AI doesn't fail loudly. It fails confidently.
AI increased code throughput. It did not increase engineering judgment.
Whatever agent writes the code, Mindrealm catches what it gets confidently wrong.
75+ deterministic checks across Go, Python, TypeScript, and Rust. On Claude Code, Codex, and Gemini, Mindrealm sends findings back for the agent to fix, then reviews the change again.
A passing build does not prove the code is correct.
The code "works."
The tests pass.
The build succeeds.
The build can pass while the code gets worse.
A passing build can still hide:
- ā¢ Weakened a failing test until it passed
- ā¢ Marked the task complete with the build broken
- ā¢ Claimed output it never produced
- ā¢ Swallowed a real error instead of handling it
- ā¢ Invented an API that doesn't exist
Complete is not the same as correct.
Built for how AI writes code.
Agents fail in patterns. These aren't slogans. They're checks Mindrealm runs for the mistakes agents make confidently.
Copy-pasted, not abstracted
Near-duplicate functions: the same logic pasted in five places instead of one shared helper.
Future-proofing nobody asked for
Exported helpers and symmetrical CRUD that nothing calls, flagged before they pile up as dead weight.
Tests that test the mock
Assertions that check a mock returned what you told it to, not that the code actually works.
Assertions that can't fail
Weak checks that pass on almost any value, and flaky tests gated on sleeps and unseeded random.
Confident-but-wrong error handling
Errors checked then ignored, swallowed in empty catches, or shadowed by an inner declaration.
Performance traps at scale
N+1 I/O in loops, O(nĀ²) string building, and maps used as caches that grow until they OOM.
Your CI is green. Your confidence is false.
Ship at AI speed. Trust what merges.
Keep the velocity your agents give you without treating a green build as proof. Mindrealm checks the code before it merges.
Review. Fix. Verify.
Generation is fast. Verification is the missing half. On Claude Code, Codex, and Gemini, Mindrealm runs when the agent finishes so it sees the findings before you do.
Your agent writes the code
Claude Code, Codex, Copilot, or another agent writes the change. Mindrealm reviews the output regardless of which agent produced it.
Mindrealm reviews it
After Claude Code, Codex, or Gemini finishes, on every pull request, or on demand from your terminal. The same code produces the same findings.
The agent fixes the findings
On Claude Code, Codex, and Gemini, the agent fixes what it can. Mindrealm checks the change again, and the loop closes when no findings remain.
Automated senior-level review.
Every review finding points to the exact line and explains why:
Architecture
Coupling and cohesion, dead and unreachable code, near-duplicate functions, scattered configuration, oversized public APIs.
Reliability
Unhandled and swallowed errors, errors overwritten before they are checked, null dereference after an error, resource leaks, missing timeouts.
Testing
Tests with no assertions, assertions that pass on any value, flaky tests, mock abuse, test pollution, missing tests.
Performance
N+1 I/O in loops, O(nĀ²) string building, unbounded collections, cache growth with no eviction, nested scans.
Security
Hardcoded secrets and credentials, SQL and command injection, untrusted input that reaches dangerous calls across files.
Concurrency
Detached and unmonitored tasks, unawaited async calls, stale closure capture, blocking calls in async paths.
Structure
Cyclomatic complexity, deep nesting, long functions, long parameter lists, oversized files, dead branches.
Hygiene
Dead functions, unused exports, duplicate definitions, magic numbers and strings, commented-out code, ignored warnings with no reason given.
Toolchain gates
Your linters and type checks run on every review and merge into one report: go vet, golangci-lint, ruff, eslint, tsc, cargo clippy.
One bar. Four languages.
Mindrealm runs the same checks and toolchain gates across Go, Python, TypeScript, and Rust, so the review stays consistent when your agent changes languages.
Same depth on architecture, concurrency, reliability, security, and performance, no matter the language.
One reviewer, three surfaces. Pick any or all of them.
Reviewed before you merge.
Once approved for early access, install the GitHub App for your organization, invite your team, and open a pull request. Mindrealm posts a check run with every finding annotated on the exact line. No CI config to write.
A swallowed error, caught inline
Findings get fixed by your agent before a PR is opened.
Wire Mindrealm into Claude Code, Codex, or Gemini. When your agent finishes, Mindrealm reviews the output and feeds the findings back. The agent fixes them, then Mindrealm checks again. Or run a review yourself from the terminal, on the whole repo or just your changes.
Five findings, caught before the PR
A hanging test, fixed with a timeout
Five fixes, verification passed
The convictions behind every review.
Determinism grounds judgment.
Same code, same findings, every run and every reviewer. A steady base to reason from, not a hallucination or a guess that drifts.
Done is not the same as correct.
Agents report success. Mindrealm checks whether it's true.
You decide what's worth fixing.
Mindrealm flags it; you set the bar. Tune thresholds or mute a check you disagree with. Every call stays on record.
Built for engineers who don't trust "it passed CI".
This is for:
- āDevelopers who'd rather catch it in review than in prod
- āSolo founders without a staff engineer safety net
- āTeams scaling AI-assisted development responsibly
- āEngineers who don't trust green checkmarks
- āTech leads tired of policing agent behavior
This is not for:
- āTeams that want a rubber stamp, not a review
- āTeams comfortable with silent regressions
- āTeams that trust AI output by default
- āAnyone who treats a passing build as proof
- āAnyone who calls tests "optional"
Built from failure, not theory.
I documented more than 6,000 failures from AI agents writing real code: broken architecture, duplicated logic, performance and security holes, and the same mistakes on repeat.
The same failure patterns kept showing up behind confident claims that the work was complete.
The solution wasn't better prompts or agent rules.
The solution was enforcement.
Bryce, Founder
AI made your team faster.
I'll help make them better.
When agent-written code outpaces review, I find what gets missed, build the guardrails that catch it, and coach your team to keep the bar high.
See consulting$30 per seat. That's the whole price.
7-day free trial. No usage fees, no surprises.
Early adopters get direct founder access and a say in what gets built.
See full pricingCatch what your agent missed, before it merges.