By playing, you agree to uListen's Terms and Privacy Policy and YouTube's Terms of Service.

BigDeal by Codie Sanchez

How to Use AI to Make Money, Grow Your Business, and Be More Productive | Geoff Woods

My new book Own Or Be Owned is out now! I wrote Own or Be Owned to answer one question: how do you make more money, less miserably?

Geoff WoodsguestCodie Sanchezhost

Jul 15, 20261h 5mWatch on YouTube

Summaries, chapters, transcripts, and FAQs on this page are made by uListen, not YouTube.

CHAPTERS

Jump to publisher timestamps

Chapter summaries

AI as a strategic thought partner: aiming it at what matters
Geoff Woods frames the biggest unlock as using AI as a thought partner rather than an assistant. He and Codie Sanchez set up the core theme: AI helps most when it improves strategic thinking and targets the highest-impact problems, not low-stakes tasks.
- •Geoff Woods says AI’s best use is as a thought partner, not an assistant
- •He argues strategic thinking is the difference between growing a business or going out of business
- •Codie Sanchez tees up concerns about AI hurting creativity and creating obvious “AI slop”
- •Geoff Woods introduces the idea that creatives become “conductors,” not just individual contributors
Simulating a hostile board: the AI board meeting turnaround
Geoff Woods shares a story about a venture-backed CEO facing a hostile board and possible termination. He walks through how the team used AI to interview them, build personality profiles for board members, and simulate board reactions to improve the deck and meeting dynamics.
- •A CEO describes recurring hostile board meetings consuming executive time and threatening leadership jobs
- •Geoff Woods says the opportunity is to treat whatever problem you’re solving as the AI use case
- •He uses CRIT to have AI interview the team and generate personality profiles for each board member
- •They test the AI board by uploading a prior deck and asking for predicted board feedback
- •They refine profiles using a meeting transcript from an AI note taker and the relationship improves dramatically
The CRIT framework explained: Context, Role, Interview, Task
Codie Sanchez asks for a breakdown of CRIT so listeners can get better outputs than generic prompting. Geoff Woods explains each component and emphasizes that the interview step—AI asking you questions—is the biggest lever for depth and quality.
- •Codie Sanchez highlights the problem of generic outputs that scream “AI”
- •Geoff Woods explains CRIT as a structured way to communicate effectively with AI
- •Context: provide detailed situation-specific information because AI doesn’t know your business
- •Role: specify the expert persona in vivid, precise terms
- •Interview: have AI ask one question at a time to extract deeper context and elevate thinking
- •Task: define the output you want once the model has sufficient context
The 80/20 mistake and the three skills to avoid being replaced
Geoff Woods argues most people apply AI to low-leverage tasks that don’t change outcomes. He lays out three foundational skills: choosing a high-impact use case, communicating well (CRIT), and staying the thought leader through skepticism and iteration.
- •Geoff Woods says people use AI on “80% tasks” that only drive “20% value,” like emails or using it as Google
- •He shares his own early mistake of using AI for better emails while his real strength was asking leaders questions
- •He describes three required skills: identify a meaningful 20% use case, communicate effectively, and remain the thought leader
- •He warns against trusting AI outputs as final; treat them as a first draft and refine through feedback loops
Debt restructuring saved by AI: the “Saving Face Consortium” story
Geoff Woods recounts a workshop where AI helped a manufacturing CEO facing bankruptcy due to a debt structure and cultural dynamics with a Japanese lender. Using CRIT, AI asks non-obvious questions and generates strategies that restore hope and create momentum toward a solution.
- •A manufacturing CEO says the company may go bankrupt without debt restructuring
- •The lender’s board refuses because they fear losing face in Japanese society
- •Geoff Woods uses CRIT with an investment banker role to generate strategies
- •AI asks a pivotal question about relationships with respected Japanese executives
- •AI proposes a strategy labeled the “Saving Face Consortium,” aiming to preserve face while restructuring debt
- •The CEO reports renewed hope and later says progress is being made
Speech-to-text, “what else?” context depth, and making AI challenge you
After the sponsor break, Geoff Woods shares practical tactics for getting higher-quality results. He emphasizes speech-to-text to increase context, repeatedly pushing for more details, and having AI switch personas to stress-test ideas and expose assumptions.
