Woods challenges claims about enormous AI productivity gains when the saved time is spent studying more tools or producing inconsequential outputs. He argues that adoption should be evaluated through business outcomes such as revenue, profit, retention, customer satisfaction, and competitive position.

Time saved is not automatically business value
Tool experimentation can become disguised procrastination
AI outputs should connect to measurable outcomes
Sophisticated systems may still be low-leverage work

“They've actually gained no business value from what they are doing.”
Geoff Woods

“Is it showing up in revenue? Is it showing up in profit? Is it showing up in better retention or better CSAT scores?”
Geoff Woods

#ai-hype#business-value#productivity#outcomes

Myth Buster

AI Turns Creatives From Instrument Players Into Conductors

Woods rejects the idea that AI necessarily destroys creativity. He argues that creative value shifts from manually producing every component toward casting a vision, choosing expert perspectives, combining disciplines, directing revisions, and orchestrating the final result.

Creativity includes vision and direction, not only manual production
AI can combine analytical and expressive roles
The human selects roles and defines the desired result
Creative scope can expand across disciplines

“Your creativity is the ability to cast the vision for where you want to go, to be descriptive with AI on the types of things…”
Geoff Woods

“You're no longer the player of one instrument. You're now the conductor, front and center, who's waving the baton”
Geoff Woods

#creativity#ai#creative-direction#orchestration

Hot Take· 2

Hot Take

Building an Agent Is Usually the Wrong Place to Start

Woods describes agentic AI as roughly the eighteenth domino in an adoption sequence, not the lead domino. Most people should first learn to identify meaningful use cases, communicate effectively with AI, and retain judgment before automating processes.

Agent building can become a solution looking for a problem
Foundational AI habits should precede automation
An agent should improve high-value work or remove burdensome low-value work
Automation matters only when it creates measurable leverage

“Agentic AI is like the 18th domino.”
Geoff Woods

“If we want to talk about agents, you have to realize you don't need an agent. That's a solution looking for a problem.”
Geoff Woods

#agents#ai-adoption#automation#leverage

Hot Take

AI-Driven Companies Will Operate Like Networks and Swarms

Woods argues that traditional hierarchies built around taking repetitive direction from a boss are poorly suited to an AI-driven economy. He expects stronger organizations to communicate a mission and strategy, match employees' distinctive strengths to high-value work, and give them agency to assemble human and technological resources around outcomes.

Repetitive direction-following resembles machine behavior
Leadership should communicate vision and strategy clearly
Employees need a defined center of gravity
Individual strengths should align with high-value responsibilities
Agency replaces excessive top-down task assignment

“In an AI-driven world, AI-driven organizations are for far more like networks and swarms rather than this hierarchy of top-down.”
Geoff Woods

“But now I think you're gonna move to everybody becomes a department chair.”
Cody Sanchez

#organizations#leadership#future-of-work#agency

Explainer· 3

Explainer

Your Undocumented Work Knowledge Is an Automation Opportunity

A job can be viewed as skills applied through repeatable processes. Woods recommends having AI interview employees about those skills and processes, then capturing the knowledge in markdown so an agentic platform can use it without the employee being present.

Jobs consist of skills and processes
Undocumented tacit knowledge blocks replication
AI interviews can turn experience into documentation
Markdown provides a model-friendly operating format
Agents can reference documented procedures to reproduce work

“Your job is just skills you apply and processes you follow.”
Geoff Woods

“Use AI to interview you to create that documentation in markdown format.”
Geoff Woods

#documentation#agents#knowledge-management#markdown

Explainer

AI Changes the Value of Skills More Than It Erases Whole Jobs

Woods frames technological disruption as a repricing of the skills and processes contained within jobs. Repetitive output generation becomes machine work, while strategic thinking, problem solving, communication, collaboration, and creativity become more valuable human contributions.

A job is a bundle of skills and processes
Technology raises the value of some capabilities and lowers others
Routine reports and document generation are increasingly machine-based
Strategic and interpersonal abilities gain importance
Entry-level development paths may be disrupted

“What it did is it made the value of certain skills and processes skyrocket in value, and the value of certain skills and processes plummet…”
Geoff Woods

“The things that I think are going to matter from a human skill standpoint moving forward, the ability to think strategically, to solve problems, to…”
Geoff Woods

#future-of-work#skills#jobs#automation

Explainer

How AI Can Weaken—or Intensify—Your Thinking

Woods describes passive acceptance of AI answers as a major cognitive risk because thinking behaves like a muscle. He counters that risk with deliberate pen-and-paper thinking, model-led questioning, and continued human judgment after the model generates an answer.

Accepting answers without evaluation outsources thinking
Questions can raise cognitive demand
Independent problem solving preserves capability
Pen-and-paper work creates original context before AI enters
AI should augment a thinking process rather than replace it

“Most people are using AI in a way that it is replacing their ability to think.”
Geoff Woods

“So the guy who wrote the book about AI uses pen and paper still because I sometimes need to sit down and really process my…”
Geoff Woods

#cognition#critical-thinking#ai-risk#mindset

Tool· 5

Tool

Why Speech-to-Text Produces Better AI Context Than Typing

Woods argues that speaking is becoming a foundational AI skill because people naturally omit and edit information while typing. Unstructured speech can give a model far more context without requiring polished punctuation, paragraphs, or perfectly organized thoughts.

Typing encourages premature editing
AI does not require polished sentence structure
Messy spoken thoughts can contain valuable context
More context generally improves the result

“And with AI, context is king. So when you type, you naturally edit yourself.”
Geoff Woods

“AI can handle all of this. And the more you give it the better.”
Geoff Woods

#speech-to-text#context#productivity#ai-skills

Tool

Two Sticky Notes That Turn AI Learning Into Daily Behavior

Woods uses two physical prompts on his desk to bridge the gap between attending an AI workshop and changing behavior. One asks how AI could help with the current activity, while the other displays CRIT as an immediate reminder of how to begin.

