Latest / AI Fire Daily / #81 Robin: The AI Exodus - Stop Renting Models and Start Owning Your Own Marketing Agents

Transcript

#81 Robin: The AI Exodus - Stop Renting Models and Start Owning Your Own Marketing Agents · AI Fire Daily

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  Beat. One week, Claude feels completely safe.
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  Beat. Then ChatGPT gets better. Yeah, and then
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  limits Titan. Exactly. Your whole workflow just
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  breaks. It is an exhausting, relentless cycle.
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  Welcome to the deep dive. We are really glad
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  you are joining us today. Absolutely. Okay, let's
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  unpack this. People always ask which AI model
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  is best. They want to know who is winning this
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  week. But we are exploring something much deeper
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  today. We are looking at portable AI marketing
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  agents. Right. We want agents that work anywhere
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  you go. We are breaking down the entire agent
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  harness today. We will structure a truly portable
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  digital workspace. You will learn to move seamlessly
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  from Cloud Code to Codex. Yeah, without ever
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  starting from scratch again. Knowledge is most
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  valuable when it is applied. That is very true.
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  We live in this world of intense information
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  overload. Portability is literally professional
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  survival right now. You cannot afford platform
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  lock -in. No, things just change way too fast
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  for that. We really need to define what an AI
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  agent actually is, though. We have to establish
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  that before making it portable. An agent is not
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  just a chat bot. Exactly. People misunderstand
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  this crucial point constantly. A chat bot waits
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  for your prompt, it answers you, and then it
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  stops. It just goes to sleep. Yeah, essentially.
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  But an agent runs a loop. A continuous loop.
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  Right. It takes an action, checks the result,
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  and decides the next step. It keeps going until
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  the job is done. It is kind of like stacking
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  Lego blocks of data. That is a perfect analogy.
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  Let's look at a concrete marketing example. OK.
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  Imagine you need a weekly SEO report. A chat
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  bot needs you to paste the data. An agent just
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  pulls the live data itself. It checks the performance
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  metrics on its own. Yeah, and then it creates
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  visual charts. After that, it rates the actual
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  strategic insights. It does all of that in one
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  loop. You just give the goal and step back. But
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  does this loop make them completely autonomous,
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  or do they still need supervision? They desperately
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  need strict guidelines. The environment they
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  operate in is critical. More important than the
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  AI itself. Without a doubt. The environment is
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  everything. So the environment provides the guardrails
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  to keep the loop on track. Right. And without
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  that, they just hallucinate. OK. So we need these
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  digital guardrails. Here's where it gets really
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  interesting. We have to understand the model
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  versus the harness. Let's break that distinction
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  down. The model is just the raw intelligence.
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  That is your clod or your gemini. It is the brain
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  doing the thinking. Right. But the harness is
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  what makes it yours. It is the physical body
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  and the rules. Exactly. The harness holds your
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  brand voice and your files. It contains your
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  specific workflows and skills. Without the harness,
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  the model is just a blank slate. We also need
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  to talk about where these run. We have cloud
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  agents and local agents. Cloud agents run on
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  big company servers. Think of the Claude managed
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  agent. They are good for managed corporate workflows.
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  Yeah, but local agents run on your machine. Like
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  quadcode or codex? Exactly, they read your actual
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  project folders directly. But wait, doesn't running
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  locally require massive computing power? Not
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  necessarily, because the heavy thinking stays
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  in the cloud. The agent software just interacts
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  directly with your files. Got it. Cloud brain,
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  but local hands organizing your actual folders.
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  If we connect this to the bigger picture, it
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  makes sense. We need a local harness that does
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  not break. I still wrestle with prompt drift
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  myself, who spend hours writing the perfect instructions.
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  Oh, I know. And three days later, the AI just
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  completely forgets. It goes back to that robotic
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  corporate tone. Relying on internal platform
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  memory is a huge trap. Plain text files are so
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  much better. That is why the local harness has
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  five core parts. Let's walk through them. First
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  is knowledge and context. Like brand voice guidelines.
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  Right. Usually stored as simple markdown files.
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  Because plain text never really degrades. Exactly.
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  Second, we have instructions. These are your
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  strict daily rules? Yeah, your writing styles
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  and approval steps. Third, we have agent skills.
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  Which are reusable digital workflows. Think of
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  a technical landing page audit. Fourth are the
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  subagents. The specialist roles, right? Yeah,
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  like a dedicated SEO analyst. And finally, the
