Most teams still write code first and specifications later. That worked when systems were smaller and requirements were simple. It breaks down quickly when software becomes distributed, AI-assisted, and product-driven. A spec-driven workflow flips the… Spec-driven development is quietly becoming one of the most powerful workflows in modern engineering
They try to do everything in one step. A single prompt.A single response.And we expect perfect results. In reality, this approach is slow, brittle, and error prone. The model has to reason, decide, and produce… Most simple AI agents fail for one reason.
Back then, when building products, everything was clear in my head. The requirements. The vision. The architecture. I knew what to build and exactly where it should live in the system. And I kept wondering:… Three years ago, I had a simple thought. Today, it is a reality
But we still version control only the output, not the reasoning Entire.io is addressing that gap Their open source CLI, Entire, integrates with Git and captures full AI agent sessions alongside commits. These records, called… AI is generating more code than ever
LLMs are being integrated into products and internal systems at unprecedented speed. Security is often treated as secondary. An LLM is not just another dependency.It is an execution surface. Integrating an LLM introduces a probabilistic… Security Considerations When Integrating LLMs
AI has compressed the time it takes to translate ideas into working code. That advantage is now table stakes. What still cannot be automated is product thinking. In an AI driven lifecycle, engineers are expected… The software engineering lifecycle has shifted, and code is no longer the hardest part
As agent-based systems grow, a single agent handling everything stops working.You need multiple AI agents, each with a clear role, working toward one outcome. That is where AI agents succeed or fail in production. In… Most real-world AI agent problems are coordination problems, not intelligence problems.
Earlier, a large part of engineering time was spent translating intent into code.That translation step is what has shrunk. AI now converts a clear mental model into working code in minutes. What did not shrink… Coding agents did not make product building faster. They moved where the time goes
I was reading this Anthropic engineering article on building agents, and one section stood out for its clarity and honesty:https://www.anthropic.com/engineering/building-agents-with-the-claude-agent-sdk The part on semantic search is especially worth attention. Semantic search works by chunking context,… Everyone is reaching for vector search. Few stop to ask if it is actually the right tool
Not because the model is weak.Not because embeddings are bad.But because the data feeding them is messy. Retrieval Augmented Generation only works as well as the structure of the data behind it. If your inputs… Most RAG systems fail for a reason no one talks about