Adrian Herrera

If celebrating software maintenance is something you want to do, you should check out the Legacy Code Rocks conference MenderCon on May 16th! I’ll be giving the opening keynote: “Community Is Just as Important as Code” Registration link is in the comments.

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Commerce Hub Update As of the last week, the team are rolling out a Public Beta which enables the creation of Lists for the new Order and Cart objects. So obviously this isn't as cool as HIPAA compliance (announced last week), however it another milestone reached for the team on with all things coming together for a complete Commerce Hub experience 👀 More and more customers and partners are making use of Commerce Hub on a daily basis and finding that it is starting really close the loop on their buyers journey and paint a clear picture of where, when and why leads become customers. This enables them to build their brands from the whiteboard to trusted label and brand. Are you using Commerce Hub? Tell us about how it's going. Opt in-to the beta in your portal! #HubSpot #Commerce #BuildABrand

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The next Earthly Show and Tell is out with Dan Miller of Replay.io. Replay has some wild requirements for dev environments and it's neat to get a peak into how they handle it all, using AWS, Earthly, Tilt and dev K8S clusters. They are really going after the holly grail of totally ephemeral dev environments. https://lnkd.in/gm9nQpdM

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4 Things You Should Put in Your Daily Dev Log To harvest meaningful patterns from your dev log, you’ll need to capture the same things daily. I’ve been engineering software for 25 years, and I’ll share what I’ve routinely kept in mine. Your context is different, so your list will be also. Just make sure you capture the same things daily. Use this list as a skeleton to start from. It’s easier when you aren’t starting from a blank page! Pull Requests I keep track of every PR I submit, approve, or merge. Almost any work product I deliver or review flows through Git. My lists of PRs serve as a personal task-level kanban board of work in progress that I am connected to. These help me easily reconstruct a story of what I’ve done throughout the week. Personal Interactions I make note of every personal interaction I have, scheduled or otherwise. In addition to these notes, I keep a page for each person, and I link to that page from my daily notes. As I note patterns of interaction with a person, I’ll describe those patterns on their page. Over time I build a library of every person I’ve collaborated with and what we worked on together. Project Actions I keep a running narrative of the things I’m working on. I keep a section for each thing I’m working on. These might be at the product or story level - it just depends. Each time I hit a stopping point or interruption, I make a note of what I’ve been doing and what I plan to do next. Guess what I use to inform my daily standup updates? Perplexing Puzzles I make a note of everything that surprises me. These could be strange program behaviors, blockers, production issues - anything unexpected. As I review these periodically, I ask myself how I can use what I’ve learned to improve my mental models. Hopefully this list helps you get past the starting line. Do this faithfully for several months and see where it takes you!

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It is CRAZY how much weaker OpenAI GPT-4o is at coding from the completions API than GPT-4. I'm not sure if this is the intended result, but very surprising nonetheless. The training recency is very evident, i.e. it knows about much more modern things, but the difference between its logical output is great with GPT-4 just thinking in a much more sophisticated fashion.

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Another thing I do is track my time, religiously. Every single bit of "work" time I spend is tracked by client (which is sometimes my own company), project, and task. This makes it easy for me to see what I was doing, when, who it was for, and how long it actually took. I can also generate reports to see how much time I spent on certain types of tasks, including mundane things like "Processing" (which includes email, Slack, etc.)

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Has anyone ever encountered an ETL project that was technically challenging? I realized recently that I've been working with large data sets for a while, and don't have any examples of things that couldn't be coded in a few days by a junior engineer with decent coaching. In my experience, ETL is: 1. 85% semantic understanding of what the data represents, and how slightly different concepts / perspectives / business rules are best translated and combined (e.g., conceptualizing the difference between edits and first-order history) 2. 10% being tactical about filtering workloads, breaking them down into chunks, etc. 3. 5% writing code code I'm trying to understand the landscape around "no-code ETL" tooling and what I've got is: A. A bait & switch where platform vendors talk up how hard (1) is to someone that doesn't realize they're buying something that only addresses (3) B. Stuff like Snowflake and AWS Data Marketplace, which really just come down to "enforcing standards so you're not getting some janky zip of tars of PSVs from that one vendor" (I get this, standards are cool) C. Resume-padders doing A with B D? Your data lake / data warehouse SQL flavors that let you query files before / while importing them into a database, which legit does help cut down subsequent workloads (though only tangentially related to the discussion)

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Branching and Merging is the first step to setting up a new repository, and many would argue one of the most important. It sets the tone for how you will handle your code commits and impacts much of the work you do down the road. Most people use a strategy that they know, without really considering other strategies, or which might be best for their current project. This four-part series on Branching and Merging will give you a great opportunity to consider other strategies and the benefits of each.

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Thanks for sharing. This is very insightful, I was waiting for when something like this would come up as there is a lot of buzz about AI, and the people who depend on it the most are not experienced software engineers. This is scary because these users will not know when they are replicating/introducing bugs into there environments, or even worse exposing themselves to vulnerabilities. While AI, may help us work faster, it should not been seen as a replacement to system analysis, requirements gathering, system design, code reviews and VAPT Testing. These interactions are very much human dependent and remain important to a successful product development/roadmap. They can not be replaced by AI just yet. Finally, for engineers, if you have to use AI, make sure it is on technology you have extensive experience and fundamental knowledge on. That way you will know when you are fed the wrong code.

