diff --git a/.Rbuildignore b/.Rbuildignore
index b85d639..17bd785 100644
--- a/.Rbuildignore
+++ b/.Rbuildignore
@@ -16,4 +16,4 @@
 ^task_agent_mapping\.json$
 ^\.gitleaks\.toml$
 ^\.jules$
-^\.jules/.*
+^\.jules/.*$
diff --git a/.jules/bolt.md b/.jules/bolt.md
new file mode 100644
index 0000000..5df8872
--- /dev/null
+++ b/.jules/bolt.md
@@ -0,0 +1,3 @@
+## 2024-10-24 - [Avoid Redundant MAP Estimations in aFIPC.R]
+**Learning:** The `fscores()` function for MAP estimation is an expensive operation in `mirt`. In `R/aFIPC.R`, these were being calculated twice consecutively: once inline for `mirt::expected.test()` and once immediately after for assignment to output variables.
+**Action:** When calculating expected scores using MAP thetas, always pre-calculate the thetas and reuse the variables rather than calling `fscores()` multiple times.
diff --git a/R/aFIPC.R b/R/aFIPC.R
index ac34996..ecb5d05 100644
--- a/R/aFIPC.R
+++ b/R/aFIPC.R
@@ -1010,28 +1010,28 @@ autoFIPC <-
     #   stop('Estimation failed. Please check test quality.')
     # }
 
+    # calculate theta
+    ThetaOldform <- fscores(oldFormModel, method = 'MAP')
+    ThetaLinkedform <- fscores(LinkedModel, method = 'MAP')
+    ThetaNewform <- fscores(newFormModel, method = 'MAP')
+
     # calculate expected score
     ExpectedScoreOldform <-
       mirt::expected.test(
         x = oldFormModel,
-        Theta = fscores(oldFormModel, method = 'MAP')
+        Theta = ThetaOldform
       )
     ExpectedScoreLinkedform <-
       mirt::expected.test(
         x = LinkedModel,
-        Theta = fscores(LinkedModel, method = 'MAP')
+        Theta = ThetaLinkedform
       )
     ExpectedScoreNewform <-
       mirt::expected.test(
         x = newFormModel,
-        Theta = fscores(newFormModel, method = 'MAP')
+        Theta = ThetaNewform
       )
 
-    # calculate theta
-    ThetaOldform <- fscores(oldFormModel, method = 'MAP')
-    ThetaLinkedform <- fscores(LinkedModel, method = 'MAP')
-    ThetaNewform <- fscores(newFormModel, method = 'MAP')
-
     # save results as object
     modelReturn <- new.env()
     modelReturn$oldFormModel <- oldFormModel