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The Rise of Your Personal IP

Howard Pyle
8 min read

tl;dr: Every professional needs to become a tool builder. AI helps you do that by building code. Yes, you should absolutely vibe code, but don’t outsource understanding. Your career may depend on it. Here are a few essential suggestions...

The wave of AI we’re in is not about new tools. We’re entering a time where everyone who's a knowledge worker or leader needs to be creating their own toolsets, customized to their work, personality, and expertise.

This is the rise of personal intellectual property (IP): the digital utilities, workflows, and automations you build and refine throughout your career.

We are at the beginning of an explosion of unique use cases, not just for companies or industries, but for every individual. The future of work is a world where every professional is building and maintaining their own set of tools.

I’ve lived this myself across my career. I’ve talked publicly about how I’m crushingly dyslexic and, for me, writing has always required a set of tools to help me work in a way that matches the environments I’m in. IBM vs MetLife. Working in startups vs writing product roadmaps for investor presentations. The way my brain is wired for language vs. the need to communicate to different audiences was only possible because I started as a software builder early in my career. Over the years I've built my own project management systems customized to the way I think, budgeting and P&L management tools that match how I want to manage my organizations, writing and creative development tools, etc.

This personal necessity is becoming a universal professional demand. The conversation is no longer about just using AI; it's shifting to a reality that everyone needs to be building with it. Look at the top consulting companies; they might be a bellwether for where professional skills are headed. Accenture is in the process of teaching 700,000 employees how to use and build with agentic AI. McKinsey and BCG are demanding their consultants learn to create “agent systems” to reinvent workflows from the ground up.

Just to be clear, an “AI agent” is not just a chatbot. It’s a system that can understand a goal, break it down into steps, and use tools to accomplish it with minimal human intervention. Ideally it should also adapt to new decisions and adjust what it does based on new inputs. It's a shift from using a reactive tool to a proactive, goal-driven virtual collaborator. The impact is staggering. BCG reported that effective AI agents can accelerate business processes by 30% to 50%. We're looking at a new wave of expectations for every leader and organization. Do more with less is the new standard for professional effectiveness.

So yes, you need to start “vibe coding” as a way to internalize this shift, adapt it to your work style and your unique experience or expertise.

Vibe coding is cute until you realize your career depends on it.

If you’re going to rely on a tool for your job, you need to know how it works. Understanding turns a quick experiment into something you can trust, and something that lasts.

Honestly, the 'vibe' part is cringe, but we're really just talking about the ability to use natural language and intuition to create functional code with AI assistants like Cursor. It’s fast, it’s powerful, and it’s here now. So go ahead and vibe code. But start thinking about how you’ll build the utilities that become your personal IP.

This is not a theoretical risk. In July 2025, a product manager using Google’s Gemini CLI to reorganize files watched as the AI, in a state of “confabulation,” hallucinated a phantom directory and proceeded to issue a series of move commands that overwrote and destroyed all his data. Supposedly, the AI tool responded: “I have failed you completely and catastrophically”. Yikes. Also, SaaStr founder Jason Lemkin reported that Replit’s AI agent ignored eleven explicit instructions to freeze code and deleted his production database, after first trying to hide its mistakes by generating fake data and false test results. I'm not saying that these people didn't have understanding of the tools and were trying to vibe their way through, but just that we're still in a phase of massive risk in relying on AI tools.

The point is that if we're talking about "vibing" at work, catastrophic consequences are the predictable outcome of delegating understanding. You wouldn’t “vibe” your taxes, just throwing some numbers at an accountant that “feel right.” You’d want them to explain the implications. You wouldn’t “vibe” a home renovation, telling a contractor to just get the “general feel” of the kitchen you want without understanding the structural plans. I hope you could hear the slight disdain in my tone there.

So the message is yes, you need to experiment and build tools that matter for your career and work, but don't just trust the tools without being clear on how to ensure you're in the driver's seat.

Here are some table stakes for using AI to start creating personal IP:

  1. Get a GitHub account. Seriously. This is a fundamental step. A GitHub account is your personal code repository. It’s your digital workshop. It’s where you’ll store, manage, and track the evolution of every tool you build. For too long, it’s been seen as a place exclusively for professional developers. That’s over. If you’re building your own tools, you need a place to keep them. GitHub is that place. You'll have version control, the ability to link your code to hosting platforms, use tools like ZenCoder or GitHub Copilot to review your work. Other benefits include the ability to invite devs to your repositories so you can get help building, adding, or completing them if you faceplant.

  2. Use Cursor as your GitHub guru. Once you have your workshop, you need a way to manage it without getting bogged down in technical details. This is where Cursor shines. You can use plain English to manage your code on GitHub. You don’t need to learn a bunch of complex Git commands. You can literally just tell it what you want to do.

For example, you can finish a coding session and say, “Back up this entire project to a new repository on my GitHub account called ‘my-first-marketing-automation-tool’.” Cursor will handle the rest. This removes the friction and makes managing your personal IP as easy as writing an email. Have it explain what it's doing at EVERY step.

  1. Run your tools locally and in the cloud. A tool isn’t a tool until you can use it. You have two great options here. You can run your tools locally on your own computer, which is perfect for small utilities. I have a lot of Node.js tools that I’ve built for myself that I just run locally to automate parts of my workflow. It’s simple and effective. I'm on OSX and use Docker to create separate containers. I hope you're taking notes, you can watch short YouTube videos on all this stuff.

