  • Set up an SMS subscription promo and benchmark open rates against email.
  • Design a simple flat‑storewide discount test on a landing page to validate the offer before scaling.
  • Prepare a password‑protected Black‑Friday landing page and plan a midnight‑cart reminder email.
  • Configure abandoned‑cart flows to trigger within 15‑60 minutes.
  • Create a one‑click upsell offer and project a 30‑40% uptake.
  • Add a $10 mystery gift card (January‑only) to each Black‑Friday cart.
  • Plan a plain‑text founder email for the middle of the sale and schedule unusual send times.
  • Prepare a post‑Black‑Friday Cyber Monday‑only offer for newly acquired shoppers.

  October 16, 2026

• Marketing & Lead Gen: ChatGPT Codex Side Hustles That Can Pay a Full Time Income

  Watch on YouTube: https://www.youtube.com/watch?v=Fcae2kekuLc

  Channel: Patrick Dang

  Intro

  Patrick Dang’s video challenges the common narrative around AI side hustles by pointing out that most tutorials focus only on tool usage and ignore the critical step of acquiring clients. He argues that without a client‑acquisition strategy, even the most advanced AI tools cannot generate reliable income. The video then presents seven specific services that combine AI capabilities with human judgment, each evaluated on four criteria: ease, demand, repeatability, and the need for human judgment. Free resources and a three‑day live training are offered to help viewers move from learning to earning while keeping a full‑time job.

  What the Video Covers

  Patrick begins by critiquing generic AI hustle advice, quoting his observation that many of these ideas are “just a waste of time.” He introduces his four‑criteria scoring system to assess each opportunity. The seven services discussed are:

  • LinkedIn ghostwriting combined with direct‑message (DM) setting
  • Webinar sales partner
  • AEO (AI search optimization)
  • Community management
  • YouTube agency
  • AI website building
  • Instagram DM setting

  For each service he provides an income range, a score out of five for each criterion, and a brief note on the skill set required. He also mentions his own results—over $100,000 per month in revenue—and cites student examples such as Brandon’s $10,000 monthly gain after 30 days and Sandy’s $50,000 monthly outcome.

  Step‑by‑Step Walkthrough

  To turn any of the seven services into a paying side hustle, Patrick outlines a repeatable process:

  1. Select a service that matches your current skill level and the local market demand.
  2. Use the free “business idea generator” skill to refine your offer and positioning.
  3. Deploy the “list builder” skill to identify prospects—founders, marketers, or businesses that need the service.
  4. Create a tangible sample using Codex (for LinkedIn posts, webinar slides, or website copy) and record a short Loom video showcasing the work.
  5. Reach out to prospects with the Loom video, emphasizing how the sample addresses their specific pain point.
  6. Close the deal by negotiating a fee structure (fixed fee, commission, or profit share) based on the service’s scoring.
  7. Deliver the work, blending AI output with human judgment to avoid “AI slop,” and request a testimonial or referral for repeat business.

Patrick stresses that the human judgment component is essential—clients want copy that sounds authentic, not robotic.

Tools and Numbers

The video names several tools and provides concrete financial ranges:

• ChatGPT and Codex as the core AI platforms
• Loom video for outreach demonstrations
• Business idea generator skill (free)
• List builder skill (free)
• LinkedIn ghostwriting + DM setting: $1,000–$3,000 per month for ghostwriting, $1,000 base plus 5‑10% commission for DM, combined potential up to $5,000 per client per month
• Webinar sales partner: $1,000–$5,000 fixed fee plus 10‑50% profit share
• AEO (AI search optimization): $1,000–$8,000+ per month
• Community management: $1,000–$5,000 per month per community
• YouTube agency: $2,000–$15,000 per project
• AI website building: $200–$2,000 per page
• Patrick’s own revenue: over $100,000 per month
• Student results: Brandon $10,000 per month after 30 days; Sandy $50,000 per month; Patrick’s channel has 400,000 subscribers, Sandy’s channel 70,000 subscribers

Caveats / Hype Check

most of these side hustles that people are talking about online are just a waste of time

AI is kind of like what the bicycle is for walking

human judgment is very important in copywriting because nobody wants to sound like AI slop

if you’re putting this stuff together and reaching out to founders, they’re going to be like, ‘Dude, this guy really got it.’

success is never guaranteed

Patrick acknowledges that the income figures presented are optimistic possibilities, not promises. He notes that results depend on effort, niche selection, and the ability to acquire clients. The free gifts and the three‑day live training may serve as entry points to paid offerings, so viewers should evaluate whether the time investment aligns with their goals.

Concrete Next Actions

Based on the video’s advice, the following steps can be taken immediately:

• Download the business idea generator skill from the link in the description and install it into your ChatGPT/Codex environment.
• Install the list builder skill to start building prospect lists for webinar sales partner or LinkedIn ghostwriting offers.
• Use Codex to draft a few sample LinkedIn posts in a founder’s voice, then record a Loom video walking through the samples.
• Sign up for the free three‑day live training (link in description) to learn client acquisition scripts and sales techniques.
• If you need a tailored plan, book a call with Patrick’s team for a custom AI‑business strategy.
• Begin outreach to founders of YouTube channels with fewer than 1,000 subscribers, offering YouTube agency services backed by your sample work.
• Approach businesses already investing in SEO and propose an AEO audit as an add‑on service, highlighting the low‑supply, high‑demand nature of AI search optimization.