The End of "Tooling": Re-engineering Workflows
Adding AI to existing processes fails; ROI requires embedding AI into the core workflow.
Insights & Research
The Engine Room
From Silicon to Strategy. The latest thinking from the frontlines of building AI.
Latest Publication
Governance-as-Code: Building the Agentic Command Center
Tracking agent drift, security, and access control in real-time programmatic monitoring.
Read Full ArticleStrategy & Economics
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Portfolio-Based Budgeting for AI Initiatives
Moving away from siloed project funding based on projected margin impact. Discover how to transition from project-based to portfolio-based AI funding to optimize ROI and survive the pilot phase.
The P&L Mandate: Transitioning the CAIO from Pilots to Profitability
Boards demand hard financial ROI over soft metrics like 'hours saved'. This is the framework to shift your AI strategy toward measurable margin and revenue impact.
The CAIO's First 100 Days: Beyond Pilot Purgatory
Moving from setting up the office to surviving the execution phase without failing ROI checks. A guide for the new Chief AI Officer.
AI Infrastructure
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Breaking the Bandwidth Wall: Why AI Clusters are Shifting to Ultra Ethernet
To scale past 100k GPUs, the industry is replacing proprietary InfiniBand with AI-optimized Ultra Ethernet.
Multi-Cloud GPU Arbitrage: Routing Workloads Between Hyperscalers and Neoclouds
Don't lock into one vendor. Learn how to use an abstraction layer to route training and inference workloads to the cheapest available capacity across hyperscalers and neoclouds.
Semantic Caching at Scale: Vector Embeddings for 5x Latency Reduction
Moving beyond exact-match caching for repetitive zero-shot inference workloads. Learn how to architect semantic caching to slash latency and compute costs.
Rack-Scale AI Design: The End of Component Scaling
We have hit the physical limits of what a single chip can do. The new unit of compute for AI infrastructure isn't the GPU; it's the fully integrated rack.
Agentic AI
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The A2A Protocol: Standardizing Handoffs Between Heterogeneous Agents
How the A2A standard allows multi-vendor agents to discover, negotiate, and delegate tasks safely.
Context Bloat: Implementing Progressive Discovery in Agent Memory
Using progressive discovery and smart tool-search to keep agents lean. Learn how to prevent context window overflow and infinite reasoning loops in multi-agent systems.
Agent FinOps: Architecting Economic Constraints into LLM Routing
We built autonomous agents that can think, reason, and execute. Now we need to stop them from bankrupting us. Here is how to build economic constraints directly into your LangGraph loops.
The Infinite Board Problem: Pruning State in Long-Running Reasoning Loops
How to manage the shared state size in complex reasoning loops to prevent context window overflow without losing critical history.
AI Engineering
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Model Distillation: Why a 7B Model Beats a Frontier Model
The fastest way to slash latency is right-sizing models for production classification.
KV Cache Quantization: Fitting Larger Context Windows on Single GPUs
The bottleneck for long-context agents is memory, not compute. Learn how to implement FP8 or INT8 KV caching to double your context length and survive inference at scale.
Chunked Prefill: Solving the Noisy Neighbor Problem in Inference
When a massive prompt stalls your entire inference server, you have a noisy neighbor problem. The solution requires rethinking how we process context with Chunked Prefill.
RadixAttention vs PagedAttention: The New Frontier in Context Management
A deep dive into the mechanics of SGLang's RadixAttention and why it represents a breakthrough for multi-turn agentic workflows compared to vLLM's PagedAttention.
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