Kenley Lamaute

Three Articles From 2024 That Will Stick With Me in 2025 1. "I Will Piledrive You If You Mention AI Again" by Nikhil Suresh ⮑ https://lnkd.in/eC7q9ZWn 2. "Godot Isn’t Making It" by Ed Zitron ⮑ https://lnkd.in/e294rHXc 3. "Casual Viewing" by Will Tavlin for n+1 ⮑ https://lnkd.in/eRq_mZjh --- ⚠️ Before reading these, you may want to install Advanced Profanity Filter, a reputable, open source plug-in for your web browser that respects your privacy. - Download: https://lnkd.in/eCNMd3Y7 - GitHub > PRIVACY-dot-md - https://lnkd.in/e2frG_Ee And here's a pic of a new friend of mine so LinkedIn doesn't re-post a preview of the first URL.

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Totally agree with Dan DiGangi here. If you don't understand the overall strategy of a business, it's hard for you to align and be fully effective. This goes from leadership down to engineering. What are you doing to try and understand that vision? Link in comments to the full interview with Dan!

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Some things I have learned building a "side gig" investing business: 🎉 It's fun! Investing has always been a hobby of mine, and turning it into a service for others is very rewarding. Especially when it works. 😊 🤔 You have to _keep_ it fun. Many times I've been tempted to seek venture funding to turn it into a "startup" and grow it like crazy...but my brother Benjamin Lyman (who co-founded with me) keeps me in check in that regard. We build because it's fun, not because we "have to", which would be the case if we had venture capital investors stipulating sales and growth targets. 👬 It's very important to pick the right partner(s). Not all partnerships work out, that's a fact of life. Fortunately my brother and I work really well together and are good complements to each others' skills. 😩 Keep trying. This is probably the 20th LLC that I've created during my career and it's the only successful one. Like science, you don't stop after your first failed experiment. You keep trying and failing until you get it right, then build upon that. 🏦 Financial companies appear to lag about 10 years behind current technology. It has been _extremely_ difficult to find a stock broker that could support our use-case with API's. The biggest broker we talked to even told us their "API" is to upload a CSV file of trades via FTP for them to execute. 🤯 📈 Data is king. Of all of the investing strategies out there, the best one we've found (and that we use) is to let the data tell you what to do. No magic numbers, no assumptions, and no guessing. Just back-test and let the numbers speak for themselves. 🤖 Automation makes it somewhat "passive". We're using cloud-based server-less functions that run every morning automatically....and most of the time we just watch the updates roll in and don't have to do anything. We've made a lot of money for our clients while we were on vacations. 🏖 💲 Control your costs. We keep reducing and simplifying, removing services and software licenses we don't _actually_ need to provide value for our clients. We're managing over $3M AUM and our monthly cloud spend....is less than $2.00 🤣 📰 Marketing is tough, especially for engineers. We apparently understand computers, data, and processes much better than we understand other humans. Still trying to figure out how much to try and do ourselves vs. outsourcing to someone else. Still in progress... we'll have to let you know how it goes. So far not so well. 😅 What things have you learned from your successful (or failed) side-gigs? What tips or advice would you give us? Please let us know in the comments! 💬 And if you want to keep up on how we're doing, we post our stats at the bottom of our webpage at www.lymanwealth.com

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Have you reduced overhead by 99% on any meaningful back office task since the launch of AI? Well, why not? Apparently, Amazon has. The interesting thing about this new technology is that it shows the jobs most at risk are things like coding, where there is a clear, quantifiable feedback loop between action and result. But adoption is going to be the challenge. Honestly, a lot of small businesses don't even know how to do basic things like mail merge. Even my peers at large companies with better-than-average technical skills have barely used these AI tools. So far, I've reduced several back office tasks by 80% through the at least partial use of AI. It's amazing how powerful this technology can be.

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Project update! My application tracking extension is now doing fuzzier matching and injecting new information into LinkedIn (and other sites) to keep me from doubling up on applications. Next up: local storage and bulk import/export operations...

