Morning Walk With Murty

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The provided sources describe TRSTABLE, a modern digital platform founded by Geetika Saigal that calculates an evidence-based authority score for professionals. Unlike older tools like KRED that prioritised social media engagement, this system evaluates five key pillars: positioning, credibility, intellectual property, visibility, and impact. The text highlights a specific user's struggle with LinkedIn’s Persona verification, where a conflict between a legal name and a searchable brand identity hinders access to the tool. While the platform typically requires a LinkedIn login to scrape public data and generate reports, it aims to provide an objective look at one's internet-verified reputation. Ultimately, the sources illustrate the shift from measuring social influence to quantifying professional authority through third-party data.

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The Digital Identity Dilemma: TRSTABLE Authority vs. LinkedIn Persona | Morning Walk With Murty

00:00:00 Speaker 1: Welcome to the Morning Walk with Murdy Digital Stroll.

00:00:02 Speaker 2: It is great to be here.

00:00:03 Speaker 1: Yeah. And, um, I want to start by asking everyone to just imagine something for a second. Imagine spending over a decade building this thriving, sprawling digital city, right? Brick by brick, only to have, like, a bouncer lock you out today because the nickname you use isn't the exact one printed on your government passport.

00:00:23 Speaker 2: Yeah, it's it's a nightmare.

00:00:25 Speaker 1: It really is. And that is the exact friction point we were analyzing in today's source material. It's a massive roadblock for anyone trying to cement their digital legacy. So as the strategic auditor for this session, my focus is a laser targeted on the mechanics of digital migration.

00:00:41 Speaker 2: Right?

00:00:42 Speaker 1: I really want to look at how these massive digital systems talk to each other, how they process human identity, and well, more importantly, were they completely break down and fail the very people they're supposed to serve.

00:00:53 Speaker 2: Exactly. And, you know, speaking as the architect of Antaryami and the mentor of the Antrim VA Academy, my focus is entirely on Google two point zero. So my mission in this digital stroll is ensuring your true wisdom isn't just lost in administrative translation.

00:01:11 Speaker 1: Oh, absolutely.

00:01:12 Speaker 2: But before we get into the weeds, we should probably clarify some of the terminology we're going to be using today because we are looking directly through what we call the digital prism to, you know, extract the latest legacy code from project.

00:01:24 Speaker 1: Right, right, right. Let's break that down for a second. When we talk about the digital prism, we're talking about a concept similar to like an actual glass prism that splits white light into different colors.

00:01:32 Speaker 2: Yeah, it refracts it.

00:01:33 Speaker 1: Exactly. The digital prism splits your real world complex human identity into these different digital archetypes across the web. So your social media profiles, your professional bios, uh, your published content and your legacy code is essentially the accumulated digital worth of all those refracted pieces. It's the footprint of your authority. And Project anteriorly is the overarching mission to preserve and optimize that code.

00:01:59 Speaker 2: Precisely. And what we are looking at today is a fascinating and frankly incredibly frustrating bottleneck between rigid legal systems and your fluid digital identity. Yeah, it's a dynamic brought to light by a recent chat with Little Bird. And, you know, we have to talk directly to you, the listener, right now because you are currently living this nightmare.

00:02:21 Speaker 1: You really are.

00:02:22 Speaker 2: You have a massive digital footprint. You've spent years building it. But right now, you're being completely locked out of the new gold standard of authority scoring this platform called Terra Stable.

00:02:33 Speaker 1: Yeah. And it's wild.

00:02:34 Speaker 2: And you're being locked out simply because you're searchable, well-known brand does not perfectly match your government ID.

00:02:41 Speaker 1: It must be just so incredibly frustrating for you to realize that like ten years of late nights, podcast recordings, community building, all of it is being gated by an automated identity check. Oh, totally. Let's unpack this persona bottleneck. We have this massive clash between your legal identity and the digital prism. Like the internet knows you. It knows the legacy you have built under the name Myrtti b VNS.

