Developer Advocate & Founder @ ML Data | Data Science & AI Content Creator

I didn't write my first line of code until I was 26. Now I get sponsored by companies like Anthropic, Amazon and IBM to create coding videos as a tech content creator.

My career path has been anything but linear - finance analyst to consultant to data scientist to full-time content creator. At each stop, I felt like I was starting over, but those diverse experiences became my superpower. My finance background taught me business fundamentals, consulting showed me how to solve complex problems, and data science gave me technical skills. 

When I combined all three and took the leap into content creation and developer advocacy, companies started paying attention.

Now I help others navigate their own career transitions by sharing what I've learned across industries and roles.

When I'm not creating content, you'll find me exploring running, playing pickleball or cuddling with my fur babies, Belle and Lola.

I'm always excited to connect with fellow career changers or anyone building something interesting. Feel free to reach out at megan@thedriveagency.co or send me a message here on LinkedIn 👋

Megan Lieu

90% of people are either wasting money on AI tools…

Or missing out on powerful tools that are literally FREE.

Including me — until I finally understood the real difference between Free vs Paid AI Tools.

Here’s what nobody tells you about AI tools:

Paid doesn’t mean better.
It just means better for a specific workflow.

So I’m finally sharing my full Free vs Paid AI Tools Framework (by category) 👇

✅ Writing & Content
↳ Paid: Jasper AI, Writesonic, Copy. ai, Frase, LongShot AI
↳ Free: ChatGPT, Google Gemini, QuillBot, Grammarly, Wordtune

✅ Image & Design
↳ Paid: Midjourney, Adobe Firefly, Leonardo AI, Seedream 4.0, Runway Images
↳ Free: Bing Image Creator, Canva, Stable Diffusion, DALL·E, Nano Banana

✅ Video & Multimedia
↳ Paid: Synthesia, Pika Labs, Runway Video, Descript, Veo 3 Fast
↳ Free: CapCut AI, InVideo, Runway, Synthesia, Pexels AI Video

✅ Coding & Dev
↳ Paid: GitHub Copilot, Cursor AI, Tabnine, Replit Ghostwriter, Codeium Pro
↳ Free: GitHub Copilot, Gemini Code Assist, Codeium, AWS CodeWhisperer, OpenAI Playground

✅ Productivity & Research
↳ Paid: Notion AI, Perplexity Pro, Coda AI, Otter. ai, Evernote AI
↳ Free: Perplexity, Notion, Microsoft Copilot, Obsidian AI Plugins, Google Gemini

✅ SEO & Marketing
↳ Paid: Surfer SEO, Clearscope, MarketMuse, SEMrush AI, Ahrefs AI
↳ Free: Ubersuggest, Google Trends, AnswerThePublic, SEO Minion, Mangools Tools

✅ Audio & Speech
↳ Paid: ElevenLabs, Murf AI, Play. ht, Resemble AI, Descript Audio
↳ Free: Google Text-to-Speech, Mozilla TTS, Audacity AI Plugins, Talkie AI

✅ New & Trending AI Tools
↳ Paid: Claude Pro, Gemini Advanced, Lovable AI, Flux Pro, Runway Advanced
↳ Free: Nano Banana, Lovable. ai , Flux, Captions. ai, Playground AI

I went from randomly subscribing to AI tools…

To building a stack that actually matches my work.

And that’s the truth about AI tools…

Free tools help you start.
Paid tools help you scale.

♻️ Reshare this if it helped and follow me for more AI tools + workflow breakdowns.

a16z just dropped their list of unicorn startup ideas for 2026. 

The Silicon Valley VC firm just released a list of the biggest ideas their investing teams believe builders need to tackle this year.

So make sure you save this if you’ve been looking for the next unicorn startup idea:
 
 1. AI-native banking & insurance infrastructure
 2. Enterprise multi-agent orchestration platforms
 3. Physical observability platform
 4. Compliance-first AI development tools
 5. ChatGPT-native apps (via OpenAI apps SDK)
 6. Autonomous scientific discovery labs
 7. Multi-modal voice agent platforms
 8. Prompt-free, proactive AI applications
 9. AI-native industrial base companies
10. Reasoning/multimodal/computer-use-enabled companies
11. Industrial data collection & annotation platform
12. Forward-deployed AI consulting
13. AI startup tooling for greenfield companies
14. Voice-first AI operating system
15. AI-powered contingency business models
16. "See Me" consumer AI products
17. Synthetic biology design studio
18. AI-native insurance products
19. AI-powered sales qualification platform
20. Electro-industrial stack components

Which of these ideas are you betting on?
 
Check out the full article from a16z linked in my comments below 👇

Tech Startups by A16z

Sr. Data Analyst @ Crunchbase | Founder @ Big Data Energy⚡️ | LinkedIn [in]structor | Empowering career growth in data | Breaking industry stereotypes

💌 partnerships@bdeanalytics.com
Hi 👋🏼 I’m Jess Ramos, the founder of Big Data Energy ⚡️ and a content creator with a community of over 450,000 followers across LinkedIn, YouTube, Instagram, and Substack. I'm an ex-corporate data analyst and data scientist turned entrepreneur. 

I'm also a Top Voice on LinkedIn and one of the leading voices in B:B marketing in tech partnering with big brands like IBM, Claude, Lyft, and the NFL!

After spending years in high-growth tech startups, I realized my true passion is working for myself as a developer advocate striving towards making tech, data, and AI more accessible to all. Through my business, I offer brand partnerships in the form of social media content, conference attendance, and live events. I also teach SQL and data courses for current and aspiring analysts.  

