Hamsterdam Part 55: Weekly SEO & AI News Recap (4/22 to 4/28, 2024)
By Ethan Lazuk
Last updated:
A weekly look-back at SEO & AI news, tips, and other content shared on social media & beyond.
Opening notes:
- Welcome to another week of Hamsterdam!
- I took a hiatus from social media this week to focus on other projects. It was quite cathartic! But, I do believe the magic of Hamsterdam recaps are its social posts — we can often find glimpses of SEO or AI tidbit gold in random tweets or LinkedIn posts. This will be the first recap focused on articles mainly. I think you’ll find it valuable, but expect more social content next week!
In other Hamsterdam news …
- In Hamsterdam Research, we looked at Google DeepMind’s PLEDGE framework for balancing attribution and specificity in conversational AI responses; this contains some lessons that I think are valuable for human-generated content, as well!
- In Hamsterdam History, we looked at the history of Microsoft’s search engines, beginning with MSN Search to the latest Bing innovations.
- I also created a Hamsterdam History playlist on YouTube, where the first video is about Searchology 2009 and the introduction of Google’s Search Options.
Want Hamsterdam recaps delivered? Subscribe to the free newsletter! (It’s pretty much a link to this article, but it’ll be conveniently emailed to you.) 😉
*Feel free to jump down to this week’s recap, or continue reading for “This week in SEO history,” an introduction, and a summary of the week’s SEO and AI news!
This week in SEO history: Ben Gomes Khan Academy interview
On April 22nd, 2021, Ben Gomes gave an Ed Talk with Khan Academy. Though this isn’t too long ago, I think it’s worth revisiting.
Ben first recounts how he spent 20 years in search at Google.
“When I thought about search, a lot of it for me was being able to answer that curiosity of the moment. Being able to get that answer really quickly that it stimulates more curiosity in the long run.”
– Ben Gomes
He describes his influences, including his mother, a geography school teacher, a priest “who really influenced my thinking about the importance of service and serving others,” and a chemistry teacher, who inspired an interest in science.
He discusses uses of technology for classroom learning, including helping students get feedback, like related to literacy.
He also talked about Google Lens in the context of connecting learning with the outdoors, like for botany.
To a question of whether people are getting smarter, Ben mentions how search allows for the exploration of information and to “build that muscle within us of curiosity.”
On the topic of global education, he mentions how, “I’ve always been interested in education in the context of India, because that’s where I grew up.” (He also wrote about his childhood in India in a 2018 blog post on The Keyword.)
To a question about what skills students need for the future, Ben mentions it “changes faster and faster and faster pace, so one of the key skills I think is getting comfortable with learning, which is why I come back to that notion of curiosity, because that’s what makes learning fun.”
He elaborates:
“Language is going to to continue to be important. Mathematics and the sciences and so on and continue to be important, but as foundational. But beyond that, I think there are different skills that we’ll need over time that are going to be hard to predict right now, and so being flexible and adaptable to that future, I think, is going to be really important for people to not just survive, but thrive in that future.” [Highlights added.]
– Ben Gomes
To a question of leveling the playing field and biases, Ben mentions machine learning and AI and thinking about “are we training them in the right ways” or “are we just replicating our existing biases in these new forms.”
He also mentions being “user-centric” and how “Google has this focus on the user and other things will follow.”
The last question asks, “What sacrifices have you made in your own journey to get where you are today?”
His response:
“I feel I’ve been really fortunate and a beneficiary of a lot of what other people around me have done. And I feel the need to serve others as a result of that.”
– Ben Gomes
On his advice for learners Ben says:
“What has served me well, actually, is a breadth of interests. Because when I started working, even at Google, I worked on infrastructure projects within Google on PageRank and things like that. I worked on ranking. But then I began to be involved with user interfaces and things of that sort. But what I felt that served me well was finding out what’s interesting in that area, and then being able to pursue it. So, I would say find the interesting thing in almost anything that you are learning and pursue that. It gets to what makes learning, I think, interesting and fun and not just a task.” [Highlights added.]
– Ben Gomes
The interview is a good reminder to stay curious. And well intentioned.
Speaking of learning, let’s get to our introduction this week …
A look into the enduring importance of public libraries!
Introduction to week 55: “where are the books?”
This week, my wife, Dania, took off Friday from work, so I knocked off early as well.
