ai
Multi-Agent Systems: When Splitting Work Across Agents Helps, and When It Multiplies Failure
Most tasks run better on one well-tooled agent. Multi-agent systems pay off only for parallel work, isolated context or independent checks.
ai
Human-in-the-Loop for AI Agents: Where to Put Approvals So They Actually Catch Errors
Agent approvals catch errors only at irreversible actions, with a clear diff, at a pace reviewers can read. Where to put them, and how to tell they work.
ai
LLM Release Management: How to Ship Prompt and Model Changes Without Breaking Production
An LLM feature has four parts that change on their own. Release them as one versioned artifact behind an eval gate. The rules, tables and build order.
technology
Service Level Objectives: Setting Reliability Targets That Survive Contact With the Business
SLI, SLO, and SLA are three different things. How to pick targets users can perceive, and why the error budget policy is the only part that changes behavior.
technology
Technical Debt: How to Measure It and When Paying It Down Is Worth It
Technical debt has no principal and no fixed rate. The proxy metrics that work, why dedicated debt sprints fail, and how to frame it for a CFO.
ai
Structured Outputs: How to Make LLMs Return Data Your Systems Can Trust
Constrained decoding against a schema, not prompt-and-parse, is how to get reliable JSON from an LLM. Schema design, validation layers, and failure modes.
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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