Highlights:

- Creator of Big SQL EnergyⓇ ⚡️ (the world’s greatest SQL course!)
- Partnered with brands like IBM, AWS, NFL, Atlassian, Lyft, Claude, Notion, and Snowflake
- Advocate for making data careers more accessible & human in an AI-driven world

Brands: partnerships@bdeanalytics.com
🎥 Youtube: @JessRamosData
📸 Instagram: @jessramosdata
💌 Newsletter: https://jessramosdata.substack.com/
🤳🏼 TikTok: @jessramosdata

Jess Ramos, MSBA

Everyone thinks when they get a job in data it'll be the most sexiest job ever full of so many intellectual smart things... 

like coding all day, using AI, and being super techy. 

Basically saving the world one query at a time!

But the reality is that data analytics is still a business job because data analysts are parts of businesses and corporations. 

So much of the day revolves around communication, catering to stakeholders, and driving insights that point to higher-level goals and KPIs.

Things that will make the execs happy and look good in front of the board are ultimately the most important tasks-- not the research and exploring you're excited to do with all of your pent-up curiosity. 

If you don't advocate for those tasks and get buy-in from leadership, they're likely a no-go.

Sometimes, it can be draining, but it makes the quiet days where you can explore data and have fun so much more appreciated. 

Is being a data analyst what you expected or not?

Jess Ramos ⚡️

Tech, Data Science, & AI Content Creator w/ 450K+ followers | Developer Advocate & Solopreneur | LinkedIn Learning Instructor | Big Data Energy⚡️ | helping you leverage tech & AI

A popular (male) data influencer has been stealing content and ideas from me and Dawn Choo  

And I'm not very happy about it. 

They copied my LinkedIn cover photo many months ago stealing my original design of "select * from jess_ramos" pointing to my cover photo. 

I didn't say anything because it's the highest form of flattery and it's not worth my time.

But then a week ago, they copied Dawn's instagram video *word for word* stealing the exact concept, text, and script. 

I commented calling them out and they DMed me saying they "tagged Dawn in the comments giving her credit." 

When I said that still doesn't make it okay to copy people, they changed their whole story and said they "filmed it weeks before and Dawn coincidentally came up with the EXACT same idea” copying them.

And they sent a fool proof screenshot with a timestamp they edited in their phone LOL

How about we stop copying other creators and stealing ideas from women??

And even worse, lying about it?

People talk. Is that really how you want your reputation to be?

Tech, Data Science, & AI Content Creator w/ 450K+ followers | Developer Advocate | Big Data Energy⚡️ | Remote Work & Entrepreneurship

No alternative text description for this image

You'll spend 80% of your time data cleaning.

So don't skip these lessons!

It's not as fun and pretty as AI & ML, but it's the bread and butter you need.

Save these functions for later:

↳ Replace(): replace values
↳ Cast(): change data types
↳ Coalesce(): return first non null value
↳ Ifnull(): replace nulls
↳ Concat(): combine string values

And save these videos to improve your skills:
Data Cleaning w/ SQL & AI: https://lnkd.in/enFBW4_5
Handling Nulls the RIGHT way: https://lnkd.in/ehaQky-Z
Recategorizing data w/ Case Statements: https://lnkd.in/eDPgdcWv

Data cleaning in SQL for data science and data analytics doesn’t have to be hard 🔥

What are your favorite functions for data cleaning??

♻️ repost for your network and save this for later!

Top 5 SQL Data Cleaning Functions

Learning how to set corporate boundaries professionally is truly an art. If you don't learn this... you'll likely be pushed around and taken advantage of. 

These are boundaries that I set for myself (and have accidentally broken in the past!):

1. Do not respond to any notifications or messages outside of your working hours. You never want to set the precedent and expectations that you will— because then if you ever don’t, your manager will feel let down and disappointed in you.

2. Overcommunicate and manage up. If your manager wants to be super hands on, keep them super updated with frequent status updates and decisions. That way they can weigh in if they want to and will build trust in you. And you can keep them from pestering you daily with updates.

3. Take time for yourself and enjoy your personal life (& PTO) GUILT FREE. Just because they have no hobbies doesn’t mean you can’t enjoy your life. You shouldn't feel guilty for using your benefits and not working past your contracted hours.

Have you had a manager like this? Are you healing from one like this?

Tech, Data Science, & AI Content Creator w/ 400K+ followers | Big Data Energy⚡️| Technical Educator | Remote Work & Entrepreneurship

Is data science still the sexiest job of the 21st century?

It’s changed a lot over the years: 

↳ 2012: DS was deemed as the sexiest job of the 21st century— and it was. It required a phd and deep statistical modeling knowledge resulting in very high salaries and demand.  

↳ 2021: This was the rise of bootcamps that over promised and underdelivered and the market became more saturated. However, tech companies were hiring so much, no one really noticed the oversaturation and many people broke in. 

↳ 2026: Hiring has slowed down greatly and so has the demand to become a data scientist. Everything has been in a lull feeling slow, and people are having to adapt their skills to include AI & agents to get jobs. 

The field isn’t dying, it’s just adapting and reshaping into new kinds of roles. 

Skills and tools are changing (as always), and you should only go into a data role if you actually enjoy it!

I think it’s worth it, what about you?

♻️ Repost for your network and 🏷️ save this for later!

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The Battle

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