We took a walk around downtown Orlando, as we’re prone to do, and then she took me to the library.
I used to frequent the library in college and high school.
But I hadn’t been to a public library in probably 10 years.
When we first walked in, there was a display of Arab-American books. This was cool, because Dania is, herself, an Arab-American (born in Saudi Arabia):
But those were like the only books we saw for a while …
The first floor was mostly digital media, like CDs and DVDs, etc.
We went to the second floor, where things got really interesting …
There were video editing bays, podcast rooms, recording studios, VR simulators, and lots of classrooms.
These classrooms teach all sorts of digital skills.
Just look at this list of 6,000+ classes: 3D printers, building robots, Adobe After Effects, etc.
There are also classes like public-speaking skills and conversational English, as well as free services like mobile showers.
Then we went up to the third floor, which had the books.
Ironically, the book floor also had most of the people on it, except many were taking naps or watching movies on their phones.
When we talk about the evolution of technology and society, I think this library visit is a perfect example of that.
The library is no longer about books. In fact, they’re kind of a dusty afterthought.
The library is about digital skills and social services.
I had no idea.
At a minimum, I’m enrolling in a couple of the classes, starting with “Creative Resources for Entrepreneurs” this Monday.
I’m also going to see about getting digital marketing, SEO, or AI into the class offerings. 😉
But I also want to help spread the word that these resources are available. I’m not even sure if the people on the book level knew …
If you haven’t been to your local library lately, check it out! You may be surprised.
Buckle up for a full week’s recap, and enjoy the vibes:
Thank you for supporting Hamsterdam and the cause of SEO & AI learning.
Missed last week? Don’t worry, I got you! Read Part 54 to catch up.
Other great sources of weekly SEO news:
- The SEO Weekly – Garret Sussman, iPullRank
- SEOFOMO – Aleyda Solis
- Weekly Video Recaps – Barry Schwartz, SER
- Weekly SEO News YouTube channel – Olga Zarr, Seosly
- Niche Surfer – Yoyao Hsueh
Now, time for our weekly review of SEO social posts, articles, & more …
Quick summary
- Google’s March core update low-key concluded; I’m currently sitting in pos. 1 for “Orlando SEO Consultant,” so that’s cool!
- Ed Zitron wrote quite the piece; I wasn’t on social media this week, which was probably a good thing, ha.
- We’ll get back to social media in next week’s recap, but I hope you enjoy the focus on articles this week! (I put quite a few of them.) 🙂
Jump to a section of this week’s recap:
- News, Google updates, & SERP tests
- SEO tips & tidbits
- Fundamentals & resources
- Articles, videos & case studies
- Local SEO
- Technical SEO
- Content marketing
- AI, LLMS, & machine learning
- Humor section
- Miscellaneous & general posts
- Older stuff that’s good!
Or keep scrolling to see it all.
Ok, time to step inside the white flags of Hamsterdam …
SEO news, Google updates, & SERP tests
These are newsworthy events in the SEO world, search engine updates, or SERP tests to be aware of from the last week.
Google March 2024 Core Update Finished April 19th (A Week Ago) – Barry Schwartz, SER
Quote: “The Google March 2024 core update finished a week ago and Google did not tell us until today. It finished officially on April 19, 2024, and took 45 days to roll out after starting on March 5, 2024. Google also said this helped reduce low-quality and unoriginal content in search results by 45%, which is up from their estimate of 40%.”
Google Warns Of “New Reality” As Search Engine Stumbles (UPDATE) – Matt G. Souther, SEJ
Quote: “In an all-hands meeting last month, Raghavan, who oversees Google’s Search, Ads, Maps, and Commerce divisions, acknowledged that the industry has shifted from the tech giant’s earlier dominance.”
The Man Who Killed Google Search – Edward Zitron, Where’s Your Ed At?
Quote: “These emails are a stark example of the monstrous growth-at-all-costs mindset that dominates the tech ecosystem, and if you take one thing away from this newsletter, I want it to be the name Prabhakar Raghavan, and an understanding that there are people responsible for the current state of technology.”
