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Cincinnati, Ohio, United States
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Excited to be on the ground @AWSreInvent in Vegas this week. We found the session on severless architectures and serverless design patterns this…
Excited to be on the ground @AWSreInvent in Vegas this week. We found the session on severless architectures and serverless design patterns this…
Liked by Ryan Amos
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Thanks for having me, Shauna Swerland! Fun to be on the other side of the mic.
Thanks for having me, Shauna Swerland! Fun to be on the other side of the mic.
Liked by Ryan Amos
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TrueCar is proud to sponsor Automotive News' Best Dealerships To Work For. We look forward to participating in a conversation about the Future of…
TrueCar is proud to sponsor Automotive News' Best Dealerships To Work For. We look forward to participating in a conversation about the Future of…
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Best onboarding I’ve ever had. So glad to be a part of the Front team and this awesome culture!
Best onboarding I’ve ever had. So glad to be a part of the Front team and this awesome culture!
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Ted Neward
"Dead tech nostalgia"? "Dead" tech? Child, that "dead" tech is what powers all that "live" tech you young'uns barely understand! You like Javascript, do you? That language that was born before you learned to speak? Running on top of a virtual machines, the concepts of which were invented when your parents were little? Maybe you're all in to the Web? Invented back in 1991? Running on an international connection of networks, called the "Internet", that was put together by first researchers and then networking folks, waaaaay before your precious "WiFi" was anything more than Morse code over radio waves?!? Hmmmph. "Dead" tech, indeed. Getoffamahlawn! (I kid, I kid, but it IS true that if it was invented before you turned 20, it's "dead tech nostalgia", but if it was invented before you turned 40, it's "cool", and if it was invented after you turned 60, it's "hype" and "overblown". Can't wait to see Millennials' and GenZ's reactions when GenAlpha starts taking shots at their parents.... ;-) )
1019 Comments -
Evan Light
Let's face it: "software engineers" and "software developers" are *not* craftspeople. We are usually a business cost-center that converts business requirements into customer dollars. Setting aside the political baggage of the Software Craftsperson (nee "Craftsman") movement (and those original words alone convey some of the baggage), I find now that I regret the entire movement itself. Paid software development is about serving a business need and rarely about crafting software that is optimized for flexibility, reliability, and understandability. When businesses seek to turn a need into software, they are often concretely planning for a quarter, loosely planning for a year, and pipe-dreaming when they "plan" for anything over three years. This has an impact on software developers. The cost of converting ideas into software usually scales something like logarithmically to exponentially with the complexity of the business. Software is usually developed with an eye toward achieving a quarterly or annual goal or an investment round--so let's say 3 to 12 month window. Management expects to be able to measure results. And, so, in most environments, you need deliverables that can be demonstrated to management in order to show progress. Except for those ideal cases where eXtreme Programming actually works (e.g., customer is always onhand for clarification, no artifacts other than code and test code, team of up to maybe 8 people, often working in pairs, etc.), the complexity of converting business needs into code is complicated bordering on complex because businesses are complicated bordering on complex. (I use the Cynefin definitions of "complicated" and "complex" where "Complicated" means something like"with a reasonable amount of effort, you can somewhat reliably predict outcomes" and "Complex" means that "this system/business is so complicated that you cannot reliably reason about its properties and so properties and outcomes are emergent) Given anything but a project or business with an exceedingly clearly bounded minimum viable product, we're rarely crafting but instead struggling to meet quarterly/annual/funding round deliverables. But wouldn't it be wonderful if we could find our way back to when software developers were able to ship software they could be proud of and businesses were better for it? Perhaps it's still possible. But we all have to be playing a long game, business and developer.
132 Comments -
Nick Carroll
I've seen a few people in my feed calling out Andy Jassy for not mentioning or giving any credit to the employees of Amazon for their recent financial success (in their public filings). While that's accurate, I don't know that's it's fair to criticize Jassy for this, at least in comparison to the rest of his tenure as the CEO there. In particular, there's no data to support the idea that Jassy cares about the employees at all; remember, this is the same person who hired people as remote employees during the pandemic, and then brutally shifted the company's remote work policy in direct opposition to both the data and employee feedback, and effectively fired anyone who would or could not comply (which in some cases, meant upending their lives and families to relocate for the company). Jassy is a relentless cost-cutter, who (to his credit) is relentless focused on _his_ customers, the shareholders of Amazon. I'm 100% certain that Jassy would eliminate 99% of the employees of Amazon tomorrow, without any second thoughts, if he thought it would raise the net profits by even 5%. I'm certain Jassy views the human employees of Amazon as just an unfortunate business expense, and only marginally contributory to his personal efforts to optimize the company's profit margins. There are some really good/smart people who work hard to keep Amazon successful, and overall they have done a pretty good job as a company, and this post isn't intended to take anything away from that. I'm just noting that Jassy demonstrating that he doesn't care about, or even acknowledge, the work of the rest of the employees there is 100% in line with who he appears to be as a person and CEO, in my experience.
