Algorithmically Elevated Album Links

Spotify: https://open.spotify.com/album/74LAGeQ0MiWSbT0NUPb6DG?si=qc-Li2PFRjqdVYZH3OD61w

Apple Music:  https://music.apple.com/us/album/algorithmically-elevated/1852540489

Amazon Music: https://music.amazon.com/albums/B0G1FFN1DT?ref=dm_sh_zuzhD11BgxZ8goBvV7j8kg25q

YouTube: https://youtube.com/playlist?list=OLAK5uy_lqlOMfksLslGRIfh43amwoof8tVk_wK_Q&si=6QAeMrxwHmVt1rEu

Algorithmically Elevated Album Intro

My debut album “Algorithmically Elevated” hits all the streaming platforms today.

We’re at an inflection point in art and technology. Every so often a new tool comes along and suddenly everyone is sure the sky is falling. Photography wasn’t “real art.” Sampling was “cheating.” Digital recording was “soulless.” Synths were the end of musicianship. Digital editing was a crime against humanity. And every time, those exact tools ended up expanding what artists could do.

We’re living through another one of those moments.

And yes—there’s plenty of AI-generated music out there that absolutely earns the name “AI slop.” You can hear when someone simply hits “generate,” and then “publish”. That’s not what this album is. These tracks were hand built by me, as a life-long musician, music producer, sound designer and technology geek.

It’s my voice—(AI versions trained on recordings of my own voice)
My arrangements. (Some of these tracks used training data sourced from my 30+ year old cassette tapes). 100% my own original lyrics.

And let’s be real: I couldn’t possibly afford to hire a full orchestra to bring these songs to life. Today’s tools made it possible to create what I’ve heard in my head for decades without needing a six-figure recording budget or a major label behind me.

Simply put: before, these songs didn’t exist.
Now they do.

The album pulls from all over my life:

  • Some brand new.
  • Some written when I was a teenager.
  • One written for a movie.
  • One about racism.
  • Two holiday songs.
  • Two experiments.
  • And one about ice cream and monogamy, because art imitates dessert.

If you’ve made it this far reading this post, you must be a mega fan, so thank you 🙏

Algorithmically Elevated on Spotifyhttps://open.spotify.com/album/74LAGeQ0MiWSbT0NUPb6DG?si=qc-Li2PFRjqdVYZH3OD61w

Algorithmically Elevated on Apple Music:  https://music.apple.com/us/album/algorithmically-elevated/1852540489

Algorithmically Elevated on Amazon Music: https://music.amazon.com/albums/B0G1FFN1DT?ref=dm_sh_zuzhD11BgxZ8goBvV7j8kg25q

Algorithmically Elevated on YouTube: https://youtube.com/playlist?list=OLAK5uy_lqlOMfksLslGRIfh43amwoof8tVk_wK_Q&si=6QAeMrxwHmVt1rEu

Algorithmically Elevated Track 01 on Algorithmically Elevated by Johnny Diggz

The title track of the album, “Algorithmically Elevated,” is a meta-song about writing songs with AI as a true co-writer. It began with a simple prompt—“let’s write a song together”—and evolved into an accordion-driven tango backed by a symphonic swirl of digital textures and orchestral instrumentation. It’s part human passion, part machine logic, and fully committed to the strange new frontier where creativity and computation meet.

The lyrics celebrate the sparks that come from constraints, glitches, and the unexpected beauty of algorithmic collaboration. As the tango unfolds, the song expands into a rhythmic chant—a playful explosion of technological descriptors—that mirrors the hypnotic repetition of code itself. Joyfully self-aware, genre-bending, and sonically cinematic, Algorithmically Elevated sounds like what happens when inspiration and innovation dance cheek-to-cheek.