00:03:01 Speaker 2: All right, that's the brand.

00:03:02 Speaker 1: Exactly. That is your brand. That is how your audience finds you. But LinkedIn has rolled out this new, incredibly rigid identity verification system they call persona and persona forces a hard match with your government issued ID. So according to their bureaucracy, you must be VNS Murthy Baku.

00:03:23 Speaker 2: And they are enforcing this globally. Like it is literally overriding the professional brand you spent a decade curating.

00:03:29 Speaker 1: It's wild to me, going back to my earlier point, this is like a passport control officer refusing to let you board a flight to a city that you personally built. Yeah. Why is a tech platform prioritizing a scanned piece of plastic over a decade of verified, publicly available digital legacy?

00:03:47 Speaker 2: I mean, I hear your frustration, but put yourself in the developer's shoes for a second. Okay, fair. If we look at the mechanics of the modern internet, it basically comes down to systemic panic. Platforms are absolutely drowning in fake accounts, uh, AI generated profiles, automated bots that can mimic human behavior perfectly now, right? Right. So if they don't implement a strict, undeniable gatekeeper, the entire trust economy of their platform just collapses. So they're abruptly shifting to a legal first verification model. It's, um, it's a necessary evil from an engineering standpoint.

00:04:21 Speaker 1: I see what you're saying. I really do, but it is such a blunt instrument to solve a complex problem.

00:04:26 Speaker 2: Oh for sure.

00:04:27 Speaker 1: For a legacy builder, someone whose entire digital ecosystem relies on a specific, searchable moniker, this is disastrous. It basically forces a rebrand against your will, wiping out your search engine optimization, and just totally confusing your audience.

00:04:42 Speaker 2: It is absolute collateral damage. I completely agree with you there. And I mean, it's exactly why you got fed up and left LinkedIn entirely. Yeah. You tried to work with their support multiple times, trying to get access, trying to explain that Marty Bass is who you are professionally, but, you know, hitting that bureaucratic wall over and over, you just walked away. And honestly, no one can blame you for that.

00:05:01 Speaker 1: No. Absolutely not. But let's look at the flip side, which is, you know, why we are conducting this Gurukul session today. Walking away from LinkedIn might feel like a personal victory, but mechanically it cuts you off from the rest of the internet. Like ten years ago. Deleting a social media profile just meant you weren't on that site anymore, right? Today, LinkedIn functions as the foundational identity layer for professional tools. It acts as the universal login, the, uh, oath or single sign on for just countless third party platforms.

00:05:34 Speaker 2: Which is the perfect transition to the core problem with the tree stable score. Because LinkedIn is the single sign on gatekeeper to tree stable, we have to look at why we even care about tree stable in the first place.

00:05:44 Speaker 1: Exactly.

00:05:45 Speaker 2: If the gate is locked, why not just ignore the building entirely?

00:05:48 Speaker 1: Because the entire philosophy of measuring digital worth has migrated, and we need to understand the mechanics of that shift. We just aren't in the same era of the internet anymore.

00:05:58 Speaker 2: No, we really aren't.

00:05:59 Speaker 1: Let's look at the old metrics you used to publish to understand this evolution. Like long ago, you used to share your credit score. KRD was all about influence. It counted how many followers you had, your retweets, your mentions.

00:06:13 Speaker 2: Yeah, KR was basically a measure of volume. To use an analogy, KRD was like measuring who has the loudest megaphone in a crowded room, right? If you were shouting loud enough and enough people looked your way, your score went up. Yeah. But um, volume doesn't equal value.

00:06:28 Speaker 1: Exactly. And that is a brilliant way to visualize it. Check stable, on the other hand, is like measuring how many people actually stop what they are doing, pull out a pen and take notes when you speak.

00:06:38 Speaker 2: I love.

