Top 5 CI Anti-Patterns That Are Slowing You Down

Your CI pipeline is supposed to help you move faster and ship with confidence.

But for many teams, CI has become a bottleneck instead of a launchpad—bloated with scripts, flaky tests, or noisy alerts. Instead of speeding you up, it saps engineering time and trust.

Let’s break the cycle.

In this post, I’ll cover the Top 5 CI anti-patterns I’ve seen over the years—across scrappy startups and regulated enterprises alike—and what to do instead.

1. “Test Everything on Every Commit” Syndrome

The Anti-Pattern:
Every time a dev pushes code, your pipeline runs every test—unit, integration, end-to-end, smoke, regression—across every environment.

It sounds safe, but it’s a performance and signal disaster.

• Your pipeline becomes slow and expensive
• Devs ignore results because they’re buried in noise
• You're running tests that aren't even impacted by the change

The Fix:
Use test impact analysis, tag filtering, or path-based triggering.

• Only run E2E tests when relevant code paths change
• Run smoke tests first, then conditionally expand
• Use monorepo-aware CI jobs that target affected areas

👉 Example (GitHub Actions):

.yml if: contains(github.event.head_commit.message, '[e2e]')

2. Flaky Test Roulette

The Anti-Pattern:
Flaky tests aren’t managed—they’re ignored, commented out, or just rerun endlessly in hopes they’ll pass. “Green is green,” right?

Wrong.

• Flaky tests erode trust in the pipeline
• Devs start ignoring all failures, not just the flakes
• Root causes pile up and tech debt grows quietly

The Fix:
Build a flake triage system, not a culture of silence.

• Auto-tag flaky tests with retry metadata
• Log and track flake frequency over time
• Make fixing flakes a sprint-level priority
• Don’t confuse “rerun and pass” with “fixed”

👉 Example: Playwright's built-in retries config + trace recording is your friend.

3. No Signal in the Noise

The Anti-Pattern:
Your CI notifies everyone… about everything.

• Every job posts to Slack
• Every test result floods the dashboard
• Build failed? Good luck parsing logs

Result? Alert fatigue.
CI becomes background noise—until something breaks in prod.

The Fix:
CI should surface just the right amount of signal.

• Only notify on test failures or regressions
• Use Slack summaries, not firehoses
• Include direct links to traces, logs, or dashboards
• Red = actionable; green = silence

👉 Bonus Tip: Set alerts to go to owners of broken components—not the whole team.

4. Pipeline Logic Hidden in the UI

The Anti-Pattern:
The CI pipeline was built in a rush using drag-and-drop GUI tools. No one knows exactly how it works anymore—and any change risks breaking prod.

• No version control
• No code review
• No reproducibility between dev and CI

The Fix:
Your CI config should live in your repo, like everything else.

• Use YAML (GitHub Actions, CircleCI, GitLab CI)
• Split into modular, reusable jobs and workflows
• Peer review all pipeline changes
• Track history like you would code

👉 Treat CI config as infrastructure-as-code, not click-ops.

5. No Feedback on CI Health

The Anti-Pattern:
You’ve built a big, beautiful pipeline—but you’re flying blind.

• How often are builds failing?
• What’s your average build time?
• Which tests flake the most?
• How long does it take from commit → deploy?

You can’t improve what you can’t see.

The Fix:
Add CI metrics and observability.

• Track failure rates, build duration, flake %
• Use dashboards (Grafana, DataDog, GitHub Insights)
• Set goals for test suite speed and reliability
• Alert when thresholds are crossed

👉 Start simple: a weekly Slack report of CI pass/fail %, top slow tests, and mean time to green.

What Great CI Looks Like

Let’s flip the script. A healthy CI pipeline should be:

Want Help Fixing Yours?

I’ve helped teams:

• Refactor monolithic pipelines into modular workflows
• Slash build times by 60%
• Kill test flake by implementing smart retries + observability
• Align CI to actual risk instead of just running everything
• Turn CI from a black box into a strategic asset

Your CI should build trust—not tech debt.

Coming Next in This Series:

• “CI Metrics That Matter”
• “How to Debug a Failing Pipeline”
• “Secrets Management for CI Done Right”
• “How to Integrate Playwright + GitHub Actions Like a Pro”
• “Test Smarter: Path Filtering & Conditional Execution in CI”