Genre Tags: Tango Fusion, Electro-Orchestral, Experimental Pop, Cinematic Pop, Indie Electronic, Accordion-Pop Fusion

Mood Tags: Innovative, Playful, Dramatic, Futuristic, Cinematic, Energetic, Clever

For Fans Of: Gotan Project, Astor Piazzolla (modern-influenced), Stromae, Björk (collaborative/experimental phase), Andrew Bird (orchestral whimsy), The Avalanches (collage-style builds)

Algorithmically Elevated by Johnny Diggz Single Cover

Lyrics

Johnny Diggz – Algorithmically Elevated

Digital whispers in the night
Algorithms spark the light
Partners, in this dance, we weave
Together in music we conceive

From glitches we ignite
Crafting worlds in pixelated sight
Limitations become our guide
In algorithmic beats, no one’s ever tried

Constraints lead to revelation
In this digital creation
Boundaries spark the inspiration
A new kind of collaboration

Algorithmically elevated
Our muse, simulated
In this dance we find our way
Where human touch meets digital play

Binary symphonies play (hey-hey)
Lines of code in bright array
With each constraint we find a way
To turn the night into day

In the glitch, an evolution
Unforeseen and bright conclusion
We break the code, transcend design
Merging words and thoughts in time

Algorithmically elevated
Our muse simulated
In this dance we find our way
Where human touch meets digital play

Algorithmically elevated
Dynamically generated
Programmatically orchestrated
Systematically integrated
Computationally simulated
Artificially animated
Digitally celebrated
Technologically innovative

It’s just a glitch
An evolution
Unforeseen and bright conclusion
We break the code
Transcend design
Merging words and thoughts in time

Algorithmically elevated
Our muse, simulated
In this dance we find our way
Where human touch meets digital play

Algorithmically elevated
Dynamically generated
Programmatically orchestrated
Systematically integrated
Computationally simulated
Artificially animated
Digitally celebrated
Technologically innovative

Algorithmically elevated
Dynamically generated
Programmatically orchestrated
Systematically integrated
Computationally simulated
Artificially animated
Digitally celebrated
Technologically innovative

Algorithmically elevated
Dynamically generated
Programmatically orchestrated
Systematically integrated
Computationally simulated
Artificially animated
Digitally celebrated
Technologically innovative

Algorithmically Elevated by Johnny Diggz Album Cover

When Power Can’t Take a Joke

The Bible already had it figured out: don’t curse the king, a bird might hear you and snitch. Leaders haven’t grown a sense of humor since.

The Old Tricks

Hitler jailed comics like Werner Finck for slipping jokes past the censors. Ordinary Germans lost their heads—literally—for cracks about the Führer. Mussolini closed satire mags and handed out prison time for offhand wisecracks. Franco’s Spain fined and shuttered satirical papers, sometimes with a mob and a chain for emphasis. Britain kept the Lord Chamberlain’s red pen on plays until 1968. Thailand still locks people up for jokes about the king’s dog. Spain manages to jail rappers in the 2020s for lyrics about the monarchy.

Different uniforms, same idea: ridicule the leader, lose your stage, your job, or your freedom.

The American Way

We like to think the First Amendment solves this. Not really. The playbook here is softer but familiar:

Jimmy Kimmel’s show pulled after a monologue. Conveniently, the FCC was rattling license chains and Trump cheered from the sidelines. Stephen Colbert gone from CBS in the middle of a merger that needed regulatory goodwill. DOJ mulling RICO charges for hecklers shouting at the president. Calling a chant “organized crime” is a stretch even by D.C. standards.

No Gestapo raids, just a phone call from the regulator and a nervous boardroom. The result feels the same.

Musk’s “Free Speech” Pitch

Elon Musk says Twitter cost him $44 billion because he had to “restore free speech.” Meanwhile, comedians are dropped for monologues and protesters get painted as racketeers. Funny how “free speech” always seems to cover your own microphone, not the heckler’s.

