Jeffrey Tremblay

Two decades ago when I started my career we used to write clean code and detailed docs so the next developer could handle change or any issues. But that era is changing fast. AI can now spin up TypeScript resolvers, GraphQL schemas, in seconds. The tactical layer of coding is becoming commoditized. The tech lead and senior developer’s role is shifting too — from writing functions to guiding architecture and intent. Because today, the “next developer”… is an AI. The SaaS providers need to expedite their product roadmap and thinking towards AI enabled system configuration of data models, workflows, endpoints etc. so thier customers can 10x their digital deployment journey.

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I was reading about Lee Robinson migrating cursor.com from a headless CMS back to raw code and Markdown. Estimated time: 1-2 weeks, probably with agency help. Actual time: 3 days, $260 in tokens, working with AI agents. While the speed he delivered it in is exciting, it's why he did it that is interesting to me. The CMS was preventing agents from helping. Content pulled over the network wasn't in the repo—agents couldn't grep it, couldn't edit it with a simple prompt. His line that stuck with me: "With AI and coding agents, the cost of an abstraction has never been higher." Here's the thing: agents work best in text, not UIs. My mind naturally goes to business automation tools. UI-first tools like Power Automate and Zapier weren't designed to be text-first. They grew up in an age where abstracting the text away from users was a design goal. Now that things have changed, they're faced with a challenge. When they bolt on code or agent interfaces, it's an abstraction on the abstraction. Which doesn't seem like a particularly good design pattern. If you're not using these tools yet, I wonder if they make sense today. If you are, is the UI first approach holding you back? https://leerob.com/agents

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In engineering, craftsmanship beats cost-cutting every time. This Stanford chart shows: true value lies in quality, not just price. Interesting to see how smaller teams can outperform, even with fewer years of experience, Romania being a standout example. It’s a good reminder that team size and tenure aren’t everything when it comes to engineering excellence.

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Most companies think Platform Engineering is about tools. IMO, it’s not. It’s about reducing the cost of change. An Internal Developer Platform isn’t a product — it’s a decision-making framework: - Standardize what is done differently across the org - Automate what is repeated - Expose reusable parts and modules - Reduce anything that distracts from meaningful engineering work When the platform gets this right, velocity accelerates without burning people out. When it gets it wrong, you’ve just created a shinier bottleneck. Platform Engineering is not DevOps on steroids. It’s the operating system of the business.

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What should your priorities be for 2026? The organizations pulling ahead aren't removing engineers from the loop, they're making engineer expertise count where it matters most The sources suggest that organizations must 1. Master multi-agent coordination, 2. Scale oversight through AI-automated reviews 3. Embed security architecture from the very beginning of the development process. Those who treat agentic coding as a strategic priority will be the ones to define the next era of what is possible in software. The landscape of software development is undergoing its most significant transformation in decades . According to the sources, by 2026, the industry will be defined by agentic coding, where AI agents shift from being simple tools to active collaborators in the development lifecycle. Here are the key takeaways for engineering leaders: 1. From Coder to Coordinator: Engineers are moving away from manual coding toward building and coordinating agents, This shift allows human experts to focus their efforts where they matter most Architecture, System design, and Strategic decision-making 2. The Collaboration Nuance: While developers use AI in roughly 60% of their work, they only fully delegate about 0–20% of tasks , This highlights that effective AI integration still requires significant human oversight, validation, and judgment . 3. Proven Impact at Scale: Organizations are already seeing massive efficiency gains #SoftwareEngineering #AI #AgenticCoding #TechTrends2026 #EngineeringLeadership

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The software development world is witnessing something unprecedented: traditional economic models are crumbling faster than anyone anticipated. While a quarter of Y Combinator startups now utilize 'vibe coding' to accelerate development, we're essentially watching the entire cost structure of software creation get turned upside down—and most people are completely unprepared for what this means. Here's the uncomfortable truth nobody wants to discuss: this isn't just about faster development cycles or trendy methodologies. When 40% of experienced developers report significant maintenance challenges in projects using this approach, we're looking at a fundamental restructuring of how we price, budget, and economically justify software projects. The question isn't whether 'vibe coding' works—it's whether our entire industry can adapt to a world where traditional development economics no longer apply. What's your take on the future of software development economics? Share your thoughts in the comments—let's spark a debate! #FutureOfTech #SoftwareEconomics #DisruptiveInnovation

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Buffering hides problems, it doesn’t fix them Buffering is often treated as a safety net. In reality, it’s more like a credit card. It defers the cost until the system is under real load. What usually breaks isn’t throughput. It’s timing assumptions leaking across layers. Buffers don’t buy safety, they buy time, but only if you know how you’re spending it.

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