Environmental cues turn intentions into behavior
The first note connects AI to current work
The second note removes prompt-starting friction
A financial review triggered the creation of an automated AI CFO

“What's missing is a trigger, a trigger in their environment that will cause them to change.”
Geoff Woods

“One sticky note said, How can AI help me do this?”
Geoff Woods

#habits#behavior-change#sticky-notes#ai-adoption

Tool

Train an AI Writing Persona With 20 to 50 Real Samples

For writers seeking greater output without losing their voice, Woods recommends providing a substantial set of emails and prior writing as context. AI can then interview the writer and produce a reusable markdown style guide, though the resulting prose still requires human editing.

Use 20 to 50 emails plus representative writing samples
Ask for a communications and prompt-engineering perspective
Require an interview before generating the style guide
Store the voice specification in markdown
Expect residual style failures even with strong instructions

“first I would feed it 20 to 50 emails. I would feed it past writing samples of what you would say is your work.”
Geoff Woods

“And then your task is to create the file in markdown format that would be my voice, that if AI ever were to write anything…”
Geoff Woods

#writing#voice#style-guide#prompting

Tool

Turn Weekly Customer Conversations Into an Executive Podcast

Woods describes a voice-of-customer pipeline that captures highlighted portions of recorded customer calls, posts them to Slack, and has an agent assemble the week's material into a podcast. He listens at the gym before product-market-fit meetings, turning distributed conversations into a recurring executive learning channel.

AI note takers capture customer conversations
Employees highlight valuable customer language
Snippets flow into a dedicated Slack channel
A weekly agent converts the collected material into a podcast
Leadership consumes the digest before product meetings

“When I wake up Wednesday morning by 5 a.m. when I'm at the gym, I'm listening to an actual podcast of everything my customers have…”
Geoff Woods

“That's how I prepare for our product market fit meetings.”
Geoff Woods

#voice-of-customer#podcast#automation#product

Tool

Build an AI Sales Coach From Calls and Conversion Outcomes

Instead of relying only on scripts and occasional role-play, Woods proposes analyzing a large set of recorded calls alongside conversion data. The resulting evidence-based sales standard can power an agent that reviews each new call and sends coaching feedback within minutes.

Combine call transcripts with actual conversion outcomes
Compare claimed scripts with observed successful behavior
Derive an evidence-based ideal sales script
Encode the standard as sales-coach instructions
Deliver feedback before the salesperson's next call

“Why don't you feed AI the last 100 sales calls and the conversion data as well as what you think your script is”
Geoff Woods

“slacks them on what they did well, what they need to change within the next five minutes before their next sales call.”
Geoff Woods

#sales#coaching#call-analysis#agents

Takeaway· 2

Takeaway

The Writing Tells That Make AI Slop Obvious

The speakers identify recurring signs of weak AI-assisted prose: excessive em dashes, formulaic contrasts, grand introductions about an era or transformation, hype, verbosity, and paragraphs that contain many words but little message. These are symptoms of allowing AI to lead rather than editing it into a human point of view.

Em dashes are a common stylistic tell
Formulaic phrases make writing feel generated
AI defaults can be verbose and hype-driven
Fluff signals a lack of human editorial leadership
A style guide reduces but does not eliminate failures

“It's it's a little verbose, hypey, inauthentic.”
Geoff Woods

“I can also just tell when I'm reading and there's a lot of words that aren't delivering a message.”
Geoff Woods

#ai-writing#editing#ai-slop#style

Takeaway

Centralize Business Data Before Building Divisional Agent Swarms

For companies considering centralized or divisional AI systems, Woods recommends first maximizing useful data centralization. The harder questions concern permissions, structure, model-friendly file formats, and empowering employees to document their own work—not proliferating agents before the organization is ready.

Most companies are not ready for advanced multi-agent architecture
Centralized data is a strategic asset
Access controls should reflect divisional needs
Data structure and file format affect model usability
Employee-created process documentation enables later automation

“I want as much data centralized as possible because it's a massive, massive asset.”
Geoff Woods

“The question is what access to what data, which is that's when you can look at divisional stuff like that.”
Geoff Woods

#data-architecture#agents#governance#enterprise-ai

Frameworks in this episode

20% Priority Filter

AI Board Design Method

CRIT Prompting Framework

Thought-Leader Revision Loop

Insights & moments

⚡Myth Buster· 2

Saving Six Hours With AI Does Not Mean You Created Value

AI Turns Creatives From Instrument Players Into Conductors

◆Hot Take· 2

Building an Agent Is Usually the Wrong Place to Start

AI-Driven Companies Will Operate Like Networks and Swarms

✶Explainer· 3

Your Undocumented Work Knowledge Is an Automation Opportunity

AI Changes the Value of Skills More Than It Erases Whole Jobs

How AI Can Weaken—or Intensify—Your Thinking

✦Tool· 5

Why Speech-to-Text Produces Better AI Context Than Typing

Two Sticky Notes That Turn AI Learning Into Daily Behavior

Train an AI Writing Persona With 20 to 50 Real Samples

Turn Weekly Customer Conversations Into an Executive Podcast

Build an AI Sales Coach From Calls and Conversion Outcomes

▲Takeaway· 2

The Writing Tells That Make AI Slop Obvious

Centralize Business Data Before Building Divisional Agent Swarms

Myth Buster· 2

Hot Take· 2

Explainer· 3

Tool· 5

Takeaway· 2