The Pattern

Authoritarians jail you outright. Democracies nudge your employer until you’re gone. Either way, the jester’s mic goes dead. And when the jokes dry up, it’s not comedy that’s in trouble—it’s the culture around it.

One Way Out

(Or: How the Democrats Could Learn a Thing or Two from Luthen Rael)

In Andor, Luthen Rael builds a rebellion out of misfits, radicals, careerists, and killers. He doesn’t ask if they’re pure. He asks if they’re useful. If they understand what’s at stake. If they’ll act.

That’s how you build a movement. That’s how you win.

Meanwhile, the modern Democratic Party can’t stop tearing itself apart over imperfection. Say the wrong thing, vote the wrong way, or fall one inch short of the current litmus test, and suddenly you’re not an ally—you’re the problem. The knives come out, and the left eats its own while the right consolidates power.

It’s like trying to form the Rebellion but canceling Cassian for his past, rejecting Mon Mothma for playing it safe, and calling Saw Gerrera a liability. The only people left would be the ones who’ve never risked anything.

You don’t get a rebellion without friction. You don’t get progress without uncomfortable alliances. And you don’t get power by demanding that everyone talk and tweet like your friend group.

The right rewards loyalty. The left demands purity. And guess who keeps winning?

In Andor, when the prisoners rise up on Narkina 5, they don’t stop to argue about who deserves to lead. They don’t vet each other’s credentials. They just run. Together. Chanting the same thing over and over as they break free.

One way out.

That’s the lesson. If you want to escape the tightening grip of authoritarianism, if you want to change the system, if you want a shot at something better—stop attacking the people who are mostly with you.

Because there’s only one way out.

And it’s together.

Why Podcasting is Key for AI-Driven Content Strategies

In an era where AI-driven search engines and large language models (LLMs) are reshaping how content is discovered, marketing leaders must rethink their approach to content strategy. Blog posts and social media are no longer enough—businesses need engaging, long-form, high-value content that not only builds authority but also works with AI-powered search. Enter podcasting.

Podcasting has emerged as one of the most effective content marketing tools for brands looking to increase visibility, establish thought leadership, and create lasting connections with their audience. However, while the benefits are clear, the process of launching and maintaining a high-quality podcast can be overwhelming.

Why Podcasting is a Smart Content Marketing Strategy in the Age of AI

AI-driven search engines and LLMs prioritize rich, contextual content that provides in-depth answers to user queries. As voice search and conversational AI become more prevalent, podcasts provide a unique advantage:

  • AI Loves Spoken-Word Content – LLMs process and prioritize audio transcripts, making podcast content highly indexable for search engines.
  • Long-Form Engagement Wins – Unlike short social media posts, podcasts hold audience attention for 20+ minutes, creating deeper connections with listeners.
  • Audio SEO Boosts Discoverability – Transcripts, metadata, and summaries make podcasts an invaluable part of a brand’s SEO strategy.
  • Repurposable Content – A single podcast episode can be transformed into blog posts, LinkedIn articles, YouTube shorts, and social media snippets, maximizing reach.

The Hidden Costs and Challenges of DIY Podcasting

Many companies attempt to launch a podcast in-house, only to quickly realize the complexity and cost involved. A well-produced podcast requires:

  • Equipment & Setup – Costs range from $20 to $5,000+, depending on the level of quality desired. While a basic USB mic and computer can do the trick, professional sound quality often requires additional investments in XLR microphones, audio interfaces, and acoustic treatment.
  • Production Expertise – Audio engineering, editing, and mastering are crucial for maintaining a polished, listenable show. Without experience, achieving professional quality can be difficult.
  • Time Investment – Researching topics, booking guests, scripting, recording, editing, and publishing each episode requires significant hours. Even a small production schedule can take up 10-20 hours per episode.
  • Content Consistency – Podcasts thrive on regular publishing schedules, which can be difficult to maintain with internal teams juggling multiple priorities.
  • Marketing & Distribution – Simply publishing a podcast isn’t enough; building an audience requires targeted promotion, cross-platform distribution, and engagement strategies.
  • Measuring ROI – Tracking performance metrics and tying them back to business objectives is more challenging than with traditional digital content.