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Ryan Rodemoyer
Observation: 9/10 SWE's quit at “reading the docs”. Cut through the BS with this easy trick: Take action and build. Writing code is 100x easier than the docs make it sound. “Reading the docs” gave me crazy imposter syndrome: -Git -WPF -Kafka -OAuth -Angular -GraphQL -RabbitMQ -Kubernetes In ALL cases, I conquered my fears by building. Except for WPF. I gave up on that. And Kafka, that's for another day. Forcing yourself to build/code/deploy melts analysis paralysis. Then you'll say "oh that was pretty easy". Trust me, we aren't building rockets. Practice AND Study build true mastery.
221 Comment -
Kyle Rowland
One frequently observed shortcoming in technology executives is found in their own software craft... namely, a completely missing TDD practice. It's not something that's been expected or taught in preparation for leadership roles (or even engineering roles, in a lot of cases). So it's not without some reason that this shortcoming is so common. That's not to say you have to live with it. Here's a quick guide to learning TDD as you carry out your leadership role: https://lnkd.in/geAfPfmp
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Peter Gillard-Moss
A water slide gave me a great chance to teach my son Theory of Constraints and Flow when we saw people queuing at the *bottom* of the slide. Me: why do you think there’s a queue at the bottom of the slide not the top? Son: because there aren’t enough inflatable tubes. Me: where do you think the queue should be? Him: at the top Me: why? Him: because you want people to be going down the slide all the time Me: right, that’s where we would measure throughput. Number of rides per minute. How many tubes do you think they need? Him: about 4 or 5. Me: if only one can go at a time why 5? Him: because it takes a long time to get up the stairs [there were 75 in total]. And it’s quicker to come down and get out. There would be 1 going down the slide, 1 waiting at the top to go next, 1 at the bottom just finished and 2 heading up the stairs. So my son could identify that the flume was where you wanted to maximise throughput, that the bottleneck was the stairs, that tubes were a resource constraint and you needed more of them than you would have in active use (leaving most of them idle). He also knew the best place to put the queue was before the ride not after. BTW later they did get 5 tubes going and the queues disappeared! Even a child can understand TOC and Flow!
458 Comments -
Chris Henry
I've been working in tech for 20 years, and it's clear we're in a rough patch. Here are some of the challenges this industry is facing: 1) Belt tightening In the last couple of years, engineering teams have enjoyed free money to buy all sorts of value-add tools. Hiring was easy, with companies willing to pay top dollar for tech talent. But that’s all changing now. Teams are getting cut, and you need to think more about how to work with fewer resources. It's about getting back to basics - figuring out what's important and what's not. 2) Influx of hiring applications If you're lucky enough to have open roles, you'll be inundated with hundreds of applications. This creates a challenge in filtering through them to find the best candidate. Previously, 100 applications were manageable, but now with hundreds or sometimes 1,000 applications, it’s harder to separate the wheat from the chaff. You need to be more specific with skills and questions in the job posting and on LinkedIn. However, the more you do this, the more likely you are to lose out on an excellent candidate who isn't willing to jump through those hoops, even in this market. A champagne problem, but a problem nonetheless. 3) Ambiguity around team's futures, whether there will be layoffs Carta, a company that manages many startups' cap tables, released data showing an increase in startup shutdowns in Q2 (linked in comments). If you're working at a series A, B, or C startup and it's clear that numbers aren't being hit, you have to deal with the ambiguity of your future at that company. For ICs, it's tough to just sit there and bear it. For managers, it's a real leadership challenge to ensure everybody stays focused, and feels like the work they’re doing will allow them to keep their job. 4) AI will be misconstrued as a substitute for quality engineering At struggling companies, leaders may turn to AI and say they don't need certain departments because of chatbots or generative AI that writes code. They may misconstrue these capabilities as something they can use to cut people. 5) How to meaningfully integrate AI into your products On the bright side, there's the question of how to integrate AI safely. Air Canada's chatbot giving wrong information and getting sued highlight the challenges. But despite the risks, not investing in AI will ensure your organization gets left behind. --- What are some challenges you’re seeing?
