ambient-code.ai

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  • The “CEO Archetype” is the new 10x

    We are entering a period where the initial “shock” of AI capabilities is fading, replaced by a ruthless reality: The learning period is well underway. What do we do with a boundless new toolset? In 2026, the question isn’t “Can AI do this?” its: Who do you want to learn with? Public “Oh 💩” Moments — read more

  • What’s it doing? A convergence of thought.

    Something strange is happening to original thinking. Engineers who’ve never met each other are arriving at eerily similar ideas within days of each other. Everyone is using the same tools to “think” now, and those tools are shaping thought in ways we don’t fully appreciate. When millions of people ask similar questions to the same — read more

  • Lethain has finally weighed in on AI adoption

    Will Larson published a post last week on facilitating AI adoption at Imprint. It’s one of the most practical things I’ve read on the topic. It’s that way because it speaks from hands-on experience. If you’re an engineering leader trying to figure out where to start, read, then do. The post maps to a lot — read more

  • 6 thoughts on my first AI.engineer CODE + AI Native DevCon

    AI.engineer was exceptional. We should crowd-source somehow keeping it the way it is. Larger conferences typically operate at a higher altitude and there is a useful niche for smaller technical events. Recordings here. I wanted to reflect on some common trends across talks from Stanford, McKinsey, Capital One, Every, Tessl, Human Layer, and others. But — read more

  • Your Codebase Is Probably Fighting Claude (part 1)

    I have been trying to keep our genAI workloads “in the pocket” of a maximum effective context window.  For performance, accuracy and the second order cost control benefits from those. Things work beautifully, but it’s not at all efficient (wrote about an efficiency requirement in this article). The Real Problem Most codebases evolved for human — read more

  • Agentic Development: A Day in the Life

    Re-envisioning what a day in the life of a software engineer looks like going forward in this agentic vision… We’ve talked about why Ambient Code matters and what it means for your career. So what does your day look like when you’re shepherding code instead of writing it? The Morning Dashboard (8:00 AM) You grab — read more

  • Tokenomics for Code: Value per Token in the Agentic Era

    Think about how much will change in the AI landscape during the lifetime of your next application. You can bet on improvements to code generation models, hardware, talent, review capabilities and more. This leads us to the need for a new metrics: something like TCO, but that also represents efficiency. I propose Value Per Token — read more

  • Sowing the Agentic Brownfield

    In the near future, it’s entirely plausible that your entire codebase will be written, refactored, and evolved by AI agents. But the “brownfield” you’ll inherit won’t be legacy human code, it will be legacy AI decisions. And those decisions will stem from choices you make today. For example, whether and when to adopt an AI-first — read more

  • Evolving what development means

    The shift to Ambient Code isn’t about replacing developers. It’s about evolving what development means. There are valid concerns AND solvable problems. Leaving engineering efficiency on the table is not an option. “I Don’t Trust AI-Generated Code” Ambient Code works the same way. You don’t trust the code because an AI wrote it. You trust — read more

  • The Path to Vibe Coding for the Enterprise

    Hey folks, I’ve been spending a lot of time thinking about how we write software. Actually, this was spurred on by a recent project: I thought, how can I drive inference workloads to llm-d? How can I keep vLLM “hot”? codegen is an inference-heavy workload, so let me look deeper. What I found was a — read more

https://github.com/ambient-code