The Advantages of Professional Podcast Production (Podcasting-as-a-Service)

For brands that want a high-quality podcast without the operational headaches, professional podcast production services offer a streamlined alternative. Podcasting-as-a-Service is a great way to introduce your brand to new audiences with little overhead.

  • Basic Production Services ($1,000+/mo) – Covers technical aspects like editing and post-production but excludes elements like guest scheduling, scripting, and promotion.
  • Standard Production Services ($2,000+/mo) – Includes post-production editing, social media graphics, and occasional re-recording but may not offer full strategic support.
  • Premium Production Services ($3,000-$6,000+/mo) – Comprehensive solutions that include episode production, post-production, guest scheduling, scripting, video podcasting, and social media amplification.

The Future of Brand Storytelling

Podcasting isn’t just another content trend—it’s a fundamental shift in how brands engage with their audience. As AI and search technologies continue to evolve, long-form, spoken-word content will only become more valuable. The smartest brands recognize this and are positioning themselves as industry leaders through podcasting.

For those looking to expand their content strategy, investing in a well-produced podcast can be a powerful tool for brand visibility, authority, and engagement.

Is America’s Decline Inevitable?

Ray Dalio says ‘all Americans’ should be happy with the election outcome because a peaceful power transfer is a massive ‘risk reduction’, however, Dalio also argues that America’s current challenges follow a predictable historical pattern. Every global power eventually declines, replaced by a rising challenger. But is this time different?

The Signs of Decline

Ray Dalio’s Big Cycle Theory

According to Dalio’s Big Cycle theory, several warning signs emerge when powers begin to fade:

  • Growing wealth inequality
  • Political polarization
  • High debt levels
  • Currency pressures
  • Rising foreign competition

Sound familiar?

Why This Time Might Be Different

America has unique advantages previous powers lacked:

  • Technological dominance
  • Geographic security
  • Deep financial markets
  • Global cultural influence

The China Question

China’s rise mirrors previous power transitions. But key questions remain:

  • Can China overcome its internal challenges?
  • Will technological competition reshape traditional power dynamics?
  • Is conflict inevitable, or can both powers coexist?

Learning from History

Tracking the Great Empires

Previous transitions (Dutch to British, British to American) happened under different conditions. Today’s interconnected world adds new complexity to old patterns.

What’s Next?

Understanding these cycles raises crucial questions:

  • Can we address inequality while maintaining innovation?
  • How do we strengthen institutions without sacrificing dynamism?
  • Is decline preventable if we recognize the patterns?

Rather than accepting decline as inevitable, perhaps understanding these cycles is the first step in transcending them.

What do you think: Are we watching history repeat itself, or can America write a new chapter?

Watch Ray Dalio’s “Principles for Dealing with the Changing World Order”

LLMO School Part 5: Leveraging User Intent and Search Intent for AI Optimization

Ever wonder why some content seems to get better results from AI tools like ChatGPT? The secret isn’t just in what you write — it’s understanding why people are searching in the first place. Let’s dive into how you can make AI work better for your content by getting inside your users’ heads.

The Heart of the Matter: Why Intent Matters
Think of user intent like a compass. When someone types a query into a search bar or asks an AI a question, they’re not just throwing words into the void — they’re trying to accomplish something specific. Maybe they’re hunting for information, looking for a particular website, or ready to make a purchase. Understanding these motivations is crucial because modern AI systems are getting remarkably good at picking up on these subtle cues.