71 Comment -
John Clifford
When there is great uncertainty, there can't be predictability to any useful level. We have to reduce uncertainty to where it can be managed effectively, and we do this by running experiments... trying things. Does the stakeholder like what we've done? Does the customer like what we've done? Are we solving the problem that customers have? This puts us in the 'complex' quadrant of the Cynefin Model, where we have to try and (perhaps) fail, perhaps repeatedly, until we know enough. Yet, we still have a goal in mind and we at least know the first few things that need to get done... or the first thing we need to test to determine feasibility. Apple knew that unless it could source a ruggedized hard drive that would withstand being carried and occasionally dropped, the iPod would not be successful... so getting a commitment from Western Digital (who had been working on such a drive and was almost ready to ship) was the key decision point. The Wright Brothers knew that unless they could figure out a way to turn their airplane without 'skidding' and stalling a wing (a problem that had killed many of their inventive contemporaries) they couldn't build a safe airplane... oh, and find a lightweight, powerful-enough motor while you're at it. It all comes down to reaching decision points: do we know enough to know whether to continue, or whether to cancel our effort? In the example below (waterproofing a below-ground basement), we are going to have to continue. Therefore, we want to continue only at the pace at which we are certain of the decisions we're making. Is what we're doing working? If so, do more! If not, do something else. That is exactly what the contractor did in the post below, making 'MVP' experiments until the path to success was clear, until they had the 'Aha!' moment. So, when do we get predictability with useful accuracy? At the 'Aha!' moment. Figure out what 'Aha!' moments are needed, devise experiments to reach those moments and drive enough uncertainty out (you'll never get to zero) to where the range of uncertainty is acceptable. #predictability #forecasting #estimation #commitment #agile #planning #riskmanagement #projectmanagement
33 Comments -
Ricardo V.
Last night I finished watching Amazon's Fallout TV series. ☢️ (Trailer: https://lnkd.in/eKy2Jxsd) If you haven't seen it yet go and watch it, it was good! The Vaults looks like an interesting idea to survive the apocalypse, also reminds me of another TV series called Silo (based on the book series "Wool"). It got me thinking. These concepts should be self-sustained, but what happens if they need to be interconnected with a mainframe for things like monitoring, remote control, support, etc? Let's design a basic system of communication between these Vaults. ☎️ According to Fallout's wiki, there is a vault named Vault 0, which was meant to serve as a mainframe for the other vaults and controlled by AI. ☢️ As you can see in the graph, each vault has its local server to be able to work in isolation. And each one of them is connected to Vault 0. ☢️ There can be 2 types of communication between them: ➡️ Asynchronous: one party sends data to the other without expecting confirmation. Example: Vault 11 sends a signal every hour to Vault 0 reporting that all systems are nominal. ➡️ Synchronous: One party sends data to the other and waits for confirmation. If no confirmation is received it can retry multiple times before taking other actions like sending an alert. Example: Vault 0 can send a signal asking Vault 11 to confirm a security code before sending a secret message. If Vault 11 doesn't respond with the correct code, then Vault 0 doesn't send the message. This architecture is used in real life and in a wide variety of industries: health, space, banking, government, farming, law, etc... Did you watch the show? What other real-life problems can you think of from it? Comment below 👇 #techentrepreneurs #softwaredevelopment #saas #softwareasaservice #spaceindustry #banking #farmingtech #solicitors
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Jason Gorman
I'm looking at two dev teams: Both are about the same size and average experience. Both are programming in C#. Both use the same IDEs. Both use Git and GitHub. Both are deploying to the same Cloud platform. One deploys most days with very little drama. One deploys every 6-12 weeks, and routinely starts fires in production that take days to put out. One has an average delivery lead time of < 14 days. One has an average delivery lead time > 3 months. They both work in the same business, under the same CTO, who openly values one of these teams above the other. Can you guess which one?
19794 Comments -
Ben Thorp
Predictability is the most insidiously destructive force in software development. I recently wasted $3k on 2 failed attempts to waterproof my basement. Finally the 3rd attempt was successful. Total cost of $9k, 2 weeks of duration, 2 walls to refinish. This, just a week after being laid off. I was super frustrated by the multiple attempts and "hidden" costs. But after finding my chill, I had an epiphany. Demanding certainty would have made it much worse. Additional work to create an "accurate estimate": - Run cameras up all drain pipes to fully inspect their flow - Dig up the pipes to manually inspect where the camera couldn't reach - Manually saturate (with a hose) each wall to try to reproduce the leak - Tear out every finished wall to inspect the concrete wall surface - Dig down to the foundation to inspect the footer drains directly Call it 3-5 days of work, at least $10k. I'd also have to re-grade / re-seed my yard and refinish the walls. And the basement would still be leaking! The point: predictability is EXPENSIVE. The contractor knew this and instead of wasting my money on estimation accuracy, they ran a $3k value experiment. Saved me 1000s. And yet… in sw development (arguably MUCH more complex), we insist on optimizing for predictability, front-loading knowledge work so we can accurately forecast how much hands-on-keyboard work can fit in an arbitrary 2 week window. Spending as much (or more) on work breakdown so we can accurately measure throughput. Cutting corners to meet the deadline. Squeezing out slack time required for sustainable pace. Reducing sw dev down to order taking, killing the spirit of innovation. Burying agility under layers of process and governance. And in the end, did we even fix the leak? 🤷♂️ In Software Engineering, we've fully automated the predictable parts already. What's left is R&D.
