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AI isn’t coming for your job; it’s coming for your YAML

AI isn’t coming for your job; it’s coming for your YAML

We don't use Agents for "Magic." We use them as a Semantic Logic Layer. This allows us to deliver the feeling of a bespoke consultancy with the economics and scalability of a SaaS product.

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Vision

How engineers survive without runbooks during incidents

How runbooks work in AI SRE agent era?

Vision

Fast Code or Fragile Systems

An effective AI agent should be able to follow an issue from a production alert, through system behavior, all the way back to the root cause in code — and forward again to a safe, confident fix.

Product

Anatomy of an Agent (Spoiler: It’s Still Just Code)

Anatomy of an Agent (Spoiler: It’s Still Just Code)

Case-study

Ewake 🤝 Booksy Case Study

How Ewake reduced SRE operational toil at Booksy

Reduced alert fatigue using AI powered alert response

Vision

No More Pager Fatigue: Intelligent Alerting for Work-Life Balance

How AI Agents can help to reduce alert fatigue for the software engineering teams

LLM calls in your code

Vision

Beyond the Demo: Real-World Problems with LLM API Implementation

Beyond the Demo: Real-World Problems with LLM API Implementation

Product

The AI Agent: Breaking Free from the SaaS Mold

Discover how integrating LLM API calls transforms software development — not just by outsourcing logic, but by shifting how we think about cost, determinism, and engineering trade-offs in dynamic systems.

💡 How Ewake reduced SRE operational toil for Booksy: read the article!