Outbrand AI

Founding Engineer.  Full Stack & MLOps

DevMornings

I lead the day to day operations, meetup coordination, partnerships, marketing and relationship management for the DevMornings organization of meetups in Bangkok, Thailand.

Bangkok Organizer of DevMornings - 5 meetups. Hundreds of members in SEA.

Oligarch Ventures, LLC

Experience building and scaling enterprise software and machine learning systems.

I can help you with every aspect of your technology stack, including the following:

- Extensive experience in production Machine Learning
- World class engagement and responsiveness throughout the engagement
- Relentless focus on overdelivering and making your project successful.

My expertise:

- Python, Tensorflow & Keras, Scikit-Learn, OpenCV
- Software engineering and design
- AWS (Amazon Web Services) & SageMaker

Full Stack & AI Engineer

TextNow

Software Engineer

Warner Bros. Digital Labs

Software Engineer, Android

The Global Hackathon

Co-Founder

Procore Technologies

Capital One

Android Developer

BAM Tech

ASTQB Certified Tester, Foundation Level.

QA Engineer

Hey there, I’m Adrian, and over the past decade, I've helped countless business owners like you earn more in their coaching or consulting business without spending more time with clients or hiring more.

Here's how I do it:

RAPID IDEA VALIDATION
Stop throwing good money and irreplaceable time after bad ideas. Validate your product market fit in only 3 days!

EXPERT COUNCIL
We have experience from large banking institutions to 3 man startups. No app is too big or takes too long.

PAINLESS CASH FLOW
Generate money without burying yourself in endless phone calls and consulting webinars.

Google has made the 👉 easy 👈 decision to lay off 200 team members (via email)

These layoffs impact various "Core" teams that are crucial to app platforms and other engineering roles.  Including its Flutter (hybrid dev), Dart (programming language), and Python projects. 

On a similar note, Tesla, under the leadership of CEO Elon Musk, 

has dramatically reduced the size of its team responsible for managing the Supercharger network. 

This comes unexpectedly as Tesla had recently gained support from major automakers like Ford and General Motors. 

The extent of the layoffs suggests a significant slowdown in the expansion of Tesla's Supercharger network, 

with Musk hinting at operational delays in a recent internal email.

Such moves raise questions about the strategic directions tech giants might be taking 

as they navigate through industry and economic pressures. 

What do you think this means for the future of innovation at these companies?

Adrian Mohnacs

𝐑𝐞𝐟𝐥𝐞𝐜𝐭𝐢𝐧𝐠 𝐨𝐧 𝐭𝐡𝐞 𝐫𝐞𝐜𝐞𝐧𝐭 𝐬𝐞𝐭𝐛𝐚𝐜𝐤 𝐚𝐭 𝐒𝐢𝐥𝐢𝐜𝐨𝐧 𝐕𝐚𝐥𝐥𝐞𝐲 𝐝𝐚𝐫𝐥𝐢𝐧𝐠, 𝐃𝐞𝐯𝐢𝐧 𝐀𝐈: 

🔹 Challenge Encountered: Their app stumbled while completing a client task, facing issues due to bad data and ambiguous instructions.

🔹 Insight Gained: This experience highlighted the vital importance of continual AI development and the role of human oversight in SaaS projects.

🔹 Looking Forward: While AI continues to advance, it's clear it won't replace developers anytime soon. Human expertise and problem-solving skills are irreplaceable and crucial.

🔹 Silver Lining: AI's true value lies in speeding up developer capabilities to get to breakthroughs faster

This failure reinforces a critical lesson: using both human talent and AI's potential is key to driving  progress and more money in the bank.

🔄 If you've faced similar challenges, how have you turned setbacks into learning opportunities?

Here's how you get product market fit...today.

Post or send an email to your customers and say this:

"We're thinking about launching a new app that will solve <insert problem>.  Do you think this will help you?  Early adopters will pay <insert price> but we expect the price to go up later.  Comment/reply and we'll sign you up."

Let's get building.

We use a smart software strategy that works in three steps: find what works fast, get it out there quickly, and make sure it brings in money.

We have all of the information you need in my weekly updates that gets you from 0 to launch in days https://buff.ly/3JwI24c 

Llama 3 has already been released 🤯

And you still haven't launched an AI app?

Are you excited to try it? 

