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The AI Vendor Evaluation Framework: How to Score AI Products Before You Buy
A six-dimension scoring framework for evaluating AI vendors, with weights, pass/fail gate questions, and a matrix a buyer can apply in a live meeting.
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LLM Observability: How to Monitor AI Systems in Production
Why classic APM misses LLM failures, the four signal layers of LLM observability, what to alert on, and how production traces feed the evaluation loop.
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Evals Are the Moat: Why AI Products Defend on Evaluation, Not Models
The durable moat in applied AI is not the model. It is the eval suite: the one asset competitors cannot rent, and the one due diligence should price.
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The AI Agent Readiness Framework: A Maturity Model for Enterprise Deployment
A five-level maturity model for enterprise AI agent readiness, with deterministic entry gates and a self-assessment matrix executives can score in minutes.
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Model Distillation: How Enterprises Get Frontier Quality at Small-Model Cost
Model distillation trains a small student on a frontier teacher's outputs. When it wins, when it fails, the provider-terms question, and the break-even math.
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Context Engineering: The Discipline That Replaced Prompt Engineering
Prompting is a commoditized layer now. The real leverage moved to context engineering: assembling the right information into the window at the right time.
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The Enterprise AI Stack: A Reference Architecture for Production AI
A practitioner reference architecture for production AI: the eight layers of the enterprise AI stack and a deterministic way to choose at each one.
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AI Guardrails: How to Keep LLM Features Safe in Production
Guardrails are the control layer between users, your model, and your systems. What they catch, where they sit in the request path, and how to build them.
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Frontier Model Lock-In: The Hidden Switching Costs of Betting on One AI Provider
Model lock-in is the new cloud lock-in. Here is where switching cost actually accumulates, how to measure your exit price, and how to keep leverage.
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How to Evaluate LLM Outputs: Building an Evaluation Harness That Catches Real Failures
Most teams ship LLM features with no real evals, then find failures in production. A practical framework for an evaluation harness that scales.
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AI Coding Assistants Hit the Productivity Wall: What the Data Actually Shows
AI coding assistants raise output, but net productivity depends on task type and codebase age. Where they help, where they add cost, and what to measure.
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Small Language Models in the Enterprise: When Smaller Beats Bigger
Frontier models do not win every task. A 2026 framework for when small and mid-sized models beat them on cost, latency, privacy, and accuracy.
What We Cover
Deep analysis across the systems, strategies, and economics that shape modern technology.
AI & Intelligent Systems
LLMs, AI strategy, and intelligent automation
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Cloud platforms, APIs, and system design
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Payment rails, settlement, and regulated infrastructure
Strategy & Economics
Build vs buy, cost curves, and competitive dynamics
Risk & Regulation
Compliance, governance, and regulatory strategy
Product & Decision Frameworks
Frameworks for product decisions and roadmaps
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