- •Geoff Woods calls speech-to-text a key skill because it allows richer, less-filtered context
- •He recommends repeatedly asking “What else?” when building context to avoid shallow prompts
- •He describes “playing AI against itself” by switching roles to challenger and customer personas
- •Codie Sanchez notes AI can be overly agreeable; Geoff Woods suggests instructing it not to just agree
- •He explains adding these behaviors into a tool’s custom instructions so they persist across prompts
Sticky-note triggers and building an agentic AI CFO (without starting there)
Geoff Woods describes how he uses environmental triggers to drive consistent AI habits: sticky notes prompting “How can AI help me do this?” and “CRIT.” He then shares how a CRIT prompt on financial statements evolved into an automated AI CFO workflow—while warning most people should master fundamentals before “agents.”
- •Geoff Woods says behavior change needs a trigger, not just a great workshop or keynote
- •He uses two desk sticky notes: one to prompt AI usage and one listing CRIT
- •He demonstrates a CRIT prompt that turns AI into a strategic CFO reviewing financials and interviewing for context
- •He says he later built an agentic AI CFO that analyzes finance team materials and posts insights to Slack
- •Codie Sanchez shares that building a first agent can feel intimidating but gets easier with iteration
- •Geoff Woods cautions agentic AI is like the “18th domino” and shouldn’t be the starting point
How to identify your highest-leverage work and what skills survive AI shifts
Geoff Woods gives a simple analog method to separate 20% priorities from everything else. He then argues technology shifts change which skills are valuable, and warns that if AI can do a key task better, humans should stop owning it and move up the value stack.
- •Geoff Woods suggests writing every weekly obligation on paper and starring the true 20% items
- •He prioritizes further by choosing the single most valuable item if only one can be done
- •He says jobs are skills and processes; tech shifts raise some and crush others in value
- •He argues that if AI is already half as good at a task, it may soon surpass you
- •He lists human skills he believes will matter: strategic thinking, problem solving, communication, collaboration, and creativity
The entry-level squeeze and the shift from hierarchy to agency at work
Codie Sanchez and Geoff Woods discuss which kinds of work are most exposed and why entry-level roles are especially vulnerable. Geoff Woods argues AI-driven organizations will look less like hierarchies and more like networks, requiring employees to own outcomes rather than wait for instructions.
- •Geoff Woods predicts frontline customer service and document-heavy legal work are early areas of automation
- •He says entry-level work shrinking creates a workforce gap because people lose “reps” for advancement
- •He says he’d avoid roles built around repetitive direction-taking in traditional hierarchies
- •He describes future orgs as networks/swarms where leaders cast vision and people apply their strengths with agency
- •Codie Sanchez contrasts “daycare employees” with “department chair employees” who have their own center of gravity
Owning your job and creating an AI-driven leadership culture
Geoff Woods shares a formative lesson about fully owning your responsibilities and not outsourcing them upward. He explains how leaders can build a culture where employees bring prioritized plans, and leaders coach the thinking rather than hand out tasks—addressing objections that this expectation is “toxic.”
- •Geoff Woods recounts being told: if you give your boss pieces of your job, you may not have one
- •He argues employees should own 100% of their job, including follow-through without reminders
- •He describes a cultural expectation: employees identify their 20% priorities and bring a plan to one-on-ones
- •He clarifies leaders must still set goals and expected outcomes, while employees propose how to get there
- •He shares an example of training an executive assistant to order agendas by priority and drive meetings
Creativity, conducting AI, and generating world-class messaging with persona flips
Geoff Woods responds to concerns that AI kills creativity by reframing creativity as vision-setting and role selection. He describes using CRIT to develop solutions to a huge business problem and then flipping AI into a “Steve Jobs” persona to draft a manifesto that energized executives.
- •Codie Sanchez raises criticism that AI kills creativity; Geoff Woods asks whether AI could enhance it instead
- •He describes solving a major C-suite problem using CRIT and generating viable solutions quickly
- •He demonstrates persona flipping to produce a CEO-ready manifesto intended to reduce fear and energize teams
