diff --git a/vision/samples/detect.js b/vision/samples/detect.js
index 398c040d95..e636d5d9fd 100644
--- a/vision/samples/detect.js
+++ b/vision/samples/detect.js
@@ -821,7 +821,7 @@ function detectPdfText(bucketName, fileName) {
       return operation.promise();
     })
     .then(filesResponse => {
-      let destinationUri =
+      const destinationUri =
         filesResponse[0].responses[0].outputConfig.gcsDestination.uri;
       console.log('Json saved to: ' + destinationUri);
     })
diff --git a/vision/samples/faceDetection.js b/vision/samples/faceDetection.js
index d9c75e15c8..45921271bd 100644
--- a/vision/samples/faceDetection.js
+++ b/vision/samples/faceDetection.js
@@ -20,13 +20,13 @@
 // specified by the GOOGLE_APPLICATION_CREDENTIALS environment variable and use
 // the project specified by the GCLOUD_PROJECT environment variable. See
 // https://googlecloudplatform.github.io/gcloud-node/#/docs/google-cloud/latest/guides/authentication
-let vision = require('@google-cloud/vision');
+const vision = require('@google-cloud/vision');
 // [END vision_face_detection_tutorial_imports]
 // [START vision_face_detection_tutorial_client]
 // Creates a client
-let client = new vision.ImageAnnotatorClient();
+const client = new vision.ImageAnnotatorClient();
 
-let fs = require('fs');
+const fs = require('fs');
 // [END vision_face_detection_tutorial_client]
 
 /**
@@ -40,7 +40,7 @@ function detectFaces(inputFile, callback) {
     .faceDetection(request)
     .then(results => {
       const faces = results[0].faceAnnotations;
-      let numFaces = faces.length;
+      const numFaces = faces.length;
       console.log('Found ' + numFaces + (numFaces === 1 ? ' face' : ' faces'));
       callback(null, faces);
     })
@@ -61,12 +61,12 @@ function highlightFaces(inputFile, faces, outputFile, Canvas, callback) {
       return callback(err);
     }
 
-    let Image = Canvas.Image;
+    const Image = Canvas.Image;
     // Open the original image into a canvas
-    let img = new Image();
+    const img = new Image();
     img.src = image;
-    let canvas = new Canvas(img.width, img.height);
-    let context = canvas.getContext('2d');
+    const canvas = new Canvas(img.width, img.height);
+    const context = canvas.getContext('2d');
     context.drawImage(img, 0, 0, img.width, img.height);
 
     // Now draw boxes around all the faces
@@ -90,8 +90,8 @@ function highlightFaces(inputFile, faces, outputFile, Canvas, callback) {
 
     // Write the result to a file
     console.log('Writing to file ' + outputFile);
-    let writeStream = fs.createWriteStream(outputFile);
-    let pngStream = canvas.pngStream();
+    const writeStream = fs.createWriteStream(outputFile);
+    const pngStream = canvas.pngStream();
 
     pngStream.on('data', chunk => {
       writeStream.write(chunk);
@@ -131,7 +131,7 @@ if (module === require.main) {
     // eslint-disable-next-line no-process-exit
     process.exit(1);
   }
-  let inputFile = process.argv[2];
-  let outputFile = process.argv[3];
+  const inputFile = process.argv[2];
+  const outputFile = process.argv[3];
   exports.main(inputFile, outputFile, require('canvas'), console.log);
 }
diff --git a/vision/samples/productSearch/importProductSets.v1p3beta1.js b/vision/samples/productSearch/importProductSets.v1p3beta1.js
index 24b057610f..12b58bf0a5 100644
--- a/vision/samples/productSearch/importProductSets.v1p3beta1.js
+++ b/vision/samples/productSearch/importProductSets.v1p3beta1.js
@@ -53,7 +53,7 @@ function importProductSets(projectId, location, gcsUri) {
       console.log('Processing done.');
       console.log('Results of the processing:');
 
-      for (let i in responses[0].statuses) {
+      for (const i in responses[0].statuses) {
         console.log(
           'Status of processing ',
           i,
diff --git a/vision/samples/system-test/faceDetection.test.js b/vision/samples/system-test/faceDetection.test.js
index d9c1ba3cb7..811e7f620b 100644
--- a/vision/samples/system-test/faceDetection.test.js
+++ b/vision/samples/system-test/faceDetection.test.js
@@ -59,7 +59,7 @@ test.after.always(tools.restoreConsole);
 
 test.cb(`should detect faces`, t => {
   let done = false;
-  let timeout = setTimeout(() => {
+  const timeout = setTimeout(() => {
     if (!done) {
       console.warn('Face detection timed out!');
       t.end();
diff --git a/vision/samples/textDetection.js b/vision/samples/textDetection.js
index f46e81877c..18dfffcc00 100644
--- a/vision/samples/textDetection.js
+++ b/vision/samples/textDetection.js
@@ -15,27 +15,27 @@
 
 'use strict';
 
-let async = require('async');
-let fs = require('fs');
-let path = require('path');
+const async = require('async');
+const fs = require('fs');
+const path = require('path');
 