Me too 🙌

It's a game-changing, believe me... 

Both Meta and OpenAI are equipping models to: 

Think → Plan → Remember
↳ Just like humans do

A big step towards creating Artificial General Intelligence (AGI).

It will surpass human cognition, 

Especially in areas like Reasoning and Planning 📝

Complex Problems → Effective Solutions

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👇    👇    👇    👇    👇    👇    👇    👇    👇    👇 

And you still haven't launched an AI app?

Launch AI app → Sell it to your Customer → Cash In

DM me ""YES"" to get started

P.S. Share your thoughts below... How Llama 3 will change the world?

𝐓𝐡𝐢𝐬 𝐢𝐬 𝐰𝐡𝐲 𝐦𝐨𝐬𝐭 𝐚𝐫𝐞𝐧'𝐭 𝐮𝐧𝐝𝐞𝐫𝐬𝐭𝐚𝐧𝐝𝐢𝐧𝐠 𝐀𝐈 𝐦𝐨𝐝𝐞𝐥𝐬... 

misplaced focus on the model.  Ignoring the data.

To get others to understand that you have a solid grasp on the concept of artificial intelligence conversations should revolve around data.

There's a common moniker in the field of AI that says "garbage in. garbage out".  Too many get caught up talking about the latest model and how many parameters it has.

If you can position yourself in an expert of data sources and training sets for these models you will automatically stand out.  The results you get will be far better as well.

It's funny how much time is wasted thinking about an idea.

Sometimes I feel like a failure, but I never quit.

I keep launch apps for clients faster than anyone else and they get paid.

In this week's issue I'll explain how I do it:

https://buff.ly/3JwI24c

When selling your mini-saas...

go for the cold outreach!

Will be launching every week for 12 weeks and sharing what I learn along the way.  Here are a few steps I've found to really crush it on the site.

Adrian Mohnacs on LinkedIn • 4 min read

This Week's Focus: Launching On Product Hunt

Everything you need to know about getting better AI performance as an entrepreneur. NO TECH REQUIRED.

Working with AI models can get complicated. It doesn't have to be.

Training a model for your specific use case happens in only a few steps:

1️⃣ Pick your model and your dataset
2️⃣ Pick your data "shards" this is how much data the AI should process at a time.
3️⃣ Pick the number of "epochs" to train. This is how many times the AI tries to learn.

These are a few of the levers you can pull to tweak your AI performance.

You don't need to understand code and tech to see success in SaaS,
but a basic understanding will take you far!

Hope this helps.

I never try to change my approach.

My results get them to market faster with an app that they can easily sell to their existing audience -- providing value -- with this simple approach:

1. Instant product market fit

I realized that too many people are spending all their time reading headlines.  SaaS doesn't take years and millions of dollars.  It only takes a few posts to find the perfect idea.

2. Launch quickly

I create a simple landing page that collects payments.  It's a genius marketing mechanism.  Customers are invested and hanging on your every post.  Waiting for the next app update.

3. Monetize now

I've realized that my app customers like me more when they pay me.  It shows that I have earned their trust and swiping their card makes them feel good.  We both win.

When I learned to code, I spent one year "starting a startup" and made $0 when competing with all the noise out there.

New ideas don't matter.

Pick one and stick to it. You’ll get comfortable and ship much faster.

Sure, you've got users,

But do you have a novel, repeatable way to get new ones?🤔

Does your product, through its very usage, have distribution built in?

NO? 

How can you leverage potential traffic?

Simple answer is, SOCIAL MEDIA.

You can generate consumer Awareness and Interest.

It’s one piece to a well-oiled machine you've already created.

On Social media, you:

🟢 Consume → 10%
🟢 Create → 20% 
🟢 Distribute → 70%

Content is King 👑

Build Distribution → then you can build whatever you want.

↳ It's not a rocket science. 

↳ It's just the potential for an ulimited traffic system.

Before you start Building → Think Distribution

When you are Building → Think Distribution

When you Launch → Think Distribution

Repost ♻ this for your LinkedIn network

P.S. Don't forget to pick my newsletter to double your reveneu https://buff.ly/3JwI24c

Am I the only person that sees GenAI automating 40% of marketing gurus?    

Yes, you heard it right...

