Production on René Zander | AI Automation Consultant

What Anthropic's April 23 Postmortem Reveals About Your Agent Harness

Thu, 30 Apr 2026 08:00:00 +0000

The April 23 Claude Code postmortem dropped last week. Three bugs, two months of degraded output, one usage-limit reset for every Pro subscriber.

I read it twice. The second time I started writing notes for my own agent harness.

It is unusually candid for a company at this scale, and it reads like a checklist of failure modes any team running production AI agents will eventually hit. Worth treating as a free engineering review.

How to Choose an LLM for Production: 7 Criteria That Matter

Fri, 17 Apr 2026 07:00:00 +0200

Most teams pick an LLM for production the wrong way. They read a leaderboard, pick the top model, and wire it into an endpoint. Six weeks later they hit a rate limit during a traffic spike, or a compliance reviewer asks where EU data is processed, or the p99 latency kills a user-facing flow. Then the real selection work starts, under pressure, in production.

This guide is how to choose an LLM for production the right way, before any of that happens. I run AI agents and LLM-backed automations for DACH clients, and every production deployment I’ve shipped went through the same seven-criteria filter. The order matters. Skip one and you will find out later, usually on a weekend.

Production AI Agent Architecture: Patterns That Actually Ship

Fri, 10 Apr 2026 08:00:00 +0200

Most agent tutorials end at “the model calls tools in a loop, done.” That works for a demo. It falls apart the first time a tool 500s, a user asks something off-script, or the token bill crosses $20 on a single task. Production AI agent architecture is the set of patterns that keep that loop alive when reality hits.

I run 10 agents in production right now. Bash scripts calling claude -p, scheduled via systemd timers, reporting outcomes to Telegram. Not fancy. They ship work every day because the architecture around the loop is boring and deliberate. This guide is that playbook: the patterns, the must-haves, the anti-patterns, and the opinionated verdicts on what to use when.