From the Front Lines of Tech

Struggling with customers who treat their business context like state secrets? You are not alone. In the world of high-stakes tech sales, "it's confidential" is often code for deeper fears about risk, cost, or capability. This post explores creative deal-structuring strategies for the tight-lipped clients. Pivot from selling "business value" to selling against technical KPIs, de-risking "internal initiatives" with phased contracts, and winning over the "we're unique" crowd with managed services.

Demystifying hardware acceleration and the competing sparsity philosophies of Google TPUs and Nvidia. This post connects novel architectures, like Mixture-of-Experts, to hardware design strategy and its impact on performance, cost, and developer ecosystem trade-offs.

The software development paradigm is shifting from prompt-and-response to an agentic workflow where developers become coaches, not players, orchestrating AI agent systems for a 100x productivity leap. The key skill is no longer prompt engineering, but Context Engineering - providing agents with structured data, documentation, and instructions. This post provides a practical playbook to build and scale this new agentic SDLC, moving from theory to an implementable strategy for the future of software development.

AI benchmarks are fundamentally broken, putting enterprise budgets at risk. This post deconstructs the technical flaws and outlines a strategy for building internal evaluations that actually predict real-world performance.

This post contrasts the switching technologies of NVIDIA and Google's TPUs. Understanding their different approaches is key to matching modern AI workloads, which demand heavy data movement, to the optimal hardware.

It's not just about specs. This post breaks down the core trade-off between the GPU's versatile power and the TPU's hyper-efficient, specialized design for AI workloads.