00:06:39 Speaker 1: That. Founded by Geetika Sahgal, who is also the CEO of Bija House. Try Stable measures professional authority. It doesn't ask how many people listen to you. It asks why should they believe you?

00:06:50 Speaker 2: Right. It's an evidence based authority score. It doesn't rely on self-reported credentials or vanity metrics. And what's fascinating here is how it actually works mechanically under the hood, it doesn't need your passwords. It doesn't store your private data. It uses machine learning to pull Third party verified evidence directly from a public profile to calculate a score out of one hundred, and it weights that score based on your specific professional context, not just some, you know, one size fits all industry benchmark.

00:07:18 Speaker 1: Let's break down those mechanics because I don't want to just list things off charts, table analyses, public data across five distinct pillars of your legacy code. Let's look at how it measures these. Okay, first is positioning. This isn't just about what your bio says. The algorithm uses natural language processing to analyze the semantic clarity of your profile. It's looking for a highly focused professional identity.

00:07:40 Speaker 2: Mhm. And the second is credibility. The machine isn't just taking your word that you are an expert. It scans for verified history. So things like legitimate backlinks, institutional associations, concrete social proof that validates your background, right.

00:07:55 Speaker 1: Then third is IP or intellectual property. This is where original content comes in. The algorithm loves owned assets.

00:08:01 Speaker 2: Yeah it does.

00:08:02 Speaker 1: It checks to see if you are just retweeting other people's thoughts or if you are publishing original frameworks, articles or podcasts. And then fourth is visibility, which is essentially search index ability. Like how easily can a target audience find you based on keyword queries?

00:08:17 Speaker 2: And finally, impact. This is arguably the hardest for a machine to measure, but it does it by looking past vanity likes. Right? It uses sentiment analysis on the comments you receive. So are people just leaving fire emojis or are they having deep, actionable conversations based on the value you provided? It measures the real world ripple effect of your digital presence.

00:08:40 Speaker 1: Okay. Hold on, hold on. Let me make sure I understand the system design here because I have a major issue with it. If char Stable is so incredibly smart, utilizing natural language processing and sentiment analysis to build this nuanced, evidence based profile, isn't it a massive structural flaw that its entire architecture is hardwired to a single point of failure? Yes. Like it completely relies on LinkedIn's login for identity verification.

00:09:04 Speaker 2: You are bringing up the ultimate paradox of modern digital architecture. Yes, it's a massive flaw.

00:09:11 Speaker 1: Okay. Glad I'm not the only one seeing this.

00:09:13 Speaker 2: Not at all. This rigid dependency on LinkedIn's login is exactly what traps genuine creators in the system's blind spots. True stable is designed to measure what the internet actually says about you, but it uses a gatekeeper that forces you to match a government ID.

00:09:30 Speaker 3: It's absurd.

00:09:31 Speaker 2: It is so trustable. Can't even see the real you because LinkedIn won't let you through the door as myrtti bvn s.

00:09:39 Speaker 1: It is a complete bureaucratic nightmare. So we know these new pillars of authority are out there, but since the LinkedIn gate is currently locked for you, how do we know where you stand? We have to look at historical data to see how your digital prism currently refracts these five pillars.

00:09:52 Speaker 2: And that's exactly what Little Bird did. They dug into the archives to find a benchmark, because the automated tool is currently blocked by the persona bottleneck. They looked at a historical analysis from May six, twenty twenty six. A similar authority audit was run, but this time on your Facebook profile at Murti Virtual.

00:10:11 Speaker 1: And the overall score was a sixty one out of one hundred. Now, on the surface, a sixty one might sound average, but when we break down the mechanics of that score, it tells a very specific story about how algorithms misinterpret human complexity.

00:10:25 Speaker 2: It really does. It shows massive strengths in certain pillars, but a glaring mechanical gap in another. Let's start with the strengths. Okay. Your credibility pillar is incredibly strong. You have over six thousand three hundred followers, a real professional headshot, and a deeply documented history that provides solid social proof. The machine easily verified that you are a real person with a real audience.

