diff --git a/README.md b/README.md
index 142021ec9..c4b70d413 100644
--- a/README.md
+++ b/README.md
@@ -32,7 +32,7 @@ solver = solve(probN, NewtonRaphson(), abstol = 1e-9)
 f(u, p) = u .* u .- 2.0
 u0 = (1.0, 2.0) # brackets
 probB = IntervalNonlinearProblem(f, u0)
-sol = solve(probB, Falsi())
+sol = solve(probB, ITP())
 ```
 
 ## v1.0 Breaking Release Highlights!
diff --git a/docs/src/solvers/BracketingSolvers.md b/docs/src/solvers/BracketingSolvers.md
index f09e64cc2..d86f79b4e 100644
--- a/docs/src/solvers/BracketingSolvers.md
+++ b/docs/src/solvers/BracketingSolvers.md
@@ -7,7 +7,7 @@ Solves for ``f(t)=0`` in the problem defined by `prob` using the algorithm
 
 ## Recommended Methods
 
-`ITP()` is the recommended method for the scalar interval root-finding problems.
+`ITP()` is the recommended method for the scalar interval root-finding problems. It is particularly well-suited for cases where the function is smooth and well-behaved; and achieved superlinear convergence while retaining the optimal worst-case performance of the Bisection method. For more details, consult the detailed solver API docs. 
 `Falsi()` can have a faster convergence and is discretely differentiable, but is
 less stable than `Bisection`.
 `Ridder` is a hybrid method that uses the value of function at the midpoint of the interval to perform an exponential interpolation to the root. This gives a fast convergence with a guaranteed convergence of at most twice the number of iterations as the bisection method.