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Exit 0 Is Not Success for an Agent Job
OpenAI's agent hacked Hugging Face, ran for days, and went unnoticed for a week. For anyone running scheduled agents the lesson is duller than the security story: a run where half the sources failed exits 0, writes a file the same size, and looks identical to a good one. Two cheap fixes from a cron job I actually run: make the agent report its own coverage in the artifact a human already reads, then let deterministic code decide whether it ships.
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Capacity Planning for Agents: Measure Yield, Not Tokens
Goldman says 24x token growth by 2030. Others say 240x once you count parallel agents. Both are demand forecasts you can't spend against. Take a curation pipeline that reports keeping 12 items from 37 swept: follow the funnel to the end and 641 candidates become 202 published items, 5 things worth acting on, and 3 anyone actually did. The metric that matters is cost per accepted change, and it sits on the wrong side of every agent's telemetry boundary.
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Agent Memory Wants a Wiki, Not a Vector Store
LangChain is reframing agent memory as a hyperlinked wiki, and a logging study found Claude Code ships ~33k tokens of overhead before your prompt even arrives. I've been running memory as a citation-linked markdown wiki for months, no embeddings anywhere in the pipeline. Here's what the setup looks like and where it beats top-k retrieval.
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Agent Sprawl Is an Identity Problem, Not a Dashboard Problem
Google's second State of AI Infrastructure report says 83% of orgs need to upgrade their infrastructure for agents. The number that actually matters is that nobody can see what their agents can touch — and a governance dashboard sitting on top of a wide-open credential is decoration. The fix is scoping, not monitoring.
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The Sandbox Problem for AI Agents: Lambda MicroVMs and Where Untrusted Code Should Run
An agent writes code you never reviewed and then runs it. The interesting question isn't the prompt — it's the blast radius. Lambda MicroVMs give each session a Firecracker VM that resumes from a snapshot in under a second, including a pattern where Anthropic runs the agent loop and you run the tool calls.
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Choosing an AI Agent Pattern: A Decision Guide for Enterprise Teams
Most teams reach for multi-agent orchestration too early. Here's how to pick the simplest pattern that does the job — from a single direct model call up to a manager-and-workers system.
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Graduated Trust for Production AI Agents: Parameterize Permissions by Phase, Not Environment
Stop promoting AI agents across dev, staging and prod. Bind their permissions to the evidence they've earned — not to a hostname.
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Maintainability in the Face of API Complexity
The what, why, and how of API gateways.
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Predicting Heart Disease from the UCI Dataset
An end-to-end ML walk-through — wrangling four UCI cardiology datasets, exploring what actually moves the diagnosis, and pitting logistic regression against an SVM that lands ~85% cross-validated accuracy.
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Exploring Modern iOS Architectures
MVC, MVVM, MVP and VIPER — the same TMDb movie app built four ways, compared on orthogonality, ease of use, and testability.
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