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Reading Time: 14 minutesMake migration for agencies usually starts after automation stops behaving like infrastructure and starts behaving like operational debt. It happened to me on a Tuesday. A client’s lead-routing Zap silently dropped 14 inbound demo requests over a weekend because a Typeform field got renamed upstream. The Zap “ran successfully” 14 times. I rebuilt that flow […]

Reading Time: 14 minutesEcommerce automation usually starts as a convenience layer. A few order notifications. Inventory sync between platforms. Cart recovery triggers. Refund alerts. Then operational volume changes the nature of the system. I had a Shopify→Airtable→Klaviyo setup that ran fine for a client at 500 monthly orders. At 14,000 orders during their Black Friday window, the Airtable

Reading Time: 14 minutesSaaS teams usually do not think seriously about migration until automation behavior starts becoming operationally unpredictable. At small scale, fragmented workflows are manageable. A few Zapier zaps, webhook chains, internal scripts, and patched integrations can survive for months. The problem appears once workflow dependency starts compounding across billing systems, CRMs, support tools, product analytics, onboarding

Reading Time: 11 minutesMake automation profitability starts looking very different once you move past a handful of stable scenarios. My first 8 scenarios felt like free money — a webhook here, a Google Sheets append there, a Slack notification on top. Then I crossed 30 active scenarios across three client accounts and the math changed. The problem isn’t

Reading Time: 16 minutesMake automation SaaS case study discussions usually focus on speed, integrations, or “time saved.” That misses the real operational reason teams adopt automation in the first place. I’ve managed 50+ active Make scenarios across multiple client accounts, and the breaking point shows up the same way every time: SaaS operations become structurally fragmented. Lead routing

Reading Time: 12 minutesMake automation api support starts looking very different once workflows stop being simple app-to-app automations and become operational infrastructure. That shift happened to me on a client account that started with 4 scenarios and ended up with 38 — webhook triggers became multi-step API chains, retry logic got layered in, and we had Stripe, HubSpot,

Reading Time: 7 minutesQuick answer — how reliable is webhook support in Make (automation platform)? Webhook handling in Make looks reliable at first — until you actually run it in production. I learned this managing webhooks for a SaaS integration client. I built a lead routing system that received webhooks from their landing page, mapped the data, routed

Reading Time: 10 minutesQuick answer — how serious are data limits in Make (automation platform)? Data limits in Make don’t behave like a visible ceiling. They behave like pressure. I learned this the hard way. I had a scenario syncing 8,000 Shopify orders daily into a client’s warehouse database. For three weeks, it ran green in the execution

Reading Time: 10 minutesWhy startups hit automation limits earlier than expected Most startups don’t plan for automation failure. They assume manual ops + lightweight tools will stretch longer than they actually do. In practice, the breaking point showed up quietly for this team: I realized the core issue wasn’t “we need automation.” It was:manual coordination was failing before

Reading Time: 5 minutesQuick answer — when Make is actually advantageous The real value behind make automation advantages only shows up when workflows stop being simple. Strong advantage appears when No real advantage when 👉 This is the key distinction:Make is not “better” by default, as a Make vs Pabbly Connect comparison reveals that for basic tasks, simpler tools often