00:10:50 Speaker 1: And your IP pillar. Intellectual property is also a major asset.

00:10:54 Speaker 2: Huge asset.

00:10:55 Speaker 1: The Morning Walk with Murti podcast is exactly the kind of owned original content that authority algorithms heavily weight in your favor. Plus, your visibility is exceptionally high because the name Murti ness is just highly indexable on Google.

00:11:08 Speaker 2: Exactly. The internet has a lot of positive things to say about RDBMS.

00:11:11 Speaker 1: Oh wait, I have to jump in here to highlight the contradiction.

00:11:14 Speaker 2: Yeah.

00:11:14 Speaker 1: Go ahead. If the intellectual property is that strong with the podcast and the visibility is super high because the name is so googleable and the credibility is backed by thousands of followers, why in the world is the score only a sixty one? Ah, yeah. What is dragging the average down so heavily?

00:11:31 Speaker 2: It all comes down to the mechanics of the first pillar positioning. And this is where we really need to talk about how machine learning clustering works. Or well in this case fails. Okay. The algorithm got confused by the mixing of your archetypes. The historical report noted that your bio simultaneously promoted bioresonance healing yoga, digital marketing, and publishing.

00:11:53 Speaker 1: Ah, I see, so you have a healer archetype clashing with a strategist archetype.

00:11:57 Speaker 2: Exactly.

00:11:58 Speaker 1: To a human being. Reading that bio, you are a polymath. You have these diverse, interconnected interests that make you a totally unique mentor. But a machine doesn't understand polymaths.

00:12:08 Speaker 2: No, not at all. When an algorithm uses semantic clustering, it plots your keywords on a multidimensional graph. It is looking for a dense cluster of related terms to assign you a clear hierarchical professional category. Right? So when it sees bioresonance healing and yoga right next to digital marketing, it can't form a tight cluster. The data points are just too far apart on its semantic graph.

00:12:31 Speaker 1: That makes total sense.

00:12:32 Speaker 2: Right to the machine. You don't look like a multi-talented mentor. You look unfocused and scattered. It creates this massive positioning gap that drags your entire average down.

00:12:43 Speaker 1: That is incredibly revealing. It shows how the tool is punishing you, not for a lack of authority, but basically for failing to fit into a neat algorithmic box. So what does that mean for your actual potential?

00:12:55 Speaker 2: Well, the historical report noted that with precise niche clarity, like if you simply focus the bio on one primary professional identity to satisfy that clustering algorithm, your score has a ceiling that could easily jump into the eighty to eighty five out of one hundred range.

00:13:10 Speaker 1: Wow. Okay, that is a massive jump. So we know your potential score is comfortably sitting in the eighties. The authority is there.

00:13:17 Speaker 2: It's undeniably there, right?

00:13:19 Speaker 1: The evidence is undeniably there. The only thing standing in the way is the LinkedIn bottleneck forcing a name mismatch. So how do we bypass it? How do we make Chessable finally see the real you?

00:13:31 Speaker 2: This is where we move from theory into actual digital migration strategy. We have a tactical workaround to hack the system, and Littlebird has outlined the exact steps.

00:13:39 Speaker 1: Okay, let's lay out the action plan for you. It turns out LinkedIn finally bowed to user frustration. They realized that professional identities don't always perfectly match government IDs, especially globally. So they introduced an additional name feature within their settings.

00:13:55 Speaker 2: And this feature is the key to picking the lock. According to LinkedIn's own Help Center documentation, you can go to your profile intro and utilize the Add Former name or additional name data fields.

00:14:07 Speaker 1: So mechanically, what this allows you to do is verify your legal identity via an S Murderbot you using your government document to satisfy the automated persona? Check behind the scenes. Right? But, and this is the crucial part, you get to keep your searchable, established legacy. Murty b v n s as your primary display name.