IDC modeled the work of 24 key marketing roles and estimated,

how much work can be delegated to GenAI over the next 5 years.

The results are shocking 🤯

GenAI will be able to handle 40%+ of the collective work of marketing teams

And 100% of specific marketing tasks.

But, how can you prepare to take advantage of GenAI❓

Let's look at a few steps:

🟢 Evaluate the breadth & depth of use cases
↳ Create strong economic justification for investment

🟢 Focus on vendor's architecture, tool, & service resources
↳ Accelerate the journey down that use case road map

🟢 Determine infrastructure required to support each type of work
↳ Demand high-performance networks and storage

🟢 Implement from data layer up, not from task automation layer down
↳ Share common services for data, governance, security, and so forth

🟢 Prepare organization for fundamental job changes
↳ Upskilling, reorganization, Job elimination and expansion

🟢 Prepare your data
↳ Must have real-time, clean, and governed data sets

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👇        👇        👇        👇        👇        👇        👇        👇        👇        👇

Are you still struggling? Doing things manually?

Automate Tasks → Uplift Growth

P.S. If you got value, repost ♻ this for your LinkedIn network

🚨 Exciting AI Breakthrough Alert! 🚨

So here's today's big news:

Introducing the gpt2-chatbot! A mysterious new AI model just popped up and it’s already shaking the AI community to its core.

What You Need to Know:
- Debuted on LMSYS Chatbot Arena, the "gpt2-chatbot" arrived without any prior buzz but quickly became the talk of the town.
- Stanford’s very own Andrew Gao tested it with a challenging International Math Olympiad problem—it passed with flying colors on its first try!
- Wharton's Ethan Mollick noticed it surpasses GPT-4 in tasks like coding a unicorn image—yes, really!
- AI influencer Rowan Cheung vouched for its unparalleled ASCII art skills. Way ahead of the curve!
- Chase from Codegen highlighted its coding prowess, outperforming major models including GPT-4 and Claude Opus.

Speculations Arise:
While many think this could be another marvel from OpenAI—thanks to a hint from Sam Altman himself—others suspect a dark horse in the AI race might be behind this.

Takeaway:
The "gpt2-chatbot" is a testament to the rapid evolution of AI technology. Staying updated is more thrilling—and daunting—than ever!

Feel inspired? Share this post to keep your network in the loop!

P.S. How do you keep up with the fast-paced world of AI innovations?

Most big AI startups aren't even launching. 

Now is your time to take advantage…

Why?

Only 10% to 20% of ML Projects ever make it to production 🤯

and 91% of models degrade in performance over time,

Software isn't ❌ “Set it and Forget it”,

that's because operations teams need to regularly perform triage.

What are the potential challenges happening?

👉 Organizational Level problem
↳ Misaligned incentives, skill sets, and cultural expectations between Teams
Solution: Need better Processes, and better Mutual Understanding

👉 Teams stop trusting each other
↳ A shortsighted focus on immediately measurable results
Solution: Teams collaboration with specific timelines, expectations and budgeting

👉 ML Experts With No Business Background
↳ Focusing entirely on Engineering KPIs
Solution: Include Business-focused use cases 

Overcome Challenges → Take Advantage → Build Empire

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👇    👇    👇    👇    👇    👇    👇    👇    👇    👇 

I help Coaches, Consultants, and Business owners double their revenue with Al.

DM me ""mini-saas"" and get access to my guide “Find Product-Market Fit in 3 days”

P.S. Repost ♻ this for your LinkedIn network

Here's the truth…

AI investments are slowing down which means the ""mini-saas model"" will grab all the profits.

Big AI investments dropped by 20% in 2023 compared to the previous year.

Strange... Right?

But Why are AI investments going down? 🤯

Let's look at a few reason:

↳ Crowded market
↳ Steep costs of Building AI Models
↳ Investors → Getting pickier → Want to see real-solid ROI
↳ New Player → Weak position → Difficult to get a piece of pie
↳ Big Companies → Strong position → Money flowing towards them

Despite these hurdles,

There's still a strong belief in the future of AI.

Especially in ways it can Boost Efficiency📈

And spark Innovation 🚀 across different sectors.

This change is key to creating small apps with the help of AI

↳ Customer-Centric
↳ Can truly change industries
↳ Actually work in the real world

Slow Investments → Getting pickier → Better Results

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👇        👇        👇        👇        👇        👇        👇        👇        👇        👇

I help Coaches, Consultants, and Business owners double their revenue with Al.