Google CEO says AI overviews are increasing Search usage – Danny Goodwin, SEL
Quote: “This was followed later by a question seeking more color around AI changing Search volume or Google use cases. Pichai answered with a non-answer about Google’s positive and profound path: ‘We view this moment as a positive moment for Search. And I think it allows us to evolve our product in a profound way. And Search is a unique experience. People come and they get to — be it if you want answers, if you want to explore more, if you want to get perspectives from across the web and to be able to do it across the breadth and depth of everything they are looking for and the innovation you would need to keep that up, I think it’s what we’ve been building on for a long time.’”
Note: Check out my Searchology 2009 article (Hamsterdam History) that mentions “slice and dice” and “explore” as search journeys. I think it relates to this type of statement.
Big Update To Google’s Ranking Drop Documentation – Roger Montti, SEJ
Quote: “The biggest change by far is their brand new section for algorithmic changes which replaces two smaller sections, one about policy violations and manual actions and a second one about algorithm changes.”
Note: One of my earliest blog articles on this site was about organic traffic changes unrelated to rankings. In my experience, dynamics with paid ads, social media virality, or offline media can be additional factors, depending on your brand, audience, and marketing mix.
Here’s an early look at Google Gemini’s integration with music streaming apps – Chethan Rao, Android Police
Quote: “In my own experience, Gemini was really fun to use the first few days, but the novelty wore off eventually, mainly due to its inability to recognize music-related commands. With support for music streaming services now on the cards, we expect more Android smartphone users to switch over to Gemini.”
Green search engine Ecosia launches a cross-platform browser – Ivan Mehta, TechCrunch
Quote: “With this new browser, Ecosia is also starting an affiliate shopping program, meaning that users will see links to shopping sites such as Amazon, eBay and Decathlon under the sponsored links section. The company said all the money earned through affiliate revenues will go toward planting trees and backing similar green projects. Through this kind of investment, Ecosia has committed to generating 25Wh of clean energy per user each day.”
FCC restores net neutrality – Perplexity (Thread)
Quote: “The Federal Communications Commission (FCC) has officially restored net neutrality regulations, which were initially implemented in 2015 but repealed in 2017 during the Trump administration. This decision, made on April 25, 2024, marks a significant shift in the regulation of broadband internet providers like Comcast and AT&T, ensuring they treat all internet traffic equally without discrimination”
SEO tips & tidbits
This section has actionable tips, cool tidbits, and other findings and observations that can be teaching moments.
How to harness the power of brand mentions across the search universe – Ashley Liddel, SEL
Quote: “Every mention serves as a digital beacon, a brand bat signal if you like, potentially reaching new audiences across these diverse platforms.”
Google Confirms Links Are Not That Important – Roger Montti, SEJ
Quote: “The reason why Google doesn’t need many links is likely because of the extent of AI and natural language understanding that Google uses in their algorithms. Google must be highly confident in its algorithm to be able to explicitly say that they don’t need it.”
Structure, consume, learn and retire: Google’s pattern of learning – James Allen, SEL
Quote: “The race is for the search engine to learn from webmasters’ interactions with Google’s suggested structure before they can learn to manipulate it. Google usually wins this race. It doesn’t mean no one can leverage new structural items before Google discards them. It simply means that Google usually discards such items before illegitimate manipulations become widespread.”
6 Things SEOs Should Advocate for When Building a Headless Website — Whiteboard Friday – Peter Richman, Moz
Quote: “So, with your front-end interface, it’s likely that an engineer or a developer is going to have to hook that up to the API and make sure that’s being interpreted in the right way. So when you’re thinking about this, what we’d love you to do is look at all the data you’d want on your pages and all the considerations, so everything from sorting and searching and organizing categories, subcategories, how you’re going to manage that data within the taxonomy of your back end so that you have everything you possibly need now and in the future for your front-end interface.”
SEO (and AI) fundamentals & resources
If you’re new to SEO, this section is for you and includes essential information, concepts, or resources to learn more.
AI has a lot of terms. We’ve got a glossary for what you need to know – Laura Bratton and Brtiney Nguyen, Quartz
Quote: “Generative artificial intelligence is a category of AI that uses data to create original content. In contrast, classic AI could only offer predictions based on data inputs, not brand new and unique answers using machine learning. But generative AI uses ‘deep learning,’ a form of machine learning that uses artificial neural networks (software programs) resembling the human brain, so computers can perform human-like analysis.”