Breaking Down User Intent
Let’s look at the three main types of intent you’ll encounter:

The Knowledge Seekers
These are your “how do I…” and “what’s the difference between…” folks. They’re in learning mode, and your content needs to meet them there. When writing for these users:

– Break complex topics into digestible chunks
– Use clear headings that answer specific questions
– Include real-world examples that illuminate abstract concepts
– Add visual aids where they truly add value (not just for show)

The Navigators
Some users know exactly where they want to go — they just need directions. Maybe they’re looking for your pricing page or trying to find your contact information. Help them out by:

– Creating clear, logical site structures
– Using descriptive link text (forget “click here”)
– Making your brand-specific terms prominent where it makes sense

The Action Takers
These users have their credit cards ready or are prepared to sign up. They don’t need to be convinced — they need a clear path forward. For these folks:

– Put your calls-to-action where they make sense, not just everywhere
– Create a smooth, logical flow toward conversion
– Use action-oriented language that feels natural, not pushy

Making It Work in Practice

Here’s a real-world example: Let’s say you’re running a cooking website. The same recipe might need to serve different intents:

– The knowledge seeker wants to understand why you knead bread dough
– The navigator wants to jump straight to your sourdough recipe
– The action taker wants to buy your recommended stand mixer

Your content needs to serve all three without feeling like it’s trying to be everything to everyone. You might structure your recipe page with:

– A quick “jump to recipe” button for navigators
– Clear, explained steps for knowledge seekers
– Natural product recommendations for action takers

Measuring What Works

Don’t just fire and forget. Keep an eye on how users interact with your content:

– Are people sticking around to read your detailed explanations?
– Do they find what they’re looking for quickly?
– Are they taking the actions you hoped they would?

Use these insights to refine your approach. Maybe that detailed technical explanation needs more real-world examples, or perhaps your call-to-action needs to come earlier in the journey.

The Big Picture

Understanding user intent isn’t about gaming the system — it’s about creating content that genuinely serves your audience’s needs. When you align your content with what users actually want, you’re not just optimizing for AI — you’re building something that works better for everyone.

Remember: The best content feels like a conversation with someone who genuinely understands what you’re looking for. Focus on that, and both human readers and AI systems will recognize the value you’re providing.

LLMO School Part 4: Optimizing Content for Voice Search

Voice search is booming, thanks to AI assistants like Alexa, Siri, and Google Assistant. Optimizing your content for voice search is a crucial part of AI content optimization. It’s all about making your content easy for these AI tools to understand, interpret, and deliver to users in a way that feels natural. Today, we’ll explore how to tailor your content so it’s voice-search-friendly, boosting your voice search optimization and helping you stay ahead in the AI game.

Voice search users tend to phrase their queries differently than they would when typing — they use full questions or conversational phrases. This means your content needs to be structured in a way that mimics these natural speech patterns. When you align your content with the way people talk, you also make it easier for natural language processing (NLP) content systems to extract useful information. Let’s look at how to optimize your content for voice search in an AI-driven world.

How to Optimize for Voice Search

1. Target Conversational Keywords

Unlike traditional SEO, which often focuses on short keywords, voice search optimization means targeting longer, more conversational phrases. Think about what questions people might ask aloud. Instead of “best pizza recipe,” users might say, “What’s the best pizza recipe for beginners?” By targeting these kinds of conversational keywords, you can enhance your AI SEO and make your content more accessible to voice search users.

2. Include Direct Answers

Voice search results need to be quick and concise, so make sure your content provides direct answers. If you’re writing a guide, add a section that explicitly answers common questions users might ask. This format is ideal for conversational AI optimization, making it easier for voice assistants to pull direct information and deliver it quickly.

3. Use Structured Data

Incorporating schema markup is essential for making your content AI-friendly. Adding structured data makes it easier for LLMs and other AI to identify and extract relevant answers from your content, which directly benefits voice search optimization. A well-marked-up FAQ page, for example, can increase your chances of being the answer a voice assistant chooses.

4. Focus on Local Searches

Many voice searches are for local information, like “Where’s the best coffee near me?” Make sure your content is optimized for local SEO. Use phrases that match what local users might ask, and keep your Google My Business profile updated. This enhances both your machine learning content optimization and voice search performance for users looking for answers nearby.