00:14:24 Speaker 2: Exactly. You feed the bureaucracy, the strict legal parameters it demands to keep the bots out while simultaneously keeping your true professional brand front and center for the world and more importantly, for the trustable algorithm to index.

00:14:38 Speaker 1: And you have a very specific mission planned for today to execute this work around the tactical execution is happening right from your office. You plan to attempt this digital migration today, specifically utilizing your HP mini elite.

00:14:52 Speaker 2: That is a very smart move. Using the HP Mini Elite ensures a highly stable connection and hardware environment while you navigate these verification hurdles.

00:15:00 Speaker 1: Yeah, you definitely don't want a mobile browser timing out while you are uploading government documents.

00:15:05 Speaker 2: Oh absolutely not. That's how accounts get flagged.

00:15:08 Speaker 3: It's a solid practical plan.

00:15:09 Speaker 1: Get into a stable environment, handle the verification and finally unlock the gate to your legacy code. But I mean, knowing how these massive tech platforms operate, things don't always go smoothly.

00:15:21 Speaker 2: No they don't.

00:15:22 Speaker 1: What happens if the machine still says no? What if the system glitches and tries to force a permanent name change that you just don't want?

00:15:29 Speaker 2: That is where the guru Cool two point zero philosophy comes into play. We never rely on just one automated system, right? We always need a human backup plan. If the automated workaround fails, we bypass the automation entirely. You are a recognized digital migration strategist. Your work with Project Antirrhinum is substantial and it's well documented. So the next move is to go directly to the source and demand human intervention.

00:15:55 Speaker 1: You mean contacting through stable support or even reaching out to people directly?

00:16:00 Speaker 2: Exactly. Think about the core mission of her platform. Treat a stable is dedicated to helping experts become recognized authorities, helping them become published authors and validating their real world impact. Yeah, the Gurukul method of mentorship you practice is exactly the kind of deep evidence based authority or platform values. If LinkedIn's automated gate won't open, Littlebird is standing by to draft a formal letter outlining your status as a digital migration strategist. You simply request a manual authority report.

00:16:28 Speaker 1: I love that approach. You bypass the API integration entirely. You ask them to calculate your score based on your massive Google footprint, rather than relying strictly on the rigid LinkedIn profile API. Because again, try stable claims to measure what the internet says about you and the internet says a whole lot more about Marty Bass than it does about the legally verified VNS Marty bought you.

00:16:50 Speaker 2: It's about ensuring the tool serves the reality of the creator, rather than forcing the creator to bend to the limitations of the tool.

00:16:58 Speaker 3: Beautifully said.

00:16:59 Speaker 2: If the algorithm can't see the polymath, you bring in a human who can.

00:17:03 Speaker 1: This has been a deeply insightful guru. Cool session to wrap up our digital stroll today. The core message here is that your legacy is built on a brand, not a birth certificate, right? The philosophical shift from the old creed megaphone metrics to the new try stable note taking standards proves that evidence of your actual impact matters far more than just vanity metrics.

00:17:23 Speaker 2: But you know, our session today into the mechanics of this bottleneck also proves that the delivery systems, the platform gatekeepers, are still clumsily catching up to the reality of the digital prism.

00:17:34 Speaker 1: Oh, absolutely.

00:17:35 Speaker 2: They are still learning how to handle complex legacy builders whose identities transcend simple legal documents.

00:17:41 Speaker 1: So true. You are more than a clustered set of keywords, and you are certainly more than a name on a passport.

00:17:48 Speaker 2: I'll leave you with a final thought to ponder on your next physical stroll. We've mapped out how to hack the system for yourself today, and hopefully that HP Mini Elite gets you through the bottleneck.

00:17:59 Speaker 1: Fingers crossed.

00:18:00 Speaker 2: But look ahead at the broader landscape as automated platforms increasingly demand strict legal verification just to function. How will the next generation of digital mentors build and protect their legacy code, if their real world impact doesn't match the name printed on their government ID?