 // By default, the client will authenticate using the service account file
 // specified by the GOOGLE_APPLICATION_CREDENTIALS environment variable and use
 // the project specified by the GCLOUD_PROJECT environment variable. See
 // https://googlecloudplatform.github.io/gcloud-node/#/docs/google-cloud/latest/guides/authentication
-let vision = require('@google-cloud/vision');
-let natural = require('natural');
-let redis = require('redis');
+const vision = require('@google-cloud/vision');
+const natural = require('natural');
+const redis = require('redis');
 
 // Instantiate a vision client
-let client = new vision.ImageAnnotatorClient();
+const client = new vision.ImageAnnotatorClient();
 
 function Index() {
   // Connect to a redis server.
-  let TOKEN_DB = 0;
-  let DOCS_DB = 1;
-  let PORT = process.env.REDIS_PORT || '6379';
-  let HOST = process.env.REDIS_HOST || '127.0.0.1';
+  const TOKEN_DB = 0;
+  const DOCS_DB = 1;
+  const PORT = process.env.REDIS_PORT || '6379';
+  const HOST = process.env.REDIS_HOST || '127.0.0.1';
 
   this.tokenClient = redis
     .createClient(PORT, HOST, {
@@ -59,12 +59,12 @@ Index.prototype.quit = function() {
 };
 
 Index.prototype.add = function(filename, document, callback) {
-  let self = this;
-  let PUNCTUATION = ['.', ',', ':', ''];
-  let tokenizer = new natural.WordTokenizer();
-  let tokens = tokenizer.tokenize(document);
+  const self = this;
+  const PUNCTUATION = ['.', ',', ':', ''];
+  const tokenizer = new natural.WordTokenizer();
+  const tokens = tokenizer.tokenize(document);
 
-  let tasks = tokens
+  const tasks = tokens
     .filter(function(token) {
       return PUNCTUATION.indexOf(token) === -1;
     })
@@ -82,8 +82,8 @@ Index.prototype.add = function(filename, document, callback) {
 };
 
 Index.prototype.lookup = function(words, callback) {
-  let self = this;
-  let tasks = words.map(function(word) {
+  const self = this;
+  const tasks = words.map(function(word) {
     word = word.toLowerCase();
     return function(cb) {
       self.tokenClient.smembers(word, cb);
@@ -114,7 +114,7 @@ Index.prototype.setContainsNoText = function(filename, callback) {
 };
 
 function lookup(words, callback) {
-  let index = new Index();
+  const index = new Index();
   index.lookup(words, function(err, hits) {
     index.quit();
     if (err) {
@@ -146,9 +146,9 @@ function extractDescriptions(filename, index, response, callback) {
 
 function getTextFromFiles(index, inputFiles, callback) {
   // Make a call to the Vision API to detect text
-  let requests = [];
+  const requests = [];
   inputFiles.forEach(filename => {
-    let request = {
+    const request = {
       image: {content: fs.readFileSync(filename).toString('base64')},
       features: [{type: 'TEXT_DETECTION'}],
     };
@@ -157,11 +157,11 @@ function getTextFromFiles(index, inputFiles, callback) {
   client
     .batchAnnotateImages({requests: requests})
     .then(results => {
-      let detections = results[0].responses;
-      let textResponse = {};
-      let tasks = [];
+      const detections = results[0].responses;
+      const textResponse = {};
+      const tasks = [];
       inputFiles.forEach(function(filename, i) {
-        let response = detections[i];
+        const response = detections[i];
         if (response.error) {
           console.log('API Error for ' + filename, response.error);
           return;
@@ -186,7 +186,7 @@ function getTextFromFiles(index, inputFiles, callback) {
 
 // Run the example
 function main(inputDir, callback) {
-  let index = new Index();
+  const index = new Index();
 
   async.waterfall(
     [
@@ -198,7 +198,7 @@ function main(inputDir, callback) {
       function(files, cb) {
         async.parallel(
           files.map(function(file) {
-            let filename = path.join(inputDir, file);
+            const filename = path.join(inputDir, file);
             return function(cb) {
               fs.stat(filename, function(err, stats) {
                 if (err) {
@@ -216,7 +216,7 @@ function main(inputDir, callback) {
       },
       // Figure out which files have already been processed
       function(allImageFiles, cb) {
-        let tasks = allImageFiles
+        const tasks = allImageFiles
           .filter(function(filename) {
             return filename;
           })
@@ -256,7 +256,7 @@ function main(inputDir, callback) {
 }
 
 if (module === require.main) {
-  let generalError =
+  const generalError =
     'Usage: node textDetection <command> <arg> ...\n\n' +
     '\tCommands: analyze, lookup';
   if (process.argv.length < 3) {
@@ -264,8 +264,8 @@ if (module === require.main) {
     // eslint-disable-next-line no-process-exit
     process.exit(1);
   }
-  let args = process.argv.slice(2);
-  let command = args.shift();
+  const args = process.argv.slice(2);
+  const command = args.shift();
   if (command === 'analyze') {
     if (!args.length) {
       console.log('Usage: node textDetection analyze <dir>');