DEV Community: Sahil Khurana

Streamlined Customer Service: Chat Integration with Gladly

Sahil Khurana — Fri, 08 May 2026 13:41:29 +0000

Customer expectations have never been higher. Businesses that fail to respond quickly and personally across every channel risk losing customers permanently. Gladly is a modern customer service platform built to solve exactly this problem — and integrating its chat capabilities into your website is one of the most impactful steps you can take toward delivering exceptional support.

What is Gladly?

Gladly organizes every customer interaction in one place. Unlike traditional ticketing systems, it unifies emails, phone calls, text messages, social media, and live chat into a single interface, giving agents a complete view of every customer's history. This makes communication management simple, efficient, and deeply personal. If you're evaluating platforms for your next custom software project, Gladly is worth serious consideration.

Advantages of Gladly

Unified Communication — All customer conversations across every channel flow into one interface. Agents never lose context, no matter how a conversation started. This is the foundation of a great customer experience strategy.
Customer Profiles — Gladly builds rich profiles that include contact details, purchase history, and past inquiries, allowing agents to deliver genuinely personalized assistance every time.
Team Collaboration — Agents can share notes, assign conversations, and work together in real time — eliminating siloed inboxes and missed handoffs.
Automation and AI — Gladly handles repetitive queries automatically, prioritizes important responses, and frees agents to focus on complex issues that need a human touch. Learn more about AI integration in customer workflows.
Analytics and Reporting — Supervisors can track response times, customer satisfaction scores, and agent performance, helping teams spot patterns and continuously improve their operations.

Chat Integration with Gladly

Chat integration with Gladly brings real-time messaging directly into your customer service workflow. The centerpiece is the Glad App — an embeddable widget that lets website visitors search help content or connect with a live agent instantly. This kind of API-driven integration is exactly where experienced development teams add the most value.

The Glad App API gives developers programmatic control over the widget. Add a JavaScript loader snippet to every page of your site — it asynchronously loads the Chat SDK without blocking page performance.

Gladly.init({
  appId: "your-own-id"
}).then(function() {
  // This is called once Glad App has been initialized.

  // An element with the id "start-chat" is assumed to be on the page.
  var startChatButton = document.getElementById('start-chat');

  // An onClick handler can be attached to the "start-chat" element
  startChatButton.onclick = function() {Gladly.show()};

  // This API call gets the current availability
  var availablility = Gladly.getAvailability();

  // Setting the availability as the class name on the "start-chat" element,
  // this allows us to change the look of the button via CSS.
  startChatButton.setAttribute('class', availablility.toLowerCase());

  // Subscribe to changes in availability, and update the class on the "start-chat" element.
  Gladly.on('availability:change', function(availablility) {
    startChatButton.setAttribute('class', availablility.toLowerCase());
  });
}).catch(function(error) {
  // If anything goes wrong when Glad App is being initialized, this gets called.
  console.log('error:', error)
});

Once the loader is in place, initialize the Glad App using your unique appId, found in Settings → Glad App in the Gladly dashboard. For basic use, a simple global config object is all you need.

&lt;script&gt;
 window.gladlyConfig = {
   appId: 'your-own-id'
 };
&lt;/script&gt;

For more control — such as launching chat from your own custom button or adjusting the UI based on agent availability — manual initialization via Gladly.init() gives you full flexibility.

Gladly.init({
  appId: "your-own-id"
}).then(function() {
  // This is called once Glad App has been initialized.

  // An element with the id "start-chat" is assumed to be on the page.
  var startChatButton = document.getElementById('start-chat');

  // An onClick handler can be attached to the "start-chat" element
  startChatButton.onclick = function() {Gladly.show()};

  // This API call gets the current availability
  var availablility = Gladly.getAvailability();

  // Setting the availability as the class name on the "start-chat" element,
  // this allows us to change the look of the button via CSS.
  startChatButton.setAttribute('class', availablility.toLowerCase());

  // Subscribe to changes in availability, and update the class on the "start-chat" element.
  Gladly.on('availability:change', function(availablility) {
    startChatButton.setAttribute('class', availablility.toLowerCase());
  });
}).catch(function(error) {
  // If anything goes wrong when Glad App is being initialized, this gets called.
  console.log('error:', error)
});

The API also provides key methods: setUser() to pre-identify a logged-in customer so they skip the name/email form, getUser() to retrieve the current user, and clearUser() to remove the user on logout. Events like availability:change, message:received, and message:sent let you react to widget activity in real time.

Creating and Configuring the Glad App

Inside the Gladly dashboard, creating a Glad App takes just a few steps — navigate to Settings → Channels → Glad App, click Create Glad App, give it a name, and you're taken straight to the configuration screen.
The screen has three sections: Configuration (business hours, Quick Actions, throttling rules), Style (colors, border radius, widget position), and Text (all copy visible to the visitor). For the full setup walkthrough, refer to Gladly's official documentation.

What is Proactive Chat?

Proactive Chat lets you engage customers before they ask for help. Instead of waiting for a visitor to open the widget, you define campaigns that automatically initiate a conversation based on triggers — pages visited, time on site, cart value, and more. For e-commerce businesses especially, this feature directly impacts conversion rates and cart abandonment.
When setting up a campaign, you define a name, description, priority order, triggers, and an opening greeting. Two optional settings give extra control: Ignore chat throttling bypasses queue limits for high-priority campaigns, and Skip onboarding removes the name/email step to reduce friction. Full campaign configuration details are covered in Gladly's Proactive Chat guide.

Conclusion

Gladly transforms customer service from a reactive process into a proactive, unified experience. With its powerful Glad App API, rich customer profiles, and Proactive Chat campaigns, businesses can deliver faster and more personal support across every channel. If you need help integrating Gladly or building a custom chat solution, Innostax's engineering team is ready to help you ship it right.

About Innostax

Innostax is a custom software development and IT staff augmentation company. We build and integrate customer service platforms, develop custom software solutions, and provide managed engineering teams for startups, scale-ups, and digital agencies — typically in situations where customer experience is broken and needs to be fixed fast.

What Is Cursor AI? The Complete Guide to the AI-Native IDE (2026)

Sahil Khurana — Fri, 08 May 2026 13:24:13 +0000

Cursor AI is a VS Code-based AI code editor with Claude, GPT & Gemini built in.

TL;DR

Cursor AI is an AI-first code editor based on VS Code, built by Anysphere Inc. and co-founded in 2023 by four MIT graduates. Unlike plugins, it runs LLMs like Claude, GPT, and Gemini directly inside the editor — enabling real-time suggestions, autonomous multi-file editing, bug detection, and refactoring without context-switching. Developer teams using Cursor report 20–40% faster feature delivery and 20% fewer production bugs.

Key takeaways

Cursor AI is an AI-native IDE (VS Code fork) with built-in LLM collaboration — not a plugin.
Agent Mode executes multi-file, multi-step tasks autonomously.
Priced from free (Hobby) to $200/month (Ultra); Teams at $40/user/month.
Used by engineers at OpenAI, NVIDIA, Shopify, Coinbase, and 50%+ of Fortune 500.
Honest limitation: requires internet — no offline or air-gapped support.

What is Cursor AI?

Cursor AI is an AI-native integrated development environment (IDE) — an editor built around AI collaboration from the ground up, rather than adding AI as a plugin — based on Visual Studio Code. As opposed to AI