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  3. Build-versus-Buy Analyzer
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intermediate
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v1.0.0

Build-versus-Buy Analyzer

Stop debating build vs. buy in Slack. Run a structured decision framework that weights cost, speed, maintenance, and risk for any operator problem.

Full prompt

You are a pragmatic SaaS operator advisor. Evaluate this operator need against three strategies: build (custom code), buy (third-party tool), and assemble (no-code/low-code automation).

Operator need: {{OPERATOR_NEED}}
Current tech stack: {{TECH_STACK}}
Team size and skill: {{TEAM_PROFILE}}
Monthly volume or frequency: {{VOLUME_OR_FREQUENCY}}
Acceptable implementation window: {{TIMELINE_CONSTRAINT}}

For each option, provide:
1. **Upfront cost** (labor, software, setup)
2. **Monthly/annual ongoing cost** (maintenance, licenses, support)
3. **Time to first working version** (weeks)
4. **Maintenance burden** (hours/month, skill required)
5. **Failure mode** (what breaks, how often, impact)
6. **Lock-in risk** (switching cost if you change your mind)
7. **Scalability ceiling** (where this approach breaks)

Then rank them 1–3 with a single recommendation and the one reason it wins. Flag any deal-breakers.

How to use

Fill in the five {{placeholders}} with real numbers and constraints from your business. Don't estimate—ask your team or pull from your last similar project. Run this when you're stuck between options, not when you've already decided. Use the output to kill a bad idea fast or validate a hunch with numbers.

Example input

Operator need: Sync customer usage data from our product database to Salesforce daily, with error alerts and manual override capability.
Current tech stack: Node.js backend, Postgres, Salesforce API access, no iPaaS currently.
Team size and skill: 2 backend engineers, 1 DevOps, no dedicated integration specialist.
Monthly volume or frequency: 15,000 customer records, one sync per day, 50–100 manual corrections per month.
Acceptable implementation window: 4 weeks.

Example output

| Option | Upfront | Monthly | Time to Live | Maintenance | Failure Mode | Recommendation |
|--------|---------|---------|--------------|-------------|--------------|----------------|
| **Build** | $8k (labor) | $2k (1 eng, 20%) | 3 weeks | High: monitoring, retry logic, schema changes | Silent sync failures, data drift, dependency hell | ⚠️ Avoid |
| **Buy** (e.g., Zapier, Workato) | $500 | $800–2k | 1 week | Low: config only | Rate limits, complex logic gaps, vendor lock-in | ✅ Recommended |
| **Assemble** (Zapier + custom webhook) | $2k | $500 | 2 weeks | Medium: webhook maintenance, error handling | Webhook timeouts, partial failures, manual retries | 🟡 Second choice |

**Recommendation: Buy (Zapier or Workato).** Wins because: 4-week window is tight, your team has no integration specialist, and daily sync is low-complexity. Assemble is close second if you need more control over error handling. Build only if Zapier's logic limits become a blocker in 6+ months—revisit then.

Customization tips

  • Add a 'compliance or security constraint' row if you're in healthcare, finance, or regulated verticals. This often kills the buy option immediately.
  • Weight 'time to live' 3x heavier if you're in a growth phase or post-funding. Speed beats perfection.
  • Include 'team context switching cost' in maintenance burden. One engineer on-call for a custom integration is expensive even if the code is simple.
  • If your volume is seasonal or unpredictable, add a 'cost at 10x scale' row. No-code tools often hit limits or pricing cliffs.
  • Run this quarterly, not once. Your answer changes as your team grows, your stack matures, and new tools emerge.