Flagship · Triple Agentic
Three AI coding agents. One task. Nobody grades their own homework.
One AI can be confidently wrong. Triple Agentic gives your task to Claude, Gemini, and GPT at once, runs every agent's tests against every other agent's code, and hands you the result with the evidence attached. You make the final call.
- 01
Same task, three sandboxes
Each agent gets its own isolated copy of your repository. None can touch the others' work or your code.
- 02
Code and tests
Each agent writes a solution and a test suite that says what "correct" means to it.
- 03
Cross-testing
Every suite runs against every solution, each on a clean copy. A solution has to pass the others' tests, not just its own.
- 04
You decide
You get the recommendation, the full test matrix, and each agent's review of the others. Nothing reaches your code without your approval.
Cross-test matrixIllustrative
$ triple run "Add rate limiting to /login: 5 per minute per IP, then 429"
| Test (written by) | A's code | B's code | C's code |
| a::sixth_attempt_gets_429 | pass | pass | pass |
| a::counter_resets_after_a_minute | pass | fail | pass |
| b::429_has_retry_after | pass | pass | fail |
| c::blocked_ip_unblocks | pass | fail | pass |
Every agent's own tests passed. Cross-testing caught a counter that never resets and a missing Retry-After header. Sample data showing the format, not a recorded run; agents are anonymized so no model is singled out.
Not claimed yet
We don't have benchmark results yet. So we're not claiming Triple Agentic catches more errors or saves more time than a single AI. The benchmark compares three agents against one model and against best-of-N from a single model, on problems with known answers. We'll publish every result, failures included.