DM me ""mini-saas"" and get my guide “Find Product-Market Fit in 3 days”

P.S. What will AI look like in the next 5 Years?

If you haven't seen that Open AI's SORA has been "cracked", then, you are falling behind.

SORA is a text-to-video model,

That can create Realistic and Imaginative scenes from text instructions.

It will save a lot of time and money 🤑 on production.

Excited to try it? Me too

But OpenAI is planning to release SORA at the end of 2024.
 
Don't worry...... 

I have some exciting news for you 🥳

While the Sora model is not open source, 

Colossal-AI team presents open source Open-Sora. 

It's a complete Sora replication 💯 architecture solution. 
 
Developers can use it to integrate Sora’s capabilities into their applications.

It allows you to generate high-quality, text-controlled video content. 

You can train models to enhance 📈 resolution and duration, 

Engage in text-to-video experiments, and Refine model conditions. 

Adopt AI → Amplify Growth → Change The World

How do you think Sora's open-sourced version will change the world? Share your thoughts below

P.S. Repost ♻ this ""news"" for your LinkedIn network

Estimated read time: 5 minutes So we're back with a new version of "Engineer to Entrepreneur", just for you. This week, we're focusing on the magic of

Adrian Mohnacs on LinkedIn • 3 min read

What IS a mini-SaaS

Elon Musk predicts superhuman AI will be smarter than people next year. His claims come with a caveat that shortages of training chips and growing demand for power could limit plans in the near term.

Elon Musk thinks that super smart AI could be here by next year. He says this AI will be smarter than anyone on Earth. But, there are some big ifs. We might not have enough of the special chips needed to train the AI, and we might not have enough power for all the computers.

Musk's new prediction is a big change from his earlier guess. Before, he thought this super intelligent AI would show up by 2029. There's a difference between "superhuman" and "superintelligent." "Superhuman" means smarter than any one person at something. "Superintelligent" means smarter than everyone put together at everything.

"My guess is that we’ll have AI that is smarter than any one human probably around the end of next year," Musk said during a live chat on his social network, X. He added that this depends on if we can keep up with the need for more power and better chips.

"Last year it was chip-constrained," he explained. "People could not get enough Nvidia chips. This year it’s transitioning to a voltage transformer supply. In a year or two, it’s just electricity supply."

Elon Musk is worried about the future with super smart AI. When he started his AI company, xAI, he said he would stop AI if he could because it might be dangerous. He wants us to avoid a scary future where AI could turn against us.

This year, xAI is trying to be a leader in making super smart AI. Musk mentioned that their new chatbot, Grok AI, is as good as the older GPT-4 model from OpenAI. But other new AI models might be even better.

Musk often makes big predictions. In the past, he's been wrong about how fast things would happen, like with his Tesla cars driving themselves across the country or his SpaceX rockets going to Mars. He also thought a brain chip from his company, Neuralink, would be ready sooner than it was.

Musk has a lot going on. Over the weekend, he was upset with a judge in Brazil and asked for him to resign. On Monday, he admitted in court that some of his posts on X might have hurt his company more than helped.

I spoke with 100 SaaS entrepreneurs and found out why they aren't launching more apps...

Entrepreneurs Live and Die by how fast they ship and launch their software.

I spend a lot of time thinking about this question, 

What's the reason behind it? 

Finally I got it 🙌

I found 100 SaaS Entrepreneurs and asked them exactly one question,

What's stopping you from shipping faster?

👇 Here's what I learned:

🟢 Codebase
↳ Dependency Bugs → Library bugs & GitHub Issues
↳ Complicated Codebase → Undocumented & Outdated Info

🟢 Process
↳ QA Processes → Adding Unless repetitions
↳ Waiting for Spec → Stakeholders decision involved
↳ Writing Tests → Not enough Test cases for code testing
↳ Unclear Requirements → Lack of clarity → Low Productivity 

🟢 Tooling
↳ Deployment speed → 3-4hrs for build completion + 1d-3d for testing
↳ Even a small change can get tedious

Slow Shipping → Hard to survive  

Repost ♻ this = Help others learn and survive

P.S. What's stopping you from shipping faster?

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