And you will know why sooner than later.

I'm not being dramatic. I'm being precise.

The pace of AI tooling evolution over the past year has been so fast that anyone who hasn't fundamentally rethought how they work is now operating at a structural disadvantage.

Think about it. Just 12 months ago, we were still copy-pasting between ChatGPT and our documents. We were manually triaging emails. We were spending hours on tasks that could now be described in one sentence and executed in seconds.

The gap between "working hard" and "working smart" has never been wider.

And it's accelerating.

In previous episodes, I showed you how to set up Claude Code and start your first project.

Today, I want to go deeper.

Not into a specific tool, but into the paradigm shift that's happening right now, and why it should fundamentally change how you think about your daily work.

I need to say this clearly because I still hear it every week: "I'm not technical enough for this."

Stop.

The entire point of what's happening right now is that you don't need coding skills anymore.

The new interface is natural language. English. German. Whatever you speak.

You describe what you want, and the AI executes it. Not as a toy demo. Not as a proof of concept. As a production-grade workflow that runs reliably.

We've crossed a threshold where the bottleneck is no longer technical skill.

It's imagination.

Can you clearly describe the problem you want solved? Can you articulate the steps of a process you repeat every week? If yes, you can automate it.

This is a fundamental shift. For decades, automation was locked behind programming languages, APIs, and developer teams. That gate is now open. Wide open.

I want to be precise about what this means in practice: You can now take a task that used to require a developer, describe it in plain English, and have it running within minutes. Not hours. Not days. Minutes.

Here's the mental model that clicks for most people:

Think of AI as having a team of infinite experts available at all times.

Need a data analyst? Done.

Need someone to draft an investor update? Done.

Need a researcher to scan 500 companies and surface the 10 that match your thesis? Done.

Need a copywriter, a scheduler, a CRM admin, a translator — all at once? Done.

The difference to 12 months ago isn't just speed. It's breadth. You're no longer constrained to one assistant that does one thing well. You have access to a generalist that operates at expert level across virtually any domain.

And the most powerful part: this team doesn't need onboarding. It doesn't need context documents. It doesn't forget what you told it last week (if you set it up right). It just works.

For investors, this changes the math on team building and operating leverage.

For founders, it collapses the time between idea and execution. For operators, it eliminates the busywork that used to consume 60-80% of the day.

So what does this actually look like in practice? Here's the framework I've been using to transform my own workflows, and it works across any use case:

Connect AI to the systems where your work actually lives: email, calendar, notes, documents, CRM, Slack, spreadsheets. This is the foundation. Without access to your real tools, AI stays theoretical.

Yes, trust and privacy, data leaks and intrusion are important to consider. And giving an access-all-areas pass to Moltbot is something different then connecting official connectors to Claude.

The good news: it has become trivially easy and access can be transparently controlled.

Most modern AI tools support integrations natively or through plugins and MCP servers. You're not building a tech stack from scratch, you're plugging AI into the stack you already have.

Not in technical language. Not in pseudocode. In plain, natural language.

"Every Monday, I need to review all inbound emails from founders, extract the company name, stage, and sector, and add them to a spreadsheet."

"Before every partner meeting, I want a 2-page summary of each portfolio company's latest metrics."

"When a new deal comes into our CRM, check if we've seen this company before, pull their latest funding data, and flag if they match our investment thesis."

That's it. That's the prompt. That's the automation.

Here's where it gets powerful. Once you've described a workflow and validated it works, you save it as a reusable skill.

The AI remembers the exact structure, format, and logic. Next time, you don't describe the problem again, you just trigger the skill.

Think of skills as your personal automation library. Each one captures a workflow you used to do manually. Over time, this library compounds. What took you hours now takes seconds.

I've been building these across my own workflows: newsletter writing, deal screening, competitive analysis, email triage, content creation. Every skill I train is a task I never have to repeat manually again.

Individual skills are powerful. Chained skills are transformative, they become workers.

Example: A new company appears in our CRM → trigger the screening skill → if it passes, trigger the research skill → summarize findings → draft an outreach email → schedule it for review.

That's five manual steps collapsed into a single pipeline. Described in natural language. Executed automatically.

The compounding effect here is real. Once you start chaining, you stop thinking in tasks and start thinking in systems.

And systems scale in a way that individual effort never can.

Run it. Review the output. Refine if needed. Then let it run on its own.

The execution loop is fast: describe → run → review → improve → automate. Each iteration makes the output better. Each automation frees up time for the next one.

Yes, initially it most likely takes longer than manually executing the task yourself.

But that’s not the point. Because if it’s a task you execute more than once, the time is well spent as for the second, third, and all the times thereafter, it executes in seconds.

That’s the true power of AI and automation.

Let me be direct about the implication:

There is no reason for you to repeat a task anymore.

If you did it once and it worked, save it. Turn it into a skill. Chain it with other skills. Let the machine handle the repetition while you focus on the work that actually requires your judgment, your relationships, and your creativity.

This isn't about replacing people. It's about amplifying what makes you valuable by removing everything that doesn't.

The investors who will outperform in the next cycle aren't the ones with the biggest teams or the most deal flow.

They're the ones who automate the commodity work and redirect their time toward the 20% that actually drives returns: building conviction, building relationships, and making non-obvious bets.

The same is true for founders. The ones who win aren't going to be the ones who hustle the hardest. They'll be the ones who automate the fastest and compound their leverage.

So obviously, AI does make us more efficient. But (as you might rightfully ask yourself) does it also make you a better investor? A better founder? A better operator?

My answer is a crystal clear YES. Hell YES!!!

Why?

Because for the first time, we can transcribe all meetings - internal and external - and get all context - structured and unstructured - into one place. Process it. And leverage it for every single request.

Ask about a company?

Yes, someone in the meeting last week (that you didn't attend) mentioned that they'd know one of the founders there. Ahh — and there's also a portfolio company that tried their product six months ago and shared feedback in a Slack thread you never saw.

That's not efficiency. That's effectiveness. That's making better decisions because you finally have the full picture, not the 10% you happened to be in the room for.

Until now, the biggest bottleneck in investing wasn't deal flow. It was information loss. Context that lived in someone's head. Notes that never made it into the CRM. Conversations that happened but were never captured. The compounding cost of all that lost signal is enormous, and invisible.

AI changes this equation fundamentally.

When every interaction is captured, processed, and queryable, your institutional memory becomes infinite. You stop relying on who happened to be in the room. You start operating on everything your team has ever seen, heard, and discussed.

That's not doing the same work faster.

That's doing fundamentally better work.

I've never been so excited to transform all my workflows 🔥

And I mean that. My December 2025 Claude Code moment with Opus 4.5 was probably the biggest tech “wow-moment” I ever had. For the first time, I really felt like having a team of 10 experts in my pocket. Working 24/7.

The shift happening right now is not incremental. It's architectural.

And if you’re not acting now: YOU. WILL. BE. LEFT. BEHIND.

The window to build this advantage is open, but it won't stay open forever.

As more people catch on, the bar will rise. What feels like a superpower today will be table stakes tomorrow.

The age of natural language automation is here.

You don't need a developer. You don't need to learn Python. You don't need a six-month digital transformation roadmap.

You need a clear description of your problem. Access to your tools. And the willingness to stop doing things the old way.

Grant access. Describe. Train. Chain. Execute.

No task repeated twice. Ever.

Stay driven,
Andre

PS: The Virtual DDVC Summit 2026 will be all about AI for VC, how the tool stacks and workflow automations of leading investment firms look like, and how they achieve better performance with smaller teams