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Anthropic released another paper on their ongoing work towards interpretability of large foundational models like their Claude 3 family, built on previous work by many. Their work continues to be enlightening and inspiring. The findings in this work are generally similar to previous findings on smaller models but scaled up to Claude 3 Sonnet: 💡 they find large numbers of "features" corresponding to combinations of neuron activations and these features map to concepts that we recognize/understand: for example, features for transit infrastructure, particular people, concepts (like bias and "objects lacking sentience"). This might sound familiar from classical machine learning, but the interesting thing is that there is no single thing/neuron encoding each of these concepts, it's a particular combination of neuron activations that embeds these concepts in "superposition" in the network. 💡they observe a sort of "distance" of these feature activations that arrange themselves "near" semantically similar features. When they use their sparse autoencoder approach to learn more and more features they observe that the level of abstraction in the detected features becomes more granular, in ways that are interpretable and meaningful. 💡when they artificially fire these activation patterns during inference, it affects the output in ways that relate to the "feature". For example, asking Claude "what's the most interesting science" normally it responds Physics, but if you clamp the feature activations for the feature "Brain Science" to 10x their max values then Claude responds: Neuroscience. Ways to interpret _and_ influence the model. Great readable work [1] along with an interactive explorer of some of the "features" themselves [2] 🎂 There's an easter egg too: if you scroll in the feature explorer tool and try and select one of the "Randomly selected features from 1M" you get a message "if you want to see the rest of the features, we're hiring!" with a link to their recruiting page :) [1] https://lnkd.in/gZbparwp [2] https://lnkd.in/gC9eus53

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People are saying that AI users are becoming too dependent on AI. Which is a pretty dumb take so early on in the game. I recall people saying the same thing about search engines. Them: "Oh you looked it up on the internet?" Me: "Uhhh, you mean the largest compendium of information ever assembled by mankind. Yes." Programmers use this technique all the time actually, if you are familiar with rubber ducky debugging. Saying it out loud and clearly walking through the steps help you untangle problems pretty quickly, especially for early career developers. In my opinion, there is nothing wrong with it. Actually, in this case at least, this is a sign they are becoming less dependent on external information and actually learning from the systems. So long as the AI aren't teaching people incorrect things, then this is the exact reason WHY you should use it. For those of you who are not familiar with the crypto world, this same type of derisive backlash was/is prevalent. The leaders in the field f***ed it all up by overpromising, under delivering, and just being scammy in general. In the case of AI, I expected tech companies to do a better job handling the PR, but tech has gotten a lot of bad rep lately and the media pushed certain AI darlings over more reasonable voices in the community. So, none of the PR efforts to appropriately shape public perception worked. I think one of the biggest problems was that voices, like my commentary, that were highly critical of less than benign actors unintentionally drove a level of disdain for the industry. Then the artist and writer communities got salty, and they drove a huge wave of bad social media. To be fair, the AI/Tech companies screwed themselves with that. They pioneered the "you wouldn't steal a car" but I guess you can steal all of the internet. So, I'm not going to cry for them too much. What I'll say though is this, this kind of petty luddite snobbery isn't going to do anything for you. Maybe you like cheap likes on Twitter, so in a sense it makes you feel good about yourself. But AI is here to stay, it's been here before ChatGPT, it will continue to be here afterword. For those of you who have a long-term positive outlook of the technology, prepare to have a lot of low brow mockery like this. For those of you with unrealistically positive short-term views, I'd say LLMs are not going to be the change that brings about the vision in your head. Keep reading up on trends, technologies, watching content explaining AI and you will build a pretty good understanding of where we are heading. And for those that opted to get on the hate train instead of the hype train, I guess I don't have to spell out how hypocritical that is. But cool your jets, if there was one technology not to bet against in the long term, it would be AI.

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In case anyone wants the "low down" on what we're doing with LymanWealth. But I also want to add -- it's super fun! If you're looking for something more aggressive to add to your portfolio, you definitely should check us out. Note: not a full portfolio management or retirement strategy, should only be used with the portion designated for growth / high risk. May not be suitable for everyone. #investmentmanagement #wealthmanagement #automatedinvesting #automatedtrading #ria #etfs #investmentstrategy #stockmarket #stocks #indexinvesting #dca #dollarcostaveraging #alpha

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Its about solving the problem, not 'having AI' in the system. This is from last March, but the Wave 1 vs. Wave 2 distinction does seem to be playing out. Less 'generate me content', more 'synthesize vast amounts of relevant data and aid in decisonmaking or signal extraction'. https://lnkd.in/ehFBFC32 They don't talk about multi-agent systems here, but looking forward to more startups with a focus on leveraging agentic design patterns (https://lnkd.in/ed5rMmFe) to streamline real world workflows.

