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Measure posture

Know what this release did to speed and security.

Your agent writes and runs k6 load and volume tests and the security scans. TestChimp compares every result with past releases, so a slower endpoint or a new vulnerability shows up before you ship, not after.

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Security and performance in TestChimp: a k6 load test of POST /checkout regressing against release 2.14, a volume test on a 48,000-order account, and security findings new in release 2.15.

Problem

Built for the demo.Broken by real traffic.

Coding agents optimise for code that works now. They fetch every row instead of a page, query once per item, skip the index, leave a database rule open or a secret in config. On test data with ten users it all passes. Then real traffic arrives, or a customer with years of data, and the vibe-coded app that passed every functional test falls over in production.

more excessive I/O operations in AI-written pull requests than in human ones
8×
more issues per pull request when the code is AI-written
1.7×
of coding tasks where AI-generated code introduced a security flaw
45%

CodeRabbit, State of AI vs Human Code Generation (470 open-source pull requests, December 2025). Veracode, 2025 GenAI Code Security Report (80 tasks, over 100 models); its 2026 update found the average security pass rate unchanged at 56%.

Where agent shortcuts break at scale.

None of these fail a functional test. They fail when the app meets production: more users, more data, or someone looking for a way in.

  1. More users

    Work that waits on everything.

    Synchronous calls on the request path, no timeouts or caching, one connection pool shared by every request. Fine for one tester; a queue at a few hundred users.

    Caught by load tests

  2. More data

    Queries that grow with every row.

    Unpaginated lists, a query per item, filters on unindexed columns, exports built in memory. Fast on seed data; slow, then failing, for your largest customers.

    Caught by volume tests

  3. Someone looking

    Defaults that ship as they are.

    Open database rules, missing authorisation checks, secrets in code, unescaped output and outdated packages. Nothing breaks until somebody tries.

    Caught by security scans

Performance, compared with the last release.

The TestChimp skill writes performance tests in k6, scaffolded with a reporter that sends every result back to TestChimp. Results attach to the release, so you can lay any past release’s run of the same test over this one.

Load: many users at once

Ramp virtual users on a flow and watch latency as the load grows. When this release bends away from the last one, you see where, by how much, and on which endpoint.

k6 load test of POST /checkout: p95 latency for release 2.15 over release 2.14, 38% higher at 400 users.

Volume: one user, a lot of data

Seed an account the size of your largest customer and run the flows they use. An export that took 1.9 seconds last release and 4.2 now is caught here.

Volume test on a seeded account with 48,000 orders: GET /orders/export regressed from 1.9 s to 4.2 s; other endpoints are within budget.

Security findings, scoped to the release.

Create a security check in TestChimp with its scope and type, copy its command from the release checks, and run it in your coding agent. The agent runs the scanners and reports the findings back.

Four scanners, one list

Dynamic scans of the running app with OWASP ZAP, static analysis with Semgrep, dependency vulnerabilities with Trivy and leaked secrets with Gitleaks. Findings are consolidated per release, so you triage what this release introduced.

  • DAST, SAST, dependencies and secrets.
  • Findings deduplicated across runs.
  • Triaged beside UX and functional issues in the release.
Security checks for release 2.15: DAST and dependency scans report new findings, including a cookie missing SameSite and two vulnerable packages.

The same commands as functional testing.

Performance and security run through the TestChimp skill in the coding agent you already use.

Once per repo

/testchimp init perf tests

Scaffolds k6 and the TestChimp reporter, so results land in the release.

For a story, a scenario or a branch

/testchimp author perf tests

Writes performance tests for the scope you give. On a feature branch, the agent works out the impacted areas itself.

Before a release

/testchimp run perf tests

Runs the tests and reports results, ready to compare with past releases.

For each security check

/testchimp run security check <config id>

Runs the scans configured in TestChimp for that check and reports the findings against the release.

How non-functional checks usually run.

Ways of running performance and security checks compared with TestChimp
Standalone load toolsSeparate security scannersProduction monitoringTestChimp
Tests written by your coding agentNoNoNoYes
Compared with past releasesPartlyNoPartlyYes
Findings scoped to the releaseNoPartlyNoYes
Catches regressions before users doYesYesNoYes
In the same release view as functional testsNoNoNoYes

Questions about security and performance.

Why do vibe-coded apps fail in production?
Coding agents write code that passes the tests in front of them, and those tests run with little data and few users. Shortcuts such as unpaginated queries, a query per item, missing indexes, synchronous calls and open database rules only show up under real traffic or real data volumes. CodeRabbit’s analysis of 470 open-source pull requests found excessive I/O operations about 8 times more common in AI-written code. Load, volume and security checks on every release catch these problems before users do.
Is AI-generated code secure?
Often not by default. Veracode’s 2025 GenAI Code Security Report found that AI-generated code introduced a security flaw in 45% of 80 coding tasks across more than 100 models, and its 2026 update found the average security pass rate unchanged at 56%. Scanning every release with DAST, SAST, dependency and secret checks is how TestChimp keeps agent-written code honest.
Is AI-generated code slower?
Not line for line: on small, self-contained problems it is often as fast as human code. The trouble is design that only shows at scale. CodeRabbit found excessive I/O operations about 8 times more common in AI-written pull requests, the kind of pattern, such as a query per item or an unpaginated list, that is invisible on test data and slow under real load or data volumes.
Do newer or bigger models write more secure code?
Not reliably. Veracode’s 2026 update found model size made no difference to security results, and coding-specialised models scored no better than general-purpose ones. Checks on the code that actually ships matter more than the model that wrote it.
How do I load test an app built with AI coding agents?
Run /testchimp init perf tests once, then /testchimp author perf tests for a story, scenario or branch. Your agent writes k6 load and volume tests, and every run is compared with past releases, so a slower endpoint shows up with a number on it.
What is the difference between load and volume testing?
Load testing asks whether the system holds up when many users use it at once. Volume testing asks whether it holds up when one user has a lot of data. Both matter, and they find different problems.
Which tools do the tests and scans use?
Performance tests are k6 scripts with the TestChimp reporter. Security checks use OWASP ZAP for DAST, Semgrep for SAST, Trivy for dependency vulnerabilities and Gitleaks for secrets.
Do the tests live in my repo?
Yes. The k6 scripts are files in your repo like your Playwright tests, written and kept up to date by your agent.
How are regressions found?
Each result attaches to a release. Lay the same test’s run from any past release over the current one to see where latency or throughput changed.
Where do findings go?
Into the release, beside functional, UX and verification results, so the release view shows everything that stands between you and shipping.
TestChimp mascot at the desk, facing camera, dual monitors with code behind.

Ship releases that are as fast and as safe as the last one.

Three commands for performance, one for security, and every result compared with the release before.

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14 days, no credit card.