n8n vs Zapier vs Make: The Enterprise AI Technology Stack Decision
Article summary
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Originally published at twarx.com - read the full interactive version there. Last Updated: August 4, 2026 Most AI technology workflows are solving the wrong problem entirely. They optimize the intelligence of individual steps while ignoring the failure surface between them: the handoffs, the retries, the state that gets dropped when a model returns malformed JSON at 2am. I have rebuilt enough of these systems to say it plainly — the model is rarely the reason a deployment collapses. AI…
1Key Takeaways
- Originally published at twarx.com - read the full interactive version there.
- Last Updated: August 4, 2026 Most AI technology workflows are solving the wrong problem entirely.
- They optimize the intelligence of individual steps while ignoring the failure surface between them: the handoffs, the retries, the state that gets dropped when a model returns malformed JSON at 2am.
- I have rebuilt enough of these systems to say it plainly — the model is rarely the reason a deployment collapses.
2AIWedia Score
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3Why it matters
Coding AI shifts how fast software ships and how much human review each change needs. DEV — ML reports that originally published at twarx.com - read the full interactive version there.
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