Vinodhini (Vini/Vino) Ravikumar

🎙️ 𝐃𝐢𝐚𝐥𝐨𝐠𝐮𝐞 #1 : 𝐓𝐡𝐞 𝐉𝐨𝐮𝐫𝐧𝐞𝐲 𝐁𝐞𝐠𝐢𝐧𝐬 The following is my conversation with Keshan Kathiripilay, a Software Engineering Student at Concordia University. In this one, Keshan opens up about the profound influence of his parents on his journey. He shares how their sacrifices and work ethic have instilled in him a deep sense of gratitude and determination. 𝑲𝒆𝒚 𝒕𝒂𝒌𝒆𝒂𝒘𝒂𝒚𝒔 𝒇𝒓𝒐𝒎 𝒐𝒖𝒓 𝒅𝒊𝒔𝒄𝒖𝒔𝒔𝒊𝒐𝒏 𝒊𝒏𝒄𝒍𝒖𝒅𝒆: 📌 Exploring different career paths is essential. 📌 Mentorship provides invaluable guidance and support. 📌 Resilience is key to overcoming challenges. 📌 Internships are competitive; persistence is crucial. 📌 A positive mindset helps navigate difficult situations. 📌 Asking questions is vital for growth and learning. 👉🏽 Join this dialogue on YouTube: https://bit.ly/47DEhFI and share your thoughts! #SoftwareEngineering #Internships #Mentorship #OloodiDialogues

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Had the chance to speak on stage and share what we are building which I discuss in the video below. Here in #Toronto talking about Niftmint and our thought leadership on #tokenization, #authentication, and #rewards.

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Today, I encountered a disheartening situation involving four of my friends who received contract job offers as “Data Analysts” from leading banks and insurance companies. Shockingly, the offered hourly rates were $19, $20, $20 and $21. These contracts are from Canada’s Top 10 prominent agencies. These wages are lower than what many earn in survival jobs, such as those in restaurants or warehouses. My intuition suggests that big companies like banks and insurance companies themselves likely offer better pay. Could it be that the agencies are taking a higher margin, or are the big companies genuinely offering such low rates? I would appreciate your insights on this matter. Let's brainstorm.

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At Carta, I've had the opportunity to mentor many sharp and hungry engineering co-ops that come from the University of Waterloo. I've found that the integration of externships into the school's curriculum has led to well-rounded, technologically agile, and effective software engineers. One document that I think that every new grad and intern should study is the Future Ready Talent Framework. This framework really does set a lot of coops forward in terms of their skills relative to the rest of the market. Check it out!

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Transitioning to a new role at Shopify has been a journey filled with both excitement and challenges. Here are a few key learnings from my experience so far. Prioritizing Information: One of the biggest challenges has been sifting through the vast amount of information available. With so much happening across the organization and an abundance of content to absorb, distinguishing between what's actionable and what's just for context is crucial. I've learned the importance of seeking early guidance from my team to help prioritize effectively. This approach has been invaluable in focusing on what truly matters and ensuring my contributions have the most impact. It's about striking a balance between being informed and overwhelmed, and I've found that open communication with colleagues has been key to navigating this. By actively engaging in discussions and leveraging the expertise of those around me, I've been able to streamline my focus and direct my efforts where they are needed most. Embracing Change and Adaptability: This is a dynamic environment where some applications and processes have been around for ages, while others may have been introduced just the month before I started. Some systems endure because they work exceptionally well, while others might be in desperate need of a rewrite, refactor, or replacement. This mix of tradition and innovation requires a willingness to ask more questions than anyone else in the room. It's about understanding the rationale behind existing systems and being game to exploring new approaches. Through all of this, I am realizing that change, while daunting, offers a chance for growth and reinvention. I was ready for a new challenge, and I got exactly what I was looking for. The supportive and collaborative spirit of the team has made this transition not only possible but rewarding. I'm lucky to be a part of this team, where the shared commitment to Shopify's mission makes it very clear we are all rowing together in the same direction. #Shopify #SoftwareEngineering #NewBeginnings #GrowthMindset