Grow with Google launches new AI Essentials course to help everyone learn to use AI – Lisa Gevelber, The Keyword
Quote: “In this course you’ll learn from our own AI experts at Google and gain hands-on experience using AI. For example, you’ll learn how to use AI tools to help: Develop ideas and content. … Make more informed decisions. … Speed up daily work tasks.”
Understanding Key Terminologies in Large Language Model (LLM) Universe – Adnan Hassan, MarkTech Post
Quote: “Contextual embeddings are representations of words that consider the context in which they appear. Unlike traditional embeddings, these are dynamic and change based on the surrounding text, providing a richer semantic understanding.”
Anatomy of a Search Result – Google Search Central
Gemini for Social Posts, Search Off the Record – Google Search Central
Articles, videos, case studies & more
These are longer-form content pieces shared on social and elsewhere.
How to launch a product-led SEO strategy – Maria Georgieva, SEL
Quote: “This article will help you transition from a keyword-focused to a customer-centric SEO strategy, offering practical tips for integrating both approaches effectively.”
Google’s New Infini-Attention And SEO – Roger Montti, SEJ
Quote: “Lastly, the ‘continual pre-training and long-context adaptation’ makes it ideal for scenarios where there’s a stream of new data that’s constantly needed to be added to train a model. That last part is super interesting because it may make it useful for applications on the back end of Google’s search systems, particularly where it is necessary to be able to analyze long sequences of information and understand the relevance from one part near the beginning of the sequence to another part that’s closer to the end.”
Local SEO
If you’re into local Search, this section is for you.
Regaining Trust: Lessons Learned From Losing a Local SEO Client – Joy Hawkins, Moz
Quote: “We believe that educating clients is important and are always looking for ways to improve how we can do that. It just so happens that this particular client attended one of these webinars and ended up coming back to us just a month ago.”
How To Request Ownership of a Business Profile – Colan Nielsen, Sterling Sky
Quote: “If you are a business owner or a marketer who forgot the credentials to your Google business listing or a listing you manage, you can follow these steps to claim access to your listing.”
Technical SEO
Everything from basics to advanced techniques.
How to Relaunch a High Ranking Websites: 11-Steps to Protect Your Rankings – Andy Crestodina, Orbit Media Studios
Quote: “Scanning through the research, you’ll notice that different URLs have different types of value and therefore different risks and opportunities. Some rank but get no traffic. Others get search traffic but don’t convert. Some have links but no rankings. Some are worthless. Some are priceless.”
Content marketing
From what is helpful content to user journeys and beyond.
Information Gainz: #250 Prioritizing information gain = rethinking how we create content – Kevin Indig, Growth Memo
Quote: “It makes sense from Google’s perspective. Search is valuable because it gives users a curation of the best answers. If every answer is the same, Google might as well give a single answer with SGE. A lack of content diversity reduces the importance of having several results. The question then is: how can we adapt our content creation process to prioritize information gain?”
How to use data stories for SEO – Eli Schwartz, Eli’s Newsletter
Quote: “The goal for any story, data or not, is to be as attractive as possible, thereby gaining follow-on activity like engagement and links. An uninteresting story supported by data is still a bland story.”
AI, machine learning, & LLMs
A section dedicated to artificial intelligence news, tips, and articles.
The Age of Generative AI: Over half of Americans have used generative AI and most believe it will help them be more creative – Vivek Pandya, Adobe
Quote: “New Adobe research found that more than half of all Americans have taken generative AI for a spin in the past year, and more than eight in ten anticipate it will help them be more creative. … More than 80 percent believe it will make life easier and more than half believe it can help them learn a new skill in the next few years. One area where generative AI is particularly appealing to the American public is e-commerce. Consumer expectations are changing fast, and Americans are excited about how generative AI can help them make price comparisons, shop and receive customer support. In fact, 41 percent of people expect brands to use generative AI in their customer experiences today.”
This AI Paper Explores the Fundamental Aspects of Reinforcement Learning from Human Feedback (RLHF): Aiming to Clarify its Mechanisms and Limitations – Sajjad Ansari, MarkTech Post
Quote: “Researchers finetuned RLHF of Language Models (LMs) by integrating the trained reward model. Also, Proximal Policy Optimization (PPO) and Advantage Actor-Critic (A2C) algorithms are used to update the parameters of the LM. It helps maximize the obtained reward using generated outputs. These are called policy-gradient algorithms that update the policy parameters directly using evaluative reward feedback. Moreover, the training process includes the pre-trained/SFT language model that is prompted with contexts from a prompting dataset. However, this dataset may or may not be identical to the one used for collecting human demonstrations in the SFT phase.”