5. Make Your Content Scannable

Voice search prioritizes content that’s easy for AI to digest. Use headings, bullet points, and numbered lists to break down information. By making your content scannable, you help voice search algorithms quickly find the specific details they need, boosting both content optimization for AI and the user experience.

Example: Optimizing a Recipe Blog for Voice Search

Let’s say you run a recipe blog, and you want to optimize for voice search. Instead of just listing “Best pizza recipe,” you could create a question-answer section: “What is the best pizza recipe for beginners?” and provide a short, direct answer followed by the full recipe. This way, if someone asks a voice assistant, “How can I make an easy pizza at home?” your content is more likely to be selected by the LLM to answer the query.

Voice search is becoming a major part of how people interact with AI-driven devices, so optimizing for it is key to any solid AI-driven content strategy. By focusing on conversational phrases, direct answers, structured data, and local relevance, you can ensure your content stands out in voice searches. Stay tuned for the next installment of LLMO School, where we’ll continue exploring how to make your content shine in the world of AI.

LLMO School Part 3: Building an AI-Driven Content Strategy

What exactly is an AI-driven content strategy? In a nutshell, it’s about creating content that’s structured, easy to process, and fits naturally into how AI-powered tools like ChatGPT interpret information. This approach ensures your content is discoverable, engaging, and optimized for both AI content optimization and AI SEO.

How to Build an AI-Driven Content Strategy

1. Start with Intent

AI systems prioritize content that aligns with user intent. When creating your content, think about what your audience is really searching for. What questions are they asking? What problems are they trying to solve? Understanding user intent is key to making sure your content hits the mark for natural language processing (NLP) content systems, as these models are trained to deliver results that closely match what users are asking for.

2. Focus on Topic Clusters, Not Keywords

Traditional SEO focuses heavily on keywords, but an AI-driven strategy shifts to broader topic clusters. Instead of targeting single keywords, focus on creating clusters of content around core topics. This helps LLMs understand the broader context of your content and boosts your chances of being surfaced in relevant searches. Topic clusters also make your AI-driven content strategy more future-proof, as AI gets better at understanding relationships between concepts over time.

3. Optimize for Readability and Structure

Clean structure is just as important for content optimization for AI as it is for human readers. Make sure your content is broken down with clear headings, subheadings, and bullet points. LLMs work best when they can quickly scan your content, picking out key points and delivering relevant answers. This approach also ties into voice search optimization, where users are often looking for quick, concise answers to their queries.

4. Leverage Data and Analytics

Don’t just guess at what’s working — use data to drive your strategy. Look at which content performs well with your audience and tailor future posts to match. AI tools, including those that assist with machine learning content optimization, thrive on data. The more you feed them content that has already proven successful, the better your overall content strategy will perform.

5. Plan for Regular Updates

AI systems like LLMs value fresh, up-to-date content. By regularly reviewing and updating your older posts, you improve your chances of being featured in AI SEO results. This not only ensures your content remains relevant to human readers but also keeps it top of mind for AI algorithms.

Example of an AI-Driven Content Strategy in Action

Let’s say you run a site about fitness and health. Instead of creating individual posts on “best workouts” and “healthy diets,” an AI-driven strategy would have you create a central pillar page on “building a healthy lifestyle” with detailed guides on both workouts and diets as supporting content. This creates a network of related topics that LLMs can easily understand and reference when users ask broad questions like “how do I live a healthier life?”

Building an AI-driven content strategy is essential for ensuring your content is both effective and future-proof. By focusing on user intent, creating topic clusters, and optimizing for both readability and structure, you’ll make your content more accessible to AI-powered tools like ChatGPT.

Stay tuned for the next post in LLMO School, where we’ll keep exploring how to refine your content for large language models and beyond.