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🎙️ 𝐃𝐢𝐚𝐥𝐨𝐠𝐮𝐞 #2: 𝐃𝐢𝐯𝐞𝐫𝐬𝐢𝐭𝐲 𝐢𝐧 𝐓𝐞𝐜𝐡 – 𝐉𝐨𝐮𝐫𝐧𝐞𝐲 𝐨𝐟 𝐄𝐦𝐩𝐨𝐰𝐞𝐫𝐦𝐞𝐧𝐭 𝐚𝐧𝐝 𝐁𝐫𝐞𝐚𝐤𝐢𝐧𝐠 𝐁𝐚𝐫𝐫𝐢𝐞𝐫𝐬. The following is my conversation with Hanine Tydrini, a Software Engineering Student at Concordia University. As a Google DSC Lead at Concordia and Women Techmakers advocate, Hanine shares her experiences navigating the tech industry as a woman from a diverse background. She discusses the unique challenges she faces, the strategies she employs to overcome them, and the importance of mentorship and networking. 𝑲𝒆𝒚 𝒕𝒂𝒌𝒆𝒂𝒘𝒂𝒚𝒔 𝒇𝒓𝒐𝒎 𝒐𝒖𝒓 𝒅𝒊𝒔𝒄𝒖𝒔𝒔𝒊𝒐𝒏 𝒊𝒏𝒄𝒍𝒖𝒅𝒆: 📌 The importance of having a supportive family environment. 📌 Diversity and inclusion are crucial for a thriving tech industry. 📌 Networking and mentorship can significantly impact career development. 📌 Confidence is key to overcoming feelings of being an outsider. 👉🏽 Join this dialogue on YouTube: https://bit.ly/3Y3r04X and share your thoughts! #SoftwareEngineering #Mentorship #WomenInTech #DiversityInTech

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Two facts: First: Jack and the Storefront team handle some of the most interesting problems at Recharge if you're into caching, synchronizing, and lots of data puzzles to solve. Second: I work with the team as Principal so we'd get to have some fun while we do the first part.

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Early in my career I worked for a company whose business model (in retrospect) was selling a dollar for 99 cents. The problem with these types of businesses is that they have infinite scale, but can never be profitable. Recognizing a business operating in this mode can be easy (MoviePass, Jokr) or tough (Uber certainly looked like it would never turn a profit). Which category does OpenAI fall into? My guess is the former. They have a wildly expensive product with no reasonable timeline to making that profitable. They're burning billions of dollars while receiving substantial subsidies from Microsoft for model training and execution and their product, while cool, is running on borrowed time. At the end of the day, how many of their subscribers would stick around if they were forced to pay the fully-loaded cost of using ChatGPT? The egress of top-tier talent along with the eagerness with which businesses whose own valuations are deeply tied to OpenAI (Microsoft, Nvidia) are ready to pour money into this funding round, IMO, is indicative of OpenAI's relatively dire position. Even if OpenAI ultimately fails, it doesn't mean that generative AI is dead. Far from it -- there is clearly value in the technology just nobody has either unlocked the absolutely killer use case or figured out how to bring the costs down far enough to make the current offering compelling in the long-term.

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Google has managed to build an impressive $175 billion revenue stream through its Search business and has stayed ahead of the competition, undefeated for the last 20 years. I have spent a considerable amount of time reading their engineering blogs in the past and firmly believe that Google Search deserves recognition for its engineering excellence and as one of the most successful businesses of our time. However, part of the reason Google has maintained a monopoly in the Search business is that it has been paying off partners to discourage competition in this space. This week, a Washington court ruled that Google has been operating as an illegal monopoly in the Search business, which is not entirely false. Google’s competitors may not match its level, but they were never given a fair chance to participate in the race. Google allocates over 30% of its revenue to partners to remain the default search engine on their platforms (Apple’s Safari, Mozilla Firefox, etc.). For instance, Microsoft Bing could never afford to pay the hefty fees to Apple to be their default browser because it doesn’t generate the same revenue as Google Search. Google may win this case in higher courts, but I hope Google loses this monopoly suit forever. This would open the floodgates of competition in the search business, especially giving AI search engines a chance to reach the masses. In the 1990s, Microsoft was seen as a villain by many budding internet startups because it was on a spree to eliminate almost all competitors in the internet/browser business landscape (one such victim being Netscape). The antitrust law then put an end to Microsoft’s aggression as a monopoly and opened the door for fair competition, which led to an explosion of innovation with Firefox (good old memories) and Chrome extensions. Internet Explorer could have still kept us confined. Google Search is undoubtedly one of the most brilliant creations of the last 20 years. But enforcing fair competition is the only way to foster a healthy innovation ecosystem. In Pic: 2023-Google Revenue Breakdown, search business making the 57% of the total..!