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First story on what we have been up to at Augment. Much more to come! https://lnkd.in/gC6gbADA

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Hey folks! Garrett Milster and I have only posted about Sacramento Labs once, so we figured it's time for an update 😊 **What is Sacramento Labs?** We’re a small team focused on launching software products that solve real-world problems. Think of us as a startup lab—constantly testing ideas, learning from feedback, and building tools that matter, and having an impact while doing it. **How do we decide what to build?** We like to build products that: -         Solve real-world problems in mostly ignored industries -         Are small, highly maintainable, and scalable codebases -         Make the world a better place directly, or by donating a percentage of profits to a relevant charity in that space You can learn more about our philosophy at sacramentolabs.com **What you can expect from us** We’ll be posting product ideas that are in various stages of our pipeline: Early Concept, Customer Development, In Progress, Launched, Scaling. We’d love to hear your feedback! **Our latest concept: Self-Hosted Security** Here’s the problem: - Businesses often use third-party URL shorteners to share internal tools, resources, or campaigns, but these services introduce serious risks. Enterprise companies like Google, Microsoft, and Stripe have built their own internal URL shorteners for this reason – but most businesses don’t have the resources to do that. - Phishing attacks are rampant, and links from external services can be spoofed or abused. - Branding and security controls are limited, leaving sensitive information exposed. - You can’t track link activity—who’s clicking what, when, or why. - When employees leave, their shared links still work, leaving potential vulnerabilities. Our proposed solution: Self-Hosted Security. It’s a plug-and-play solution for businesses to host their own branded URL shorteners with: - SSO for secure access tied to your company’s directory. - Link expirations to ensure old links don’t stay active indefinitely. - Audit logs to track activity and improve visibility into link usage. 📢 We need your input! Would this solve a problem for you? What features would make this indispensable? Check out the landing page and share your thoughts: selfhostedsecurity.com Want to chat? Email me at [email protected] 😊 💡 And here’s something we’re passionate about: a percentage of profits from Self-Hosted Security will go to the Electronic Frontier Foundation (EFF). Your feedback not only helps us create better solutions, but also contributes to making a positive impact. Thanks for being part of the journey!

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There is a surprising amount of complexity to choosing colors to represent data. Here are some of my favorite resources: https://lnkd.in/gg_YHqGV https://lnkd.in/g-priQZB

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Tech friends, don’t treat every “symptom” as a task list item, not all issues/needs/wants are acute. Build based on wholistic customer needs that further the mission statement, customer satisfaction and the profit line. You have a finite amount of time, energy, and runway.

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https://lnkd.in/gcJsEKrG Q. What happens when #neural #networks are applied to fields like #Physics? A. In short, a Nobel Prize. More broadly, neural networks, built on the laureates' foundational work, have wide-ranging applications across science, technology, and various industries. They excel at tasks like pattern recognition, classification, and data generation. #Physics #AI #HVSays

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A question for all of my friends in Software Engineering. Are there any reasonable alternatives to evaluate besides CircleCI that you'd recommend for running a very large set of Rails Unit and Integration tests automatically on Pull Requests? I'm aware of how we could spin up some things on AWS, but the goal is something low maintenance for a small team to increase the visibility of the tests.

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Drop a salary anchor! So I was messing around with Gemini, which like most LLMs is great for pulling together ideas and categorizing them, and ran into this item among a longer discussion of negotiation strategies: Make the first offer: This can set the anchor point for the negotiation. Base your offer on your research and be prepared to justify it with data or evidence. I've long thought that this is a strong key to my success in negotiations - I lead with my justified expectations - the recruiter is informed right up front what they are and why. As gemini points out "anchor point" - they had the opportunity to set an anchor point by advertising their rates - but they didn't, so, here is mine! By establishing this value point up front, they have to face the fact that they want to offer me less than the anchor - which doesn't feel or look good, especially when I have perfectly justifiable reasons for why that is where it is. So I say, whenever you get the chance, drop an anchor. They may drag it lower - but you don't want to know how much lower it would have gone if they weren't dragging it. Stay close to where you want to be - drop an anchor.

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