Ian Walter

Context-switching is not just a buzz word. It's something that is integral to successful agency work. Not hiring engineers with this in mind can be a huge problem. The smartest CTO -- and now technical recruiting whiz -- I know has some big thoughts on this, questions to ask to find these unicorns and red flags to keep an eye out for during the interview process. If you need to grow your team, this is a must read as Jason Trobman has successfully hired and placed hundreds of engineers. https://lnkd.in/d9mKKNGw

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Really loved this read, a very practical approach to languages and platforms. https://lnkd.in/ej3tGd9s 'Is it boring? Yes. But solving CRUD operations at scale shouldn’t be exciting. It should be boring and safe. It’s 2025 —we as an industry should know how to scale CRUD apps to hundreds of thousands of queries per second safely and reliably without bugs, without performance bottlenecks, and without “excitement.”'

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Don't believe the BS that you can use Claude Code for free. Ollama recently made their API compatible with Claude Code. Many creators quickly jumped on the opportunity to farm engagement with the hook: "You can now use Claude Code for free!" My thought? Claude Code without Opus 4.5 is not Claude Code. Period. But this is exciting news. Not because I can use Claude Code for free, but because I see an opportunity to optimize costs by delegating easier tasks to local LLMs. The key question is: what tasks can local LLMs handle? I tested out 7 local LLMs. In this post, I will explain the BS and share my 1st experiment. -- Why the BS? Claude Code has been praised as one of the best AI tools by its users, not only for coding but for many other tasks. But the price feels steep to many. The $20/month plan is not enough for any serious work. You need to at least subscribe to Max 5x ($100/month). Many heavy users, including me, subscribe to Max 20x ($200/month). It’s a steal. But still, many were eager to try it but aren't ready to pay. Ollama's recent announcement means you can buy a Mac, a Strix Halo, or a GPU and use Claude Code for "free" with local LLMs. It’s appealing, as it is a one-time investment, and you can use the machine for other purposes. Creators are leveraging this opportunity to farm engagement. But the reality? Claude Code without Opus 4.5 is not the same Claude Code we praised. Local LLMs are far less intelligent. -- But for those who understand the difference, we see an opportunity to optimize costs by delegating some easier tasks to local LLMs. I'm interested in finding out what tasks local LLMs can handle. This is my typical flow when using Claude Code. This is for coding, but I have similar flows for marketing and content creation. 1. Research and planning 2. Create PRD and implementation plan 3. Break plan into bite-sized tasks 4. Implement + review with reflection pattern 5. Final review with agents 6. Final review and QA by me Based on my quick tests, we can forget about asking local LLMs to do research and planning. All of them failed at a simple instruction: "Visit https://learnparrot.ai/ and tell me about the website." So, I think the most viable use cases would only be (4) — implementation + review loops. While it looks like a very narrow use case, it is where we burn a lot of tokens. So I think it is worth a try. The main selection criteria for this will be instruction-following capability. One very common task is to refer to code samples or templates to code a new feature or page. This is a good test of instruction-following. So, I crafted my first test: - Used Opus to create HTML that I can screenshot as a LinkedIn carousel to display info for each model. - Turned one of the pages into a template and deleted the rest. - Asked each LLM to refer to the template to code its own page, given its specs. Swipe the carousel to see the results. Who would you hire? #LocalLLM #ClaudeCode #VibeCoding

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A new release of Rotonda, NLnet Labs' composable, programmable #BGP engine in #rustlang, is now available. Version 0.4.0 'Bold and Undaunting Youth' features and #RPKI RTR component, as well as Route Origin Validation on incoming routes. https://lnkd.in/eT3V8Zk3

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3 reasons why we build software and service as one team: We don’t build tech *for* operations at Tandem. We build tech *with* operations. Here’s why that matters; 1) Fix friction at the root. If a vet has to click 5 times to do something that should take one, we fix it. Not just because it’s “inefficient”. But because it creates cognitive load, slows care delivery, and compounds under pressure. Less friction = faster throughput, fewer errors, and lower burnout. 2) Close the loop between builders and users. The person who writes the feature talks directly to the person who uses it. That means issues surface faster, fixes are more accurate, and nobody ships something that “technically works” but operationally fails. It’s not just “faster iteration” - it’s tighter alignment with reality. 3) Scale the system, not the sprawl. New clinics, new roles, new workflows. We don’t layer on SaaS duct tape. We evolve a system designed to flex with operational growth. That means fewer integration points, tighter control, and a consistent experience from core to edge. We don’t treat tech like a layer. We treat it like a nervous system. Because when you’re delivering care in the real world, you can’t afford delay, dissonance, or dropped signals. That’s why we built Tandem the way we did: One system. One team. Zero silos. Because when service and software evolve together, the whole organism gets smarter, faster, and stronger over time. ------------- Hi, I’m Doug. I’m the Chief Technology Officer at Tandem. We’re engineering the backbone for modern pet care. Follow me for posts on: * How we build tech with ops, not for them * How we build tech tools that scale cleanly * Scaling hybrid companies without SaaS bloat

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