How I Eliminated Self-Doubt in AI?

Conquer your impostor syndrome in AI. Today’s newsletter breaks down how I eliminated self-doubt in AI and includes learning resources for AI.

I added some content, news, and resources about Production RAG, Gemini CLI, AI Engineer Roadmap, and more.

I am starting a new live cohort of AI Engineer HQ this July. Reply to this email for early bird registration.

In today’s edition:

• AI Roundup— learning resources, news on RAG, Edge devices, and Gemma 3n

• Dive Deep Drill— How I Eliminated Self-Doubt in AI?

• Build Together— Here’s How I Can Help You

AI Roundup

I found these resources, content, and news this week.

Learning Resources

— [YouTube] Building Production-Ready RAG Applications
— [YouTube] Google Gemini CLI Is FREE & Crazy Powerful
— [LinkedIn] 10 GitHub repos to build a career in AI engineering.
— [YouTube] HeyGen AI - Full Tutorial 2025: BEST AI Avatar Video Generator
— [GitHub] AI Engineer Roadmap

Crazy Week News

— [news] Google announced the general availability of Gemini 2.5 Pro

— [news] OpenAI's GPT-5 Summer Release and Industry Anticipation
— [news] Meta's Superintelligence Lab and Scale AI Acquisition Strategy

— [news] Google’s Gemma 3n brings multimodal AI capabilities to edge devices

Sponsor Spotlight

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Dive Deep Drill

How I Eliminated Self-Doubt in AI?

If you’re deep into learning AI engineering or leading AI initiatives, and you’ve ever felt like an impostor,

I get it. I’ve been there.

Even after training hundreds of professionals through AI Engineer HQ, working with tech leaders in The Elite - an AI Leadership Accelerator, and leading my own AI consulting company, that voice still shows up:

• "Do I know enough to lead this?"

• "Am I really good at this, or just lucky?"

• "Everyone else seems ahead of me."

The truth?

Most people in AI feel this at some point.

Engineers, product folks, decision-makers, even experts.

Here’s how I’ve learned to deal with it, not only eliminating self-doubt, but by working with it.

You can apply this 5-part framework:

1. Stop trying to know everything

2. Turn learning into leverage

3. Build proof for yourself

4. Get out of your own head

5. Practice confidence

1 - Stop Trying to Know Everything

In the beginning, I thought I had to know every model, paper, and framework to feel like a “real” AI engineer.

As a leader, I thought I had to understand every architecture to be taken seriously.

That pressure was exhausting.

What helped was realizing that AI is too big for one person to master entirely.

Instead, I focused on:

• learning what mattered for my work

• going deep in my area, and staying aware of the rest

• surrounding myself with people who were smarter than I in specific areas

2 - Turn Learning into Leverage

Imposter syndrome hit me hardest when I was stuck.

Bugs I couldn’t fix, papers I didn’t understand, decisions I wasn’t confident making.

So I changed how I saw those moments.

Instead of "I'm not good enough," I started asking,

"What am I learning right now that I didn’t know last week?"

As an engineer, this meant:

• documenting code experiments and model failures

• keeping a journal of technical wins, even small ones

• sharing work-in-progress instead of waiting for perfect results

As a leader, it looked like:

• blocking time to explore AI tools hands-on

• writing reflections after each big decision or pivot

• using doubt as a signal to get clearer, not to shrink back

Trust me, you don’t need to be smart, you need to be clear,

so “WRITE THOUGHTS DOWN“.

3 - Build Proof for Yourself

A turning point for me was building a portfolio, not just to show others, but to remind myself that I can do this.

As an engineer, it meant shipping:

• end-to-end projects with real-world impact [Steal my GitHub]

• code that solved problems, not just passed tutorials

• write-ups explaining my process and decisions [using AI tools to write for me]

As a leader, it meant tracking:

• strategic calls I made under uncertainty [some failed, some worked]

• experiments I launched and lessons I learned [MasterDexter]

• feedback I gave that helped my team grow

When you create good evidence of your progress, it becomes hard to argue with the facts,

even when that imposter voice tries to.

4 - Get Out of Your Own Head

Talking to others was one of the most underrated things I did.

Whether it was engineers on GitHub, leaders in my cohort, or peers in AI forums, everyone had their version of the same doubts.

That realization was freeing.

• I wasn’t alone

• I wasn’t behind

• I wasn’t supposed to have all the answers

So I joined communities [mine at Discord]

Asked “dumb” questions.

Shared half-baked ideas.

And started getting better, faster.

Remember, speed is equally important as the intensity of your work as of 2025.

Learn fast, build fast, ship fast, fail fast, and win fast.

5 - Practice Confidence

I used to think confidence would come after I learned enough.

But I’ve learned that confidence comes from doing, reflecting, and repeating.

That applies whether you’re:

• debugging your first model

• leading a GenAI rollout for your org

• pitching AI strategy to the executive team

I still feel self-doubt sometimes.

But now I move anyway.

Because I know every small win builds momentum.

And momentum beats perfection every time.

Final Thought

If you’re learning AI, leading AI teams, or just trying to keep up with this wild space, and you sometimes feel like you don’t belong,

Remember this:

You’re not behind.

You’re in motion.

And motion is what separates the ones who grow from the ones who give up.

Whether you’re in my cohort, in your company, or just learning on your own

Keep building.

Keep leading.

Keep sharing.

That’s how I overcame impostor syndrome.

And how I still do, every day.

Want to work together? Here’s How I Can Help You

• AI Engineering & Consulting (B2B) at Dextar—[Request a Brainstorm]

• You are a leader?—Join [The Elite]

• Become an AI Engineer in 2025—[AI Engineer HQ]

• AI Training for Enterprise Team—[MasterDexter]

• Get in front of 5000+ AI leaders & professionals—[Sponsor this Newsletter]

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Paper Unfold

A series in which you will get a breakdown of complex research papers into easy-to-understand pointers. If you missed the previous ones:

• Apple's Bomb on Reasoning Models

• Agents are Not Enough [Paper Unfold]

• Attention Is All You Need [Paper Unfold]

AI Engineer HQ

New Cohort starting this July, reply to this email for details.

PS: Reply to this email if you want me to write on the topic you are interested in.

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