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If you are an investor in developer platforms, dev tools or play a role in building any business competing for developer audiences, then you need to pay close attention. 📣 The good folks at DevRel.Agency are committed to elevating the work of Developer Relations and the profession at large (more news on that later). Take my word for it, for a decade now, they have provided the de-facto data driven insights into the talent fuelling developer focused businesses. 📊 This year the State of Developer Relations Report will be richer than ever.🚀 Stay tuned…📺 #developerrelations #devrel #stateofdevrel #developerplatforms #devtools #executivesearch #lawsonbrooke

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Interview tip #4, y'all: let's talk about the coding assessment! First off, let's get the elephant out of the room: some jobs use automated technical screening platforms that assess your code against a set of tests/metrics/etc. These are bad and dumb and do those teams an incredible disservice. They're rarer than you think, but still much more common than they ought to be. If you've gotta do one, just do your best and hope they have a better screening process beyond it. I consider that practice a 🚩. 🤝 A healthy coding test relies on collaboration, just like your work on the job. You might be asked to work on a problem or project independently and then discuss it during a live interview later, or you might be asked to write some code live for an interviewer or panel. Here's the most important thing to remember: 𝐢𝐭'𝐬 𝐲𝐨𝐮𝐫 𝐓𝐇𝐎𝐔𝐆𝐇𝐓𝐒 𝐭𝐡𝐚𝐭 𝐜𝐨𝐮𝐧𝐭! Yes, you are being assessed on technical competency, but just brute-forcing through a solution in silence can be just as harmful as if you couldn't write code in the first place. Your interviewers want to understand how you're making your decisions and what trade-offs you're aware of. This can be scary in the moment. Here are some frameworks to check out that can help you feel confident: - "OICE" is an acronym for "Outputs, Inputs, Constraints, and Edge Cases". It's a simple way to verify your assumptions about a problem, establish a path forward, and demonstrate that you're taking a thoughtful approach before you write the first bit of syntax. You can read more on Medium: https://lnkd.in/eTRZTQc7 - "PREP" goes a little farther - "Parameters, Returns, Examples, and Pseudocode" takes you beyond just establishing what's needed and helps you practice writing out simplified algorithmic approaches. PREP is especially good for problems that feel really big. Even if you can't write a full code solution due to time constraints or technical challenges, you've already shown what you were working towards. Again, Medium has some more context: https://lnkd.in/eRRXyvZT These are great tools, but they don't mean anything if you can't deploy them on demand. To use them well you have to practice! Load up CodeWars and phone a friend - ask them to pick any problem at a difficulty level you know you can crush, and practice writing out just the framework portion of your approach. 💡 This is just as important as practicing your syntax! Being able to justify and explain the code you write is what differentiates you from every LLM on the block. ChatGPT can solve most problems faster than you, but it can't pick the most appropriate solution for a specific context without a lot of help and prompting. You, dear engineer, totally can! 💪 Flex that brain and learn to love the meta of coding, and these scary challenges become opportunities to show off your communication skills.

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As a dev team tech lead, I found that the best use of my time was NOT to lead by example. Sure I could put my head down for days and produce some clean lovely code... then show it to the team like "Behold! This is what you should be striving towards." Arguably I was never an amazing developer anyhow... but no as an SME in the tech stack the rest of the team is grappling with, I found the best use of my time was just to walk around and have a chat with the other devs. 100% of the time when I'd ask, "How's it going?" they would always be at a 'how do i solve this?' stage. One could say that programming is just a never ending series of 'how do i solve this?' problems. Sometimes a dev may have been stuck on something for 30 mins, sometimes a day, or sometimes have gone down a completely wrong path... and a chat that unblocks them or a tip for a quirky piece of kit so that the penny drops can really make someone's day and foster a team culture that promotes retention.

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Check out this cool combo: Venafi + Otterize Cloud are teaming up to make life easier for enterprises who want fully automated, hassle-free machine identity management and verification, all while keeping things nice and secure with Intent-Based Access Control (IBAC) policies. Here's the lowdown: 🔄 Full life-cycle automation for certificates and keys in the Otterize Cloud. 🔒 Intent-Based Access Control (IBAC) for stringent validation and less unauthenticated access. 💼 Improves efficiency and reduces administrative overhead. 🛡️ Enhanced protection and seamless management via the integration. Learn more below. ⤵ #Otterize #Venafi #CloudNative #IdentityandAccessManagement

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With both investors and the clients I partner with to improve the speed and quality of their software delivery, I always remind them: this is hard. If it wasn't hard, it would be boring, and we work on ways to get the best results. And we do. Over and over. Employees lives get better, investors get great returns, and we have a reduced risk of dementia later in life?!?! #winning https://lnkd.in/gxnSQ6nR #privateequity #devops

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RSVP: July 19: 12pm EST: Modern #softwareengineering (Building Better Software Faster), with Dave Farley https://lnkd.in/eE9iFRry What really works to help us build better software faster? What are the fundamentals of our profession, that if we get them right, and apply them whatever our goal and whatever our technology, will increase our chances of success. Some of these ideas have been hiding in plain sight, and if we just take them and build our practice and process on them, we do get better results. So what are they, what does that take, and what are the hallmarks of great software development? In this talk Dave Farley explores these ideas, and with examples from software and other industries illustrates each of 10 ideas that when combined can be used to form the basis of a modern, agile, engineering approach to software development. Dave also answers the question “what does ‘quality’ in software really mean?”. #softwaredevelopment #morewithless #organizationaldesign Bastiaan van Hamersveld Frans Meuwissen RSVP: https://lnkd.in/eE9iFRry

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