What this means: Policy-gradient algorithms analyze the rewards an LLM gets based on its outputs and makes adjustments to its parameters to improve its policy (how it chooses actions.) based on the feedback received.
How to turn any LLM into an embedding model – Ben Dickson, TechTalks
Quote: “In a new study, researchers at Quebec AI Institute (Mila) and ServiceNow Research introduce LLM2Vec, a simple unsupervised approach that can transform any decoder-only LLM into a strong text encoder. Experiments show that LLM2Vec models have state-of-the-art performance on embedding tasks. … There are several reasons for decoder-only LLMs to be suitable for embedding tasks. First, their training recipe makes them learn from all input tokens as opposed to encoder models that mask part of the input during training. Second, there is a lot of activity on decoder LLMs, and there is a rich ecosystem of models, techniques, and tools to choose from. Finally, LLMs that have been fine-tuned for instruction following and human preferences can be very suitable foundations for universal text embedding models that generalize across many tasks.”
What this means: Embeddings are numerical representations of text data (vectors) used in machine learning, natural language processing, as well as semantic search engines. Researchers created a method called LLM2Vec for turning text-generating LLMs into embedding models. Traditional embedding models (encoders) hide parts of text during training. But LLM2Vec (using a decoder-only LLM) can see whole sentences or the entire text at once, instead of processing left-to-right, for better context (understanding of relationships between words) and embeddings.
DeepMind researchers discover impressive learning capabilities in long-context LLMs – Ben Dickson, VentureBeat
Quote: “A new study by researchers at Google DeepMind explores the ‘many-shot’ in-context learning (ICL) ability of LLMs that have very long context windows. Their findings show that by fitting hundreds or even thousands of training examples in the prompt, you can improve the model’s abilities in ways that would previously require fine-tuning.”
What this means: In-context learning involves giving solved examples in the prompt, along with the desired problem. Whereas fine-tuning involves changing the parameters (weights) of the model, this eliminates that need. It also can replace RAG models, where the LLM is augmented with an external knowledge source. As the article notes, “the model’s performance continues to improve as more examples are added to the prompt.” However, one issue is scalability.
Why we may be headed for a generative AI winter – Mark Sullivan, Fast Company
Quote: “Indeed, the AI industry at large is trying to push LLMs beyond ChatGPT-style text drafting and summarizing tools to become autonomous agents that can reason and make plans. ‘Emerging startups are now focusing on AI agents, which will act more independently from humans and complete tasks on behalf of humans on the internet and in other apps, without the human being present,’ says Jeremiah Owyang of Blitzscaling Ventures.”
What this means: I chose that quote above because it was interesting, but an AI winter is a period of decreased funding and interest in AI, basically after hyped expectations. It’s happened several times before, going back at least to the 1970s. As far as I can tell from reading about those periods, now feels different, given the rate at which advancements are coming, but it does seem “AI agents” are trending (as we saw in Hamsterdam Part 53).
Graph-based metadata filtering for improving vector search in RAG applications – Tomaz Bratanic, LangChain (Partner Post)
Quote: “Text embeddings and vector similarity search help us find documents by understanding their meanings and how similar they are to each other. However, text embeddings aren’t as effective when sorting information based on specific criteria like dates or categories; for example, if you need to find all documents created in a particular year or documents tagged under a specific category like “science fiction.” This is where metadata filtering or filtered vector search comes into play, as it can effectively handle those structured filters, allowing users to narrow their search results according to specific attributes.”
What this means: This is a specific use-case, but more generally, we can see how structured and unstructured data together (like schema, metadata, and document chunks) can contribute to more accurate vector search, where numerical representations are created from these data sources for similarity analysis. As SEOs, we can appreciate how connecting the dots between all types of data can build richer context for search engines and generative-AI responses with RAG applications.
The Economic Impact of Generative AI – Andrew McAfee, Visiting Fellow, Technology & Society at Google
Quote: “By one estimate, close to 80% of the jobs in the U.S. economy could see at least 10% of their tasks done twice as quickly (with no loss in quality) via the use of generative AI. Previous general-purpose technologies like the steam engine and electrification have brought their changes over decades. However, we anticipate that generative AI’s effects will be felt more quickly due to its ease of diffusion.”