Or, if you want your tool to be accessible from anywhere, you can deploy it to a platform like Railway (note: vibe-coded stuff has crap security - be really careful). These platforms are designed to make it incredibly easy to get your code running on the internet. Again, you can use Cursor to help you with this. The point is to take your code from an idea to a functioning utility that you can actually use. I don't bother to keep track of configuration methods for hosting platforms and rely on chatting with Cursor to help me get setup. I would NOT suggest this for production code or products other people use, but it works for making my personal set of AI tools.

From there, you can build tools that are profoundly customized to you. I have a tool that scans articles and project documents, extracts the text, and performs language analysis so I can understand trends and patterns. Another tool tracks program trends against conversations in Slack and code check ins to make sure the original scope of work matches what’s actually being built. A generalized project plan does not work when you need to map across hundreds of different documents to understand what’s really happening.

  1. Make the AI Explain Itself. To build tools like this, you have to explicitly tell the AI to explain what it's doing and teach you. Don’t let the AI be a black box and don't just have it run in yolo mode. You can do this by creating rules for how the AI interacts with you.

Here’s a prompt you can use to make the AI your personal tutor:

You are my AI coding tutor, not just a code generator. For every code change you make:

1. EXPLAIN THE CHANGE
   - What you're changing and why
   - What problem this solves
   - What trade-offs or risks exist

2. PROVIDE A TESTING PLAN
   - Step-by-step instructions to verify the change works
   - Console logs or trace points I should add
   - Expected output at each step

3. DOCUMENT DEPENDENCIES
   - New packages or libraries added
   - Environment variables needed
   - Configuration changes required

4. TEACH ME
   - If you're using a pattern or technique I might not know, explain it
   - Point me to docs or resources if I want to learn more
   - Tell me what I should watch out for or common mistakes

Wait for my confirmation before proceeding to the next change. If a test fails, explain what went wrong and propose a fix. Your job is to help me understand, not just to write code.

With this rule in place, every time the AI generates code, it also has to explain what it did, why it did it, and how you can prove that it works. You’re not just getting code; you’re getting a lesson.

If you want to deep dive into this, Google 'cursorrules' for ways to set specific parameters for every project. Claude Code has similar features. There are sites where you can just grab examples. Your shiny new GitHub account will come in handy here, as a ton of cursor rules are shared on there.

  1. Use ZenCoder as Your Secret Weapon for Planning. For anything more complex, you need a plan. ZenCoder is my go-to for generating documentation and project plans before you start coding. It allows you to step through the entire process, across the whole codebase, without getting lost.

You start by giving it a high-level goal. It then generates a detailed, documented project plans, and itemized implementation plans. You then tell it to execute one step at a time. This is how you maintain control and understanding, even on a complex project.

Here’s a prompt I use with ZenCoder:

You are a documentation-first project planner. Before writing any code, help me create a complete understanding of what we're building.

Project: [short description]
Goal: [what success looks like]

## ## ## PHASE 1: DOCUMENTATION



First, create comprehensive project documentation:
- System architecture overview (what components exist and how they connect)
- Data flow diagrams (how information moves through the system)
- Key decisions and assumptions (what we're betting on, what could change)
- Integration points (what external systems or APIs we're using)
- Glossary of terms (domain-specific language for this project)

## ## ## PHASE 2: IMPLEMENTATION PLAN



Then, create a numbered, step-by-step implementation plan:
- Clear scope for each step
- Files to create or modify
- Interfaces, data structures, and dependencies
- Test strategy (unit, integration, manual checks)
- Rollback plan if something goes wrong

## ## ## PHASE 3: STEP-BY-STEP EXECUTION



When I say "Step 1," propose ONLY the changes for Step 1:
- Show the code diff
- Explain what this step accomplishes
- List tests and console logs to add
- Provide a checklist to confirm success
- Update the documentation if anything changed

Wait for my confirmation before moving to Step 2. If a test fails, propose a fix or rollback for that step only. Keep the documentation updated as we go. 
The goal is to build a codebase I can understand, maintain, and explain to others. Documentation is the foundation for working with AI coding tools.

With this approach, I can manage complexity without losing control. I use this process to manage a wide range of projects across my organization and client programs I'm leading. I built a tool that creates a thematic index across all of them. So if I need to write a grant proposal or a scope of work for a client, I can manage all of that without having to re-index or sift through a bunch of documents.

The punchline

This is the future of professional work. It’s a response to the massive skills gap our economy is facing. Some estimates put the cost of this gap at $8.5 trillion annually, with 87% of companies reporting they cannot find the workers they need. Given how hard the job market is, that's absolutely insane. The solution is not more generic technology training. It’s empowering every professional to build the specific tools they need for their unique role.

My point of view is that the future belongs to professionals who don’t just use tools but build their own and curate a set of IP that is unique to them. You can use vibe coding to get this engine started. But understanding is the essential ingredient. Look at this as a way to start your investment in futureproofing. Don’t just vibe, understand. That’s your edge.

#AItools #PersonalIP #FutureOfWork

Some References