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  fifth part is tools. This connects the agent
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  to your marketing systems. Like your CRM or HubSpot.
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  So how do we make all these parts portable? We
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  organize them into three portability buckets.
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  Bucket 1 is fully portable. That is the plain
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  text and PDFs. Right. Any model can read those
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  instantly. Bucket 2 needs a small translation.
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  Instructions, skills, and sub -agents. Usually
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  you just rename some folders between platforms.
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  The core logic stays the same. Exactly. Bucket
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  3 is not directly portable. This requires manual
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  human intervention. These are your tools, specifically
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  your MCP connections. Let's define that. A secure
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  bridge, letting AI use your outside apps. As
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  a perfect definition, you just have to manually
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  reconnect them. How should a solo consultant
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  structuring multiple clients handle this? Inherit
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  by default and only add what is different. Keep
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  shared skills at the top level. And separate
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  folders for each client below that. Yeah, isolate
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  the specific brand context completely. Keep shared
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  tools at the top. isolate custom rules in client
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  folders. Exactly. It keeps everything so incredibly
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  clean. Beat. So we have a conceptual blueprint
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  now. Let's actually pour the concrete in Claude
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  code. You start by making a workspace folder.
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  Inside, you create a brand context folder. And
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  a marketing folder for your active channels.
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  You also need that mcp .json file. That handles
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  the secure bridges. Right. But the most important
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  file is killade .md. It is basically the agent's
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  subconscious mind. It is the overriding rulebook
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  for the folder. It tells Claude to always check
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  context first. It demands approval before changing
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  any files. Next, you install the Marketers Agent
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  Skill Pack. That gives you pre -built skills
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  instantly. Content research, copywriting, data
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  visualization. Then you create a data analyst
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  agent. It pulls your live search console data.
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  It checks the CTR and rankings. Runs the visualization
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  skill and saves the reports. How is this different
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  from just a really long prompt? A prompt vanishes
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  when the chat ends. This creates a saved, completely
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  reusable workflow. Right. You're building a permanent
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  employee, not just having a one -off conversation.
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  Exactly. One that never forgets its training.
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  Sponsor. So what does this all mean for your
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  actual workflow? Claude Code is working beautifully
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  today, but then prices change or a better model
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  drops. It is time to test the portability. We
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  move to Codex. You just open the exact same folder
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  in Codex. A Codex maps your clawed skills directly
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  to its own format. The brand context stays completely
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  identical. Only bucket three needs that quick
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  manual reconnection. You just re -authenticate
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  the secure bridge. Right. Now let's introduce
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  a new skill in Codex. A landing page audit skill.
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  We create a growth specialist agent in Codex.
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  Whoa. Beat. Imagine scaling this. It is wild.
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  It opens your home page in an actual browser.
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  It takes screenshots on mobile and desktop. It
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  checks for UX friction and confusing copy. Then
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  it outputs a formatted Word action list. Right
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  back into your local workspace. But what if we
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  want to switch back to Claude code? You use an
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  agent migration skill to sync it back. But you
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  should always back up your folders first. Always.
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  Never trust an automated migration blindly. Does
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  having two systems editing the folder cause memory
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  conflicts. Memory files definitely need careful
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  handling. If they write at the same time, it
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  corrupts. Right. You should point both to a shared
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  memory source. So keep a centralized memory bank
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  so both models share one brain. Exactly. One
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  single source of truth. Let's recap the really
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  big idea here. Stop worrying about which model
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  is smartest. It is a total distraction right
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  now. Claude code versus Codex is just a workflow
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  choice. It is not a lock -in problem anymore.
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  This raises an important question about software.
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  We usually think the platform is the product.
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  But the workspace is the real product now. The
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  models are just temporary engines running on
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  top. You just swap them out when a better one
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  arrives. Two -sec silence. I want to leave you
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  with a final thought. Your custom agents compound
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  with every single project. They get smarter and
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  adapt to you. What happens when your folder is
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  more valuable than the AI models themselves?
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  It is a highly disruptive future. The power is
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  shifting back to you. Keep exploring that profound
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  idea this week. Start capturing your unique business
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  knowledge locally. Thank you for joining us on
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  this deep dive. See you next time.