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In Montreal, a taxi has a base rate of $4.10, then $2.05/km and $0.77 per minute waiting. I hate to break it to the CBC but that's also an algorithm. Any pricing scheme is going to be better for some and worse for others. And like with almost all AI, transparency or explainability is an illusion. Is it better to know how your taxi fare is calculated, as above, but have no idea how much the trip will cost, or to know how much the trip will cost but have no idea how it's calculated? It's not about the underlying technology, or what constitutes an algorithm, it's the impact that matters. It would be a very cool study to look at who benefits from one-size-fits-all time and distance pricing, vs. who benefits from customized pricing. It's not a slam dunk that the latter is worse. https://lnkd.in/gvjiPKnZ

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When I was a senior engineer on the Uber Eats team, I once caused an outage that resulted in $20k worth of UberEats orders getting stuck and unfulfilled (and lived to tell the story) 👇 If you placed an order sometime in 2018 and your order got stuck, I apologize, it might have been me. The outage followed the regular incident response protocols implemented at Uber, so I found myself in our outages Zoom with multiple critical teams trying to undo my error. Fortunately, Uber’s incident command is completely blameless so nobody at any point in time said “Irina did this stupid thing” or “Irina messed up”. Also, I didn’t get fired. But inside, I was dying of shame. I was a senior, I should’ve known better. For the volume of orders that UberEats did at the time, the incident I created was a scope low, but it was still an L5 (highest level), as it was impacting critical flows. I remember one of my more senior teammates consoling me, saying how it’s okay, he caused an L5 high at one point. I was the one who messed up and I was being consoled. You probably wonder what my mistake was: a combination of being on the team for only a few months, lacking context, assuming some pre-existing tests would catch if I did something wrong combined with a rubber stamp from someone else on a bad PR. The lessons from this story are: ➡️ 𝗔𝗹𝘄𝗮𝘆𝘀 𝘃𝗮𝗹𝗶𝗱𝗮𝘁𝗲 𝗮𝘀𝘀𝘂𝗺𝗽𝘁𝗶𝗼𝗻𝘀. In my case, the mistake I made was making assumptions I didn't validate. For things you think you know, ask yourself: how do I know this is true? ➡️ 𝗗𝗼𝗻'𝘁 𝘀𝗸𝗶𝗽 𝘀𝘁𝗲𝗽𝘀 𝗳𝗼𝗿 𝘁𝗵𝗲 𝘀𝗮𝗸𝗲 𝗼𝗳 𝗺𝗼𝘃𝗶𝗻𝗴 𝗳𝗮𝘀𝘁. My desire to move fast blindsided me, but it taught me important lessons. For your customers' sake, never skip steps, and ensure you always do rigorous testing. ➡️ 𝗠𝗶𝘀𝘁𝗮𝗸𝗲𝘀 𝘄𝗶𝗹𝗹 𝗵𝗮𝗽𝗽𝗲𝗻, 𝗯𝗲 𝗸𝗶𝗻𝗱 𝘁𝗼 𝘆𝗼𝘂𝗿𝘀𝗲𝗹𝗳. Learn from your mistakes and move on! There is no point in dwelling on your mistakes. You don’t need to commit seppuku! - - - - - - - - - - - - - - - - - - - - - - - - ♻️ Please repost if you found this useful 🤝 I help engineers and leaders grow in their high-pressure tech careers, DM “CONNECT” to learn more

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Yesterday, I had the chance to attend a presentation on Apple Intelligence at Apple Montreal’s office. First of, thanks to Apple for hosting such a nice event. It was a good recap of what’s to come. While I don’t think it showcased anything beyond what was already covered in the WWDC24 videos, it gave everyone the opportunity to dive deeper into Apple Intelligence, which promises to be the biggest leap forward for the Apple ecosystem in years. Here are my main takeaways: - Find app-specific content from anywhere on your device: The potential here is immense. With new capabilities to index app content through AppIntents, Siri and Spotlight can now find app-specific content during a generic search on the device. For instance, we could make specific products or categories easily accessible through a Spotlight search or Siri query. While there may be limitations on the amount of data we can index on the device, this is still a very promising feature. - Siri awareness of on-screen content: Siri will now understand the context of what’s displayed on screen. Combined with the ability to make our app-specific content transferable (Apple’s method for serializing content to popular formats such as PDF, image, or text), this opens up possibilities for app content to interact with other apps through Siri. Although initially limited to a few domains like photos and emails, the potential is exciting! - Easier than ever to deploy on-device AI models: To power Apple Intelligence, Apple has optimized its hardware for on-device AI operations. They are also simplifying the deployment of machine-learning models for tasks related to vision, speech recognition, natural language processing, and sound recognition. Tools such as Create ML make it straightforward to train models with our own datasets. Additionally, we can still import existing models to Core ML from popular sources like Hugging Face or those built with TensorFlow or PyTorch. As I mentioned in my previous post about WWDC24, I’m excited both as a builder and as a user. Let’s build!

