Where Does Temporal Even Run When You’re All-In on Vercel?

The content discusses integrating Durable AI into a serverless application, InterlinedList. The challenge arises from needing persistent components, like Temporal services and workers, which conflict with the serverless model. The solution involves adding one always-on worker to manage tasks while reusing existing codebase and maintaining app structure, ensuring budget control and process integrity. Continue reading →

I’ve Been Brainstorming Durable AI for InterlinedList, and It Kept Pointing at Temporal

Adron explores the challenges of integrating durable AI features into InterlinedList, which is entirely serverless. Key obstacles include serverless limitations on memory, scheduling flexibility, and cost management. A proposed solution is to employ a durable-workflow engine, like Temporal, which enhances efficiency and reduces costs associated with AI token usage. Continue reading →

That Gap Is Still Widening, But The Bottleneck Was Never Engineering

The content discusses the widening gap between organizations effectively leveraging Generative AI and those that are not. It argues that management bottlenecks, rather than engineering inefficiencies, are the core issue hindering progress. Generative AI exposes these inefficiencies, emphasizing the need for systemic thinking and simplification to fully realize productivity gains. Continue reading →

“Loop Engineering” Is Mostly Just Broken SDLC Wearing a Costume

Adron critiques the concept of “Loop Engineering,” arguing it merely retrofits outdated software development practices onto language models. This approach adds unnecessary complexity and coordination, hindering LLMs’ potential. Instead, the author advocates for creating efficient workflows that leverage LLM capabilities by improving input quality, structuring tasks by data flow, and integrating event-driven feedback mechanisms. Continue reading →

The Gap Is Widening and It’s Not Slowing Down

Brendan O’Leary’s recent article highlights the slow adoption of AI coding tools among engineers, noting a widening gap between early adopters and others. Despite challenges like security concerns and past negative experiences, teams that integrate AI effectively gain significant advantages. Current adoption must be disciplined to avoid creating technical debt while enhancing productivity. Continue reading →