In the next year, this blog will be painted with a mix of technical machine learning content and personal notes. I've spent more of my 20s thinking about my life than machine learning. I'm not good at either, but I enjoy both.
I was born in a village in China. My parents were the children of rural farmers who grew up during the Cultural Revolution. They were the first generation of their family to read and write, and also the first generation to leave the village.
Have you ever wondered why some teams seem to effortlessly deliver value while others stay busy but make no real progress?
I recently had a conversation that completely changed how I think about leading teams. While discussing team performance with a VP of Engineering who was frustrated with their team's slow progress, I suggested focusing on better standups and more experiments.
That's when Skylar Payne dropped a truth bomb that made me completely rethink everything:
"Leaders are living and breathing the business strategy through their meetings and context, but the people on the ground don't have any fucking clue what that is. They're kind of trying to read the tea leaves to understand what it is."
That moment was a wake-up call.
I had been so focused on the mechanics of execution that I'd missed something fundamental: The best processes in the world won't help if your team doesn't understand how their work drives real value.
In less than an hour, I learned more about effective leadership than I had in the past year. Let me share what I discovered.
This FAQ is generated by NotebookLM and Gemini and addresses common questions from the "Systematically Improving RAG Applications" course. The course is a comprehensive, six-week program that guides you through:
When I talk to engineering leaders struggling with their AI teams, I often hear the same frustration: "Why is everything taking so long? Why can't we just ship features like our other teams?"
This frustration stems from a fundamental misunderstanding: AI development isn't just engineering - it's applied research. And this changes everything about how we need to think about progress, goals, and team management. In a previous article I wrote about communication for AI teams. Today I want to talk about standups specifically.
The ticket is not the feature, the ticket is the experiment, the outcome is learning.
Helping software engineers enhance their AI engineering processes through rigorous and insightful updates.
In the dynamic realm of AI engineering, effective communication is crucial for project success. Consider two scenarios:
Scenario A: "We made some improvements to the model. It seems better now."
Scenario B: "Our hypothesis was that fine-tuning on domain-specific data would improve accuracy. We implemented this change and observed a 15% increase in F1 score, from 0.72 to 0.83, on our test set. However, inference time increased by 20ms on average."
Scenario B clearly provides more value and allows for informed decision-making. After collaborating with numerous startups on their AI initiatives, I've witnessed the transformative power of precise, data-driven communication. It's not just about relaying information; it's about enabling action, fostering alignment, and driving progress.
Picture this: Four AI engineers walk out of some big tech office, maybe its layoffs, or burn out, or the golden handcuffs, but they're finally free. Fast forward one year, and their paths couldn't be more different.
Engineer 1 went the traditional freelance route. He's making $300 an hour, meticulously tracking every minute, and constantly hearing he's "too expensive." Yet, he's always scrambling for the next gig.
Engineer 2 dove into the startup world. She's now a VC-backed founder, drowning in pitch decks and investor meetings. Sure, the TechCrunch headlines are nice, but she hasn't had a good night's sleep in months, constantly worrying about runway and growth metrics.
Engineer 3 became an indie hacker. He's over the moon about hitting $2,000 in Monthly Recurring Revenue with his AI product. It's a great start, but he's realizing that building the product was just the beginning. Now he's grappling with the challenges of distribution and marketing, discovering that these skills are just as crucial as his technical expertise.
And then there's me, Engineer 4. I'm writing this from a business class seat on my way to San Francisco, closing a six-figure deal with a client. But that's just the tip of the iceberg.
As an AI consultant, I've built a personal brand, grown an audience, and mastered marketing and distribution - all while confidently selling my expertise. I've made friends with VCs, hosted dinners for industry leaders, and built a network that spans the tech world.
The best part? I've got $500K sitting in my business account, deployed 100k in angel investments and have paid my friends 100s of 1000s of dollars to work together and on projects we love. If I ever decide to start a company, raise money, or build a product, I've already developed all the skills I need - plus the cash to get started.
Look, creating content that matters is hard. Here's how to craft impactful content without the bullshit.
I remember stories about the tech booms of past decades. In the late 1990s, the web revolution began. Teenagers who knew HTML were earning thousands per project, building websites for local businesses. In the late 2000s, a similar trend emerged with mobile apps. Young developers were profiting from creating applications for smartphones.
"This is the future," people would say. Many were skeptical about how these basic websites or simple apps could change anything. We know how those predictions turned out.
Now, in 2024, I'm feeling the same way about AI freelancers and consultants. But this time, I'm not skeptical. I believe we're at the start of something significant, a change that will surpass the web and mobile revolutions in its impact.
Here's why:
It always goes this way. Someone will try teaching you a parable or life story, but you never really understand it until you have to experience it yourself. Some call this ‘learning things the hard way.’ Some call this life. Now, folks always told me that consulting was either a feast or famine, which sounds straightforward, but it turns out I didn’t really know what this meant until I had to deal with Chase.
Earlier this year, for reasons that are still not fully known to me, and despite my existing relationship with Chase (dating back to my first job out of university over a decade ago!), Chase froze $180,000 of my money without warning. This left me scrambling to pay employees and nearly derailed my business—all without explanation. It was a major wake-up call not just for me but for any entrepreneur. The importance of diversifying your banking and choosing financial partners that actually support small businesses has never been more important.
As I've shared insights on indie consulting, marketing strategies, and referral techniques, a recurring question from my newsletter subscribers is about pricing. Specifically, many ask if they should lower their rates or make them public.
In this article, we'll delve into the counterintuitive reasons why listing your consulting prices might not be the best strategy, regardless of whether you're aiming to appear affordable or exclusive. We'll explore the potential drawbacks of transparent pricing, introduce more effective alternatives like minimum level of engagement pricing, and provide actionable strategies to help you maximize your value and earnings as a consultant.
Building on the foundation laid in my previous posts about building a consulting practice and using the right tools, this piece will add another crucial element to your consulting toolkit: strategic pricing.