What this means: In a very meta task, I uploaded this 30-page PDF to Gemini 1.5 Pro and asked for a 3-sentence summary: “This report argues that generative AI is a general-purpose technology with the potential to significantly accelerate economic growth due to its rapid improvement, pervasiveness across industries, and ability to spark complementary innovations. The report predicts that unlike previous general-purpose technologies, the impact of generative AI will be felt much faster due to existing infrastructure and ease of use, leading to increased productivity, job market shifts, and business transformation. It also highlights the importance of responsible development and deployment to maximize benefits and minimize risks, such as potential job displacement and bias.”
DeepMind Researchers Propose Naturalized Execution Tuning (NExT): A Self-Training Machine Learning Method that Drastically Improves the LLM’s Ability to Reason about Code Execution – Nikhil, MarkTech Post
Quote: “Despite their sophistication, large language models (LLMs) trained on code have struggled to grasp the deeper, semantic aspects of program execution beyond the superficial textual representation of code. This limitation often affects their performance in complex software engineering tasks, such as program repair, where understanding the execution flow of a program is essential. … Researchers from Google DeepMind, Yale University, and the University of Illinois have proposed NExT, which introduces a novel approach by teaching LLMs to interpret and utilize execution traces, enabling more nuanced reasoning about program behavior during runtime. This method stands apart due to its incorporation of detailed runtime data directly into model training, fostering a deeper semantic understanding of code.”
What it means: NExT is a methodology that integrates execution traces into training data for LLM models, improving their capability to understand and fix code. An execution trace is a record of what happens when code runs, like the values of different variables, order that lines were executed, or the final output. While LLMs can understand code as text, they struggle with execution traces, or what the code does. NExT embeds the execution traces into the code, like giving the LLM notes to explain each step. As a result, the LLM develops a deeper understanding of how the code runs and how to fix it.
Meta has gone all-in on open-source – All-In Podcast Clips
Tip to Fix Google – Flesh Simulator
Using ChatGPT to avoid writing like ChatGPT – Hard Fork Podcast (NYT)
Hey, dude, this is happening! (early internet) – Lacey Loves Horror
Apple LLM releases (OpenELM) – CJ Trowbridge
General marketing & miscellaneous
This is for great content that isn’t necessarily SEO or marketing-specific. PPC, PR, dev, design, and social friends, check it out!
Design for Humans, Rank for Google: The Designer’s Simple SEO Playbook – Nanjing Johnmark, Bootcamp (UX Design)
Quote: “The ‘SEO experts’ try to complicate it with all sorts of technical lingo about backlinks, keywords, sitemaps, and on and on. But at the end of the day, great SEO is just great UX. It’s about understanding the core user intent and then using your design skills to lay out content in a clear, visually appealing way that seamlessly guides users (and search engines) toward finding exactly what they’re looking for.”
Note: Not sure why the dig at SEO experts. Also, I wouldn’t ignore those “technical lingo” items, but I take your point, lol.
TikTok SEO: The ultimate guide – Cali Saturn, SEL
Quote: “SEO strategies for Google and TikTok share some similarities but also have notable differences. Both emphasize the importance of creating informative and helpful content tailored to the target audience’s search intent, weaving relevant keywords into the content and consistently producing quality content following platform best practices. However, one significant difference is that previous brand success doesn’t heavily influence rankings on social platforms like Instagram and TikTok, unlike Google, where brand authority plays a significant role.”
Note: There’s also a nice “TikTok SEO” video in Hamsterdam 28.
E-commerce personalization: helping users or exploiting their personal data? – Anna Rátkai, UX Collective
Quote: “If using personalization to push impulsive, excessive consumption is an unsustainable approach, we want to move towards the opposite: using it to help mindful, intentional consumption. Instead of going for a short-term spike in sales, let’s focus on nurturing long-term connections and thus increase lifetime value.”
Older stuff that’s good!
Not everything I find worth sharing is new as of this week, so these are gems I came across published in the past.
Prof. Geoffrey Hinton Forward-Forward Algorithm – MoroccoAI Conference (2022)
Professor Simon Prince – This is why Deep Learning is really weird. – Machine Learning Street Talk (2024)
Great job making it to the end. You rock!
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