- •He says creatives shift from playing one instrument to conducting an orchestra of expert personas
- •He emphasizes creativity in defining roles, tasks, and direction—not merely drafting text
Building a writing persona and spotting “AI-sounding” output
Codie Sanchez asks for a tactical method to make AI write in someone’s voice. Geoff Woods explains how to feed writing samples, generate a markdown style guide via CRIT, and then iteratively refine—while both share tells that reveal low-effort AI writing.
- •Geoff Woods suggests feeding 20–50 emails or writing samples as context to build a voice persona
- •He recommends having AI create a markdown style guide that can be embedded into future workflows
- •Codie Sanchez and Geoff Woods discuss common giveaways like em dashes, hypey phrasing, and fluff
- •Geoff Woods reiterates treating outputs as a first draft and iterating with specific feedback
- •They note even strong setups still require human judgment and edits
Creating an AI board for guidance: skills-based personas and a “future self” advisor
Geoff Woods explains why he built an AI board: as a founder without investors, he wanted on-demand counsel tailored to his blind spots. He describes feeding vision, plans, culture documents, and personality profiles into CRIT to identify missing skills and then building personas—including a future version of himself.
- •Geoff Woods says an AI board helps when it’s “lonely at the top” and you want advice on demand
- •He describes feeding long-term vision, business plan, culture docs, and personal strengths/weaknesses into CRIT
- •He uses the interview step to surface strengths and weaknesses he may be unaware of
- •He builds board members around missing skills and sets strict rules on what they can and can’t advise on
- •He names several personas on his board and says his most valuable board member is his future self
The overlooked risk: mental atrophy, and how CRIT increases cognitive demand
Geoff Woods argues the biggest AI risk is cognitive decline from outsourcing thinking. He contrasts passive consumption of AI answers with CRIT-driven workflows that force deeper thinking through context-building, creativity in role definition, and judgment in refinement.
- •Geoff Woods says many people use AI lazily, letting it replace their thinking muscle
- •He warns that accepting answers without skepticism shifts “thinking leverage” away from the human
- •He argues CRIT increases cognitive load: recalling context, creatively defining roles, answering interview questions
- •He suggests monitoring whether you can still solve problems without AI as a personal check
- •Codie Sanchez shares an example of deliberately thinking first before feeding work into AI
Sales and customer insight agents: voice-of-customer podcasts and real-time coaching
The conversation turns to practical company applications, especially in sales and customer learning. Geoff Woods shares two implementations: capturing voice-of-customer highlights into a weekly synthesized podcast, and using call transcripts plus conversion data to build an AI sales coach that gives immediate feedback.
- •Codie Sanchez asks about centralized vs decentralized AI “brains” in companies; Geoff Woods says most aren’t doing it
- •Geoff Woods emphasizes centralizing data and structuring it in formats models can use, like markdown
- •He shares a voice-of-customer workflow: highlight moments in calls, send snippets to Slack, compile into a weekly podcast
- •He outlines training sales with AI: feed call transcripts and conversion data to derive an ideal script
- •He describes an agent that reviews transcripts and messages coaching within minutes; Codie Sanchez says similar tooling helped an underperforming rep become a top closer
The 30-day CRIT challenge: one daily habit to change how you work
To close, Geoff Woods gives a single action: write one strategic CRIT daily for 30 days and iteratively refine outputs without trusting first drafts. He argues this practice helps people “see color,” enabling first-principles thinking about processes and what an AI-driven organization could be.
- •Geoff Woods recommends writing CRIT once a day for 30 days on something that matters
- •He repeats the loop: don’t trust the answer; specify what you like, dislike, and what to change
- •He says consistent practice reshapes how you see processes and unlocks more creative approaches
- •Codie Sanchez summarizes the message: keep it simple and focus on the one core habit rather than endless hacks
- •They wrap with thanks and a brief mention of Geoff Woods’ book and that it was purchased for employees

Publisher timestamps

Get more out of YouTube videos.

Read along on your phone, search it beside the video, or ask your favorite AI app what was said.