diff --git a/evalharness/model/pool.py b/evalharness/model/pool.py
index cbac67b..599633a 100644
--- a/evalharness/model/pool.py
+++ b/evalharness/model/pool.py
@@ -312,7 +312,7 @@ class AdaptiveGate:
             # not enough evidence yet at this level: keep measuring.
             # need = max(MIN_OK, level): rate noise shrinks only with
             # samples proportional to the concurrency being judged
-            need_ok = max(self.MIN_OK, lvl)
+            need_ok = max(self.MIN_OK, lvl * 2)
             if self._level_ok < need_ok and dt < self.MAX_AT_LEVEL_S:
                 return
             # zero completions in MAX_AT_LEVEL_S: hang or overloaded -> hold
@@ -325,15 +325,20 @@ class AdaptiveGate:
 
             if self._mode == 'probe':
                 self.stats['probe'] += 1
-                improved = prev_rate is None or rate > prev_rate * self.GAIN_EPS
-                if improved and lvl < self.HI:
+                # continue while NOT WORSE (>= 0.9x): with heterogeneous
+                # request lengths (lbv2: 4k..2M-token docs) completion-rate
+                # noise dwarfs a 10% gain threshold, and demanding strict
+                # improvement bisected [1,2]->1 on the first plateau.
+                # Only CLEAR degradation (<0.9x) means past the knee.
+                ok = prev_rate is None or rate >= prev_rate * 0.9
+                if ok and lvl < self.HI:
                     self._bis = (lvl, min(lvl * 2, self.HI))  # remember bounds
                     self.limit = float(min(lvl * 2, self.HI))
                     self.stats['ramp_demand'] += 1
                     self._push_limit()
                     self._enter_level()
-                elif not improved:
-                    # throughput plateaued: knee is between prev_lvl and lvl
+                elif not ok:
+                    # throughput CLEARLY degraded: knee is in (prev_lvl, lvl]
                     self._mode = 'bisect'
                     self._bis = (prev_lvl or max(1, lvl // 2), lvl)
                     self._good_rate = prev_rate or rate
@@ -350,13 +355,24 @@ class AdaptiveGate:
                         self._enter_level()
                 else:
                     self._enter_level('steady')   # hit HI with gains: stay
+            elif self._mode == 'steady':
+                # capacity estimates are noisy: periodically re-probe upward
+                self._steady_ticks = getattr(self, '_steady_ticks', 0) + 1
+                if self._steady_ticks >= 12:   # ~60s at PROBE_S=5
+                    self._steady_ticks = 0
+                    self._mode = 'probe'
+                    self._prev = (lvl, rate)
+                    # try one level up, not a full double, from settled state
+                    self.limit = float(min(lvl + 1, self.HI))
+                    self._push_limit()
+                    self._enter_level()
+                    return
             elif self._mode == 'bisect':
                 lo, hi = self._bis
-                if rate > self._good_rate * self.GAIN_EPS:
-                    lo = lvl            # still improving: knee is higher
-                    self._good_rate = rate
+                if rate >= self._good_rate * 0.9:
+                    lo = lvl            # not worse here: knee is at/above
                 else:
-                    hi = lvl            # no gain: knee is lower
+                    hi = lvl            # clearly worse: knee is below
                 self._bis = (lo, hi)
                 if hi - lo <= 1:
                     self.limit = float(lo)