I've recalculated your problem using Pari/GP up to tetration-"height" $h=50$ (update:$h=1.000.000$).
The used internal precision was 200 dec digits. It needed 2 secs to compute the list of first 50 entries. (The error using the found $b$ is less than 1e-180).
Here is an excerpt of the solutions for your problem $\;^hb = b^h $ (or: $ \;^{h-1}b = h$ or: $\;^{h-2}b\cdot \log(b) = \log(h)$):
h b
-+----------------------
2 2
3 1.825455022924830
4 1.722191912772396
5 1.655390902316565
6 1.609627746636388
7 1.576964928603568
8 1.552901631749337
9 1.534710270835191
10 1.520655935607996
11 1.509593123816016
12 1.500742202664287
13 1.493558789695041
14 1.487654237606995
15 1.482745596652516
... ...
48 1.448984047079777
49 1.448814814881550
50 1.448655327023237
... ...
199 1.444929953048032
200 1.444927354272319
... ...
499 1.444709831304874
500 1.444709663947240
... ...
1000 1.444678333141238
... ...
10000 1.444667965901445
... ...
100000 1.444667862058820
1000000 1.444667861020257
... ...
... ...
e^1/e 1.444667861009766
To illustrate the weirdness of that approximations, here we see the base $b=b_{100}$ as found for tetration-height $h=100$ and $h=1000$:
Example 1 ($b_{100} \approx 1.445692829534854 $):
$$ \small \begin{array} {llll}
a_1&=\;^{100} b_{100} &\approx& 1.017659983991973 E16 \\
a_2&={b_{100}}^{100} & \approx &1.017659983991973 E16 \\
a_1-a_2 & & &= 5.389496515861541 E-190
\end{array}$$
Computations done with $200$ dec digits precision
or even more:
Example 2 ($b_{1000} \approx 1.444678333141238$):
$$ \small \begin{array} {llll}
a_1&=\;^{1000} b_{1000} &\approx& 5.904177641015545 E159 \\
a_2&={b_{1000}}^{1000} & \approx &5.904177641015545 E159 \\
a_1-a_2 & & &= -2.113731367714944 E-639
\end{array}$$
Computations done with $800$ dec digits precision
The program in Pari/GP is (for the first 50 or so entries; for isolated values of heights of $h=1000$ or $h=1.000.000$ one needs a more sophisticated procedure to avoid numerical overflows):
default(realprecision,200) \\ this is my default
\ procedure for iterated exponentiation for heights h
tetr(b,h)=my(a=b);for(k=2,h,a=b^a);return(a)
\ actually computing...
vb=vectorv(50); vb[1]=1; vb[2]=2; \ this vector gets the set of solutions
\\ compute the solutions for heights 3 to 50:
for(h=3,50, vb[h]=solve(b=vb[h-1],1.4,tetr(b,h-2)*log(b)-log(h)))
\ printout
printp(Mat(vb))
update: Here is a table for further use, say, interpolations or to find some better estimation formula for $b$ depending on $h$ than that of simply using the guessed constant $c \approx 3.23...$ (see earlier comment) as given for $w_2$. The shown guess is already good: it allows to really approximate $b$ even for high $h$ in more reasonable computing time and enabled me to get an estimate for $h=1.000.000$:
Table 2:
$$\small \begin{array} {r|r}
h & b & w_1=1/(b-\lambda) & w_2=w_1^{0.5} \cdot c \approx h\\ \hline
10 & 1.520655935607996 & 13.15995970798423 & 11.74997695258401 \\
20 & 1.467343859391106 & 44.09949159384668 & 21.50931235098078 \\
50 & 1.448655327023237 & 250.7858365743097 & 51.29337051500824 \\
100 & 1.445692829534854 & 975.6397152922338 & 101.1706337147851 \\
200 & 1.444927354272319 & 3853.664600623257 & 201.0697286191011 \\
500 & 1.444709663947240 & 23921.76388643725 & 500.9637885955461 \\
1000 & 1.444678333141238 & 95491.54368949162 & 1000.903463303749 \\
2000 & 1.444670481514372 & 381605.8929592410 & 2000.862622116834 \\
5000 & 1.444668280509221 & 2383793.325683243 & 5000.852378528801 \\
10000 & 1.444667965901445 & 9533644.761419189 & 10000.90306047686 \\
20000 & 1.444667887234663 & 38131704.16346160 & 20001.05216061220 \\
50000 & 1.444667865205928 & 238313029.9051765 & 50001.56863347198 \\
100000 & 1.444667862058820 & 953239447.1432710 & 100002.4725468315 \\
200000 & 1.444667861272031 & 3812933641.379400 & 200004.3117840303 \\
500000 & 1.444667861051729 & 23830749177.08709 & 500009.8763919837 \\
1000000 & 1.444667861020257 & 95322887666.87609 & 1000019.180814657
\end{array}$$