6522 Comments -
Sebastian Kline
Ticket velocity isn't the *only* measure of an engineering team's effectiveness. At a high level, the best engineering organizations can predictably deliver against the priorities set forth by the business. That involves proper monitoring (through metrics) and coaching by effective managers. Here's a few non-velocity metrics I use to measure my organization: - Tenure of the team. - Platform uptime. - Number of critical issues in the last 8wks. - Automated code coverage percentages. - *Employee* vs customer detected bugs. - Number of requirements missed during project planning. Read more about my leadership style here: https://lnkd.in/geP2m7DJ #metrics #engineeringeffectiveness #team #leadership #software #tech #startup #management #dora #space #agile #projectmanagement #podcast
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Jesse Riley
"But we'll have to rewrite/rebuild/redo it" "We don't want to do it twice" "It's just throwaway so it's a waste of time" Yea? So what? How do you know? You haven't built anything yet. Building things that don't exist yet, have zero 1:1 example, existing outside the realm of certain are ...messy. Not only are they messy, but it is also the definition of uncertain which scares the hell out of most people. When I hear concerns (fear) around not being perfect, I defer back to action, trying something, doing something, other than sitting around to talk about it. Why? 2 reasons. 1. I may not ever have to do it again because it might be good enough, and that buys me time to do other things. 2. If I need to build it again, I will have way more insight, skill, learnings and experience than I do right now to build something significantly better than I do right now. Maybe, just maybe ...it's ok to do it "wrong" the first time. https://lnkd.in/gg-F-mRA
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Larry Diehl
🚀 If you haven't heard, I've been working on an API testing startup called Colimit 🚀 🐞 We've made a devtool that automatically finds bugs in APIs (similar to chaos testing or fuzzing, but for functional correctness bugs) and integrates directly with test runners of popular frameworks (like Rails, Next.js, Django, etc.), avoiding flakiness and changes to your development workflow. 😱 We're looking to partner with companies dealing with large legacy applications, where development is bogged down by fears of breaking existing functionality. If your app is so complex that changes are daunting and no one fully understands it anymore, Colimit give you the safety net needed to get dev velocity back up. 🔍 With Colimit you can document your app's workflows as executable specifications, giving you a high-level overview of what your app is supposed to do. Our verification engine then rigorously tests your app to ensure it performs as expected, uncovering bugs along the way. ✉ If you think Colimit could help your team, please reach out to me via a LinkedIn message, or send an email to larry at colimit dot io. 👍 Also, I'd really appreciate any likes and shares to help with outreach :)
11414 Comments -
Amr Elssamadisy
We are (at least some of us) being dishonest, or at least negligent. "Hallucinations" from AI.... Seems to me we are either passing the buck, being lazy, or just... well... being dishonest. So AI gives us some information: * We don't review: then being lazy or negligent. * We do review, and kind of ignore, well... being dishonest. With all the breakouts about AI "they took our jobs!!! (Southpark reference - https://lnkd.in/gV-aJuDd)".... Maybe they will one day. But today, they are incompetent at least 10% of the time.... The responsible thing to do is review and consider before we use....
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Rick Boone
Question for engineering leaders (managers, directors, VP's, etc): I'm curious about the current landscape of developer productivity analysis + management tools - things like LinearB and Jellyfish. Which tool, if any, are you using? Any opinions/pros/cons on the tool you're using (or the entire domain overall)?
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Amitai Schleier
Premise: Everyone involved with software teams needs them to pay off. Claim 1: Compared with other ways to try to ensure ROI, #XP is hardly extreme at all. Claim 2: XP is therefore for everyone involved with software teams. "Not So #ExtremeProgramming": link in the comments.
112 Comments -
Bernard Traversat - We're hiring.
We released a new update of our Visual Studio Code Java extension. Go try it! Bunch of new improvements and already supporting JDK 23 Early Access builds as the extension is directly leveraging javac. https://lnkd.in/g8BKsNjS #java #IDE #OpenJDK #VSCode
611 Comment -
Jason Gorman
Why do I favour practices like developer testing, TDD, refactoring and continuous integration? It's to enable rapid & sustained evolution of production-ready software. The odds of delivering the right thing in a single pass are so remote that many iterations are likely required. And even when we hit the bullseye, it's almost always a moving target. Not least because putting software into an environment has a tendency to change that environment and the problems we need to solve.
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