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"The challenge lies in setting aside your ego and prioritizing the outcome over being right. Growth involves a personal struggle, and this aspect is particularly tough because we naturally desire to be right and protect ourselves, a tendency that has often served us well." For more insights, you can listen to the episode https://lnkd.in/dph2hxFA

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Did you know there are no "roles" (SDE, SDET, TPM, …) when you get to L8 IC (Senior Principal) at Amazon? It’s one of Amazon’s peculiarities. [Side note: in general, Amazon SDEs tend to be "jack of all trades" where we pragmatically do whatever is necessary to make our organization successful at that given moment (within reason). In fact, I believe being well-rounded and able and willing to wear a number of hats is one of the things that makes me valuable to an employer. We don’t over-index on "that’s not part of my role doc." Other companies where I worked (eg Google) have very clear swimming lanes and people stick to them pretty religiously, eg. "oh no I don’t talk to customers, I’m an SDE and talking to customers is for TPMs." Whereas at Amazon I never once had a manager tell me, "what you did (although impactful, important and necessary) was not really your job." ] My little side note about this critical piece of amazon culture explains why as you get to L8 the concept of a "role" no longer really makes sense. The boundaries between roles get fuzzier and fuzzier as you go from Senior Engineer (L6) to Principal Engineer (L7), and they become unimportant when you get to L8. We’re all just “Senior Principals” - whether you came via the SDE path, the TPM path, or in my snowflake case, the SDET path. In fact I think most L8s are snowflakes in that their path to L8 was unique and the value they bring to the company is also unique. In phonetool (our amazon directory) you can have whatever unofficial title you want (also within reason...), so I chose to keep the "SDET" title to reflect my background and passion for testing, engineering and operational excellence, and developer tools. I also hope that by keeping the title, others in my (old?) role can see that SDETs at Amazon do not have a "ceiling" in their career. And lastly, it's a fun conversational piece ("you're an L8 SDET???") (The image here is "Peccy" - a beloved little icon that has represented Amazon's Peculiar Ways for years) [Edit: Strictly speaking there are a few L8 IC roles that do have a different job code, like PMT or Scientist - but I think we generally view all L8 ICs in the same lens]

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Ah...the joys and pain of working with distributed systems/microservices. I am sure this parody will ring close to reality in many settings for software engineers all around :-) To my Product Managers and non-technical stakeholder friends, this is a must-watch as no amount of storytelling can help shine light on the complexity and implications of a microservices architecture, leading to unrealistic expectations or a lack of appreciation for the associated overhead in software development.

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Every time I see Plaid as an option I expect it to be great and take me through an oauth flow and make things work seamlessly, and every time it asks me to input my credentials on its website & I bail and go back to the awkwardness of getting my bank info. In 2024 how is it viable a 3rd party business literally asks you to give them your sensitive financial credentials and people do it?

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Revolutionizing Customer Support with AI and LLMs at Shopify! The landscape of customer support is undergoing a remarkable transformation, thanks to the power of Artificial Intelligence (AI) and Large Language Models (LLMs). Here’s how my team is changing the game at Shopify: We harness the power of LLMs to empower merchants to find answers independently via our AI chatbot on the Help Center. When merchants require expert advice, our support advisors are equipped with a powerful co-pilot that instantly provides all relevant merchant information and potential solutions, reducing effort and speeding up issue resolution. This allows merchants to focus on what they do best: running their business, not spending time on customer support. Here are some high-level considerations that support organizations should be thinking about as they look to incorporating AI/LLMs into their solutions: 24/7 Availability: AI-driven chatbots and virtual assistants ensure that customers receive support anytime, anywhere. This round-the-clock availability enhances customer satisfaction and loyalty. Instant Responses: With AI and LLMs, responses are instantaneous and accurate. Customers no longer have to wait in long queues, resulting in a smoother and more efficient support experience. Personalized Interactions: AI systems can analyze customer data to provide personalized recommendations and solutions. This level of customization makes customers feel valued and understood. Efficient Issue Resolution: LLMs can understand and interpret complex queries, directing customers to the right resources or human agents. This reduces resolution times and improves overall efficiency. Continuous Learning: AI systems are constantly learning from interactions. This continuous improvement means that customer support becomes more refined and effective over time. Scalability: AI and LLMs allow businesses to scale their support operations effortlessly. Whether handling peak times or expanding into new markets, these technologies provide the flexibility needed to grow. Multilingual Support: AI and LLMs can translate and communicate in multiple languages, breaking down language barriers and providing seamless support to customers worldwide. This inclusivity broadens the reach and enhances the user experience on a global scale. Lean Operations: AI-powered support enables organizations to run leaner, more efficient operations. By reducing the need for large support teams and streamlining processes, businesses can achieve more with less, improving both efficiency and profitability. Excited to see how AI and LLMs continue to evolve and revolutionize the customer support space! 🚀🌐 #AI #LLM #CustomerSupport #TechInnovation #CustomerExperience #FutureOfWork #Shopify

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The job market in 2024 has been like navigating a storm—one that’s not following usual patterns. Despite a "good" economic environment (the stock market booming, companies making record profits) - hiring seems to be scarce, and the average job search is stretching to nearly 14 months. What’s causing this bizarre situation? 🌐 Legacy Things Crashing and Burning Legacy bits are finally reaching the end of their lifespans. Many companies have delayed upgrading for decades, but now have no choice (because things either have stopped working or upgrading {with "AI"} is the only way to prevent competition from crushing them). Higher interest rates mean money put into these necessary capital expenditures has to come at the expense of operational expansion. Instead of hiring new talent, companies are restructuring and laying off staff, further burdening already skeletal crews (all the while keeping job posts they aren't going to fill open). ⚔️ Too Many Seekers, Too Few Roles Too many job seekers are now fighting for too few non-ghost roles. Layoffs and restructuring have increased the number of qualified professionals hunting for jobs at the same time. With fewer companies expanding, the imbalance between job seekers and openings is at an all-time high, making competition fiercer than ever (even with 4x the number of job postings to job seekers). Not to mention the AI-Resume-ATS battles raging on in the recruiting world. 🧱 People Aren't Leaving Their Jobs People aren’t leaving their current roles as frequently as they did in the past. Job hopping has slowed significantly, whether due to economic uncertainty, job security, or fear of not finding another role (due to current job market conditions). This stagnation means fewer positions are opening up, bottlenecking the job market. 🌄 The Silver Lining: Relief Is Coming It’s not all doom and gloom—there’s a silver lining on the horizon. Once the Federal Reserve reduces interest rates, capital will be available for companies to start hiring again. The current strain on the bare-bone-marrow workforce has led to increased burnout. Without support, employees will start leaving (even if the market is bad), opening up more vacancies. Over the next few months, we can expect the number of open positions to increase as companies hire again (because they have money or to prevent more people leaving) or as people leave their jobs, creating more opportunities - which will then spur others to leave their roles accelerating this process. 🌟 The Light at the End of the Tunnel As the market rebalances itself again, the number of job applications per role should drop, finding that next position will become easier. The storm will pass, and the job market will begin to normalize. Until then, hang tight; this imbalance is hopefully a phase—one that will eventually clear, making way for brighter days ahead. #Jobpocalypse2024 #OpenToWork

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#Layoffs and Misguided Corporate Spending ( A note to Leadership) I've spent over 16 years working across both MNCs (50%) and startups (50%). During my time at one of the world’s top 10 dream companies, I used to see an annual trend: layoffs. The pressure this puts on employees is immense. Here’s the ironic part: the same company ( Should I say some Big Heads) cutting jobs spends crores on unnecessary luxuries—like installing 90-inch LED TVs in lift lobbies, excessive property beautification, and lavish gifting. The amount spent on these could easily cover the salaries of hundreds of employees. When layoffs happen, it's often percentage cut—x% must go. But why aren’t senior leaders cutting these extravagant expenses in first place? I’m not suggesting cutting essential marketing costs and basic comfort costs for employees that drive business, but who’s choosing companies based on lift lobby TVs or expensive sofas in the pantry? We’ve all heard of a company that hired a famous footballer for an ad, only to later struggle to pay employees. It’s baffling that leaders allow these misguided financial priorities to persist. Why isn’t there a system in place to curb over-spending and protect employees—the true backbone of the company? Those four LED TVs won’t save the company. But four dedicated employees just might.

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