The Hidden Cost of “Agentic Development” in Enterprise Teams
There’s a shift happening across engineering teams right now. Developers are spending less time searching, planning, and wiring things together,...
RAG != Context
Understanding the limits of retrieval in real software systems Over the past two years, retrieval augmented generation has become one...
Bigger Context Windows Won’t Fix AI Coding
The past two years of AI development have been defined by a race toward larger models and larger context windows....
Context: The missing layer in Enterprise AI
For the last two years, the AI conversation has been dominated by one thing, new model releases. Every few months, there's another announcement, a bigger model, a faster model, a more capable agent, a new benchmark, a new demo. And to be clear, the progress is real. The models are extraordinary. https://tabnine-2.wistia.com/medias/e2u5n3lf3i But inside enterprise production environments, something different is happening. The real bottleneck isn't model capability. It's that...
How AI Context Engines Reduce Technical Debt Across Distributed Teams
Technical debt rarely shows up all at once. It accumulates quietly. A quick workaround to hit a deadline. A duplicated...
From Code Completion to Code Understanding: The Rise of Context Engines
For years, AI in software development has meant one thing: autocomplete. You start typing a function. The assistant predicts the...
Why Context Matters in AI-Driven Software Development
For the past two years, the software industry has been fixated on model size. Bigger models. Longer context windows. Faster...