Tag: Automation

AI automation means using smart computer programs to do tasks automatically without human help. It saves time by handling things like answering questions or sorting information on its own.

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Production Hardening: Idempotency, Run Isolation, and Crash Safety Elena Daehnhardt · 2 Aug, 2026 LangGraph replays a node from the start every time it resumes after an interrupt, so a `finalized` flag alone cannot stop a side effect from firing twice. Here's how stable run identity, atomic file writes, and operation-level idempotency keys turn a crash into a tested recovery path instead of a corrupted report. Read more...
Connecting Codex CLI, Cursor, and Antigravity via MCP Elena Daehnhardt · 2 Aug, 2026 I was maintaining three separate integrations — one each for Codex CLI, Cursor, and Antigravity — until I moved them all behind a single shared MCP server. Here's how one LangGraph orchestrator now serves every client without duplicating approval, file-writing, or retry logic. Read more...
I Asked AI to Audit My Flask App. First, I Had to Audit the AI Elena Daehnhardt · 27 Jul, 2026 I built four reusable AI skills to audit Flask applications. Their first real run found two flaws in their own scanning instructions — and two genuine vulnerabilities in my app. Read more...
Agents, Access, and the Confused Deputy Problem Elena Daehnhardt · 20 Jun, 2026 Running a local AI is private. Giving it the ability to take actions introduces a different class of risk. This post explains prompt injection, the confused deputy problem, and the practical mitigations that hold up in 2026 — with macOS and M1 specifics where relevant. Read more...
I used Claude to generate Pinterest pins. Here is the actual API cost. Elena Daehnhardt · 28 May, 2026 I built a Python script that reads a Jekyll blog post, calls the Claude API to generate an SEO-optimised Pinterest pin title, description, and hashtags, then uploads the result to Pinterest. Before running it on all my posts I wanted to know exactly how many tokens each call uses and what it costs. The answer is surprisingly cheap — and worth understanding in detail. Read more...
Codex CLI Part 4: Advanced Operations, Troubleshooting, and Team Patterns Elena Daehnhardt · 29 Apr, 2026 Part 4 closes the Codex CLI series with advanced operational patterns: non-interactive automation, permission strategy, troubleshooting playbooks, and team-level standards for reliable adoption. Read more...
Codex CLI Part 3: Practical Workflows for Blogging and Python Development Elena Daehnhardt · 22 Apr, 2026 A practical, high-depth guide to using Codex CLI for blog editing and Python delivery: review loops, safe refactoring, debugging, and non-interactive automation with explicit guardrails. Read more...
Workflow Automation with n8n Elena Daehnhardt · 11 Aug, 2025 Manual content pipelines inevitably fail at scale. After outgrowing brittle Python cron jobs, I migrated my infrastructure to n8n—a self-hosted, node-based orchestration layer. Here is the technical breakdown of configuring databases, managing OAuth2 security, and deploying AI-driven agents. Read more...

Production Hardening: Idempotency, Run Isolation, and Crash Safety

Connecting Codex CLI, Cursor, and Antigravity via MCP

I Asked AI to Audit My Flask App. First, I Had to Audit the AI

Agents, Access, and the Confused Deputy Problem

I used Claude to generate Pinterest pins. Here is the actual API cost.

Codex CLI Part 4: Advanced Operations, Troubleshooting, and Team Patterns

Codex CLI Part 3: Practical Workflows for Blogging and Python Development

Workflow Automation with n8n