You have two IT people. Maybe three, if you count the contractor who’s been with you so long they feel like staff. Between them, they handle helpdesk tickets, keep the servers running, maintain the platform, manage vendors, and occasionally get to work on actual improvements.
Your business does a few million a year. Real revenue. Real customers. A platform that, for all its quirks, keeps the money flowing.
Now everyone’s talking about “digital transformation” and “AI-first” and “DevOps maturity.” Enterprise consultants want to sell you six-figure transformation projects. The tech press makes it sound like you need a 50-person engineering team to be taken seriously.
Here’s the truth: you can get enterprise-grade practices without enterprise bloat. You just need to focus on the right things.
The Small Team Reality
Let’s be honest about constraints. Your team:
- Wears multiple hats constantly
- Can’t dedicate six months to infrastructure projects
- Has limited budget for new tools
- Doesn’t have time to become experts in Kubernetes or service meshes or whatever the latest thing is
- Needs solutions that work, not science projects
These aren’t weaknesses—they’re constraints that should shape your strategy. You need high-leverage moves that deliver real value without requiring more people or more time than you have.
High-Leverage Move #1: Infrastructure as Code (Lite)
Don’t let the jargon scare you. Infrastructure as code just means: “write down what your servers look like so you can recreate them.”
Right now, if your main server died, how long would it take to rebuild? Do you even know everything that’s installed on it? Every configuration change made over the years?
Start simple:
- Document your current setup in a README file
- Write a script that configures a fresh server to match
- Test it by actually spinning up a new server and running the script
You don’t need Terraform or CloudFormation (though they’re great if you want them). A bash script that installs dependencies and copies configuration files is infrastructure as code. It’s better than what most small teams have.
Estimated time: 2-3 days of focused work. Value: priceless when something breaks.
High-Leverage Move #2: Basic CI/CD
Continuous integration and continuous deployment sounds fancy. Here’s what it actually means for a small team:
- When someone pushes code, it automatically gets tested
- When tests pass, it automatically deploys (or becomes one-click deployable)
Most cloud providers include basic CI/CD tools. GitHub Actions is free for small teams. GitLab has built-in CI. AWS CodePipeline isn’t complicated.
Start with:
- A simple pipeline that runs your tests on every push
- A deployment script that’s triggered by a button (or automatically on the main branch)
- A rollback procedure that’s documented and tested
Estimated time: 1 week to set up. Value: every deployment becomes safer and faster.
High-Leverage Move #3: Critical Path Testing
You don’t need 80% test coverage. You need 100% coverage of the things that matter most.
Identify your top 5 revenue-critical workflows. For most businesses, this might be:
- User signup/login
- Core transaction (purchase, order, booking, whatever you sell)
- Payment processing
- Main report or dashboard customers rely on
- Key integration (if you have one)
Write automated end-to-end tests for these five workflows. Run them before every deployment. If they pass, you can deploy with confidence. If they fail, you caught the problem before customers did.
Estimated time: 2-3 weeks for initial tests. Value: dramatically reduced deployment risk.
High-Leverage Move #4: Simple Monitoring
You don’t need a fancy observability platform. You need to know when things are broken.
Start with:
- Uptime monitoring: Services like UptimeRobot or Pingdom will check if your site is up and alert you if it’s not. Free or nearly free.
- Error tracking: Tools like Sentry or Rollbar capture errors with context so you know what went wrong. Cheap for small teams.
- Basic metrics: Track response times, error rates, and database query counts. Even basic logging with alerts on error volume helps.
The goal isn’t comprehensive observability. The goal is knowing about problems before customers report them.
Estimated time: 1-2 days. Value: problems get fixed faster, customers trust you more.
Where AI Actually Helps Small Teams
AI tools can genuinely help resource-constrained teams—if you use them right:
- Generate boilerplate code: Instead of writing repetitive CRUD operations from scratch, let AI generate the first draft.
- Write tests: Describe what a function should do and have AI generate test cases. Review them, but let AI do the tedious part.
- Refactor legacy code: “Explain what this 500-line function does, then break it into smaller functions” is a reasonable AI task.
- Write documentation: AI can generate decent first-draft documentation that humans then refine.
- Debug weird issues: Paste an error message and get suggestions for what might be wrong.
But remember: AI generates plausible-looking code, not necessarily correct code. Humans still own the architecture decisions. Humans still need to review and test everything. AI is a force multiplier for your small team, not a replacement for thinking.
The 6-Month Roadmap
If I were an AI-first CTO parachuting into your 2-person IT team with a directive to “modernize without disrupting the business,” here’s roughly what I’d do:
Month 1: Document current state. Write down how everything works. Identify the scariest single points of failure.
Month 2: Infrastructure as code for your critical systems. Make sure you can rebuild if something dies.
Month 3: Basic CI/CD pipeline. Automate builds and tests. Make deployments one-click.
Month 4: Critical path tests. Cover your top 5 revenue-critical workflows.
Month 5: Monitoring and alerting. Know when things break before customers tell you.
Month 6: First modernization project. Pick one slice of your system and improve it using your new foundation.
This isn’t a transformation. It’s a series of practical improvements that compound over time. At the end of six months, you have a significantly more resilient system, a team that can ship with confidence, and a foundation for continued improvement.
Key Takeaways
- Enterprise practices don’t require enterprise budgets. Focus on high-leverage moves.
- Infrastructure as code can start with a bash script. The goal is reproducibility.
- Basic CI/CD makes every deployment safer. It’s not as complicated as it sounds.
- Test your critical paths religiously. 100% coverage of 5 workflows beats 20% coverage of everything.
- AI helps small teams move faster—for generating code, tests, and documentation—but humans own the architecture and quality.
Questions to Ask Your Team
- If our main server died right now, how long would it take to rebuild? Do we have documentation?
- What are our top 5 revenue-critical workflows? Do we have any automated tests for them?
- What’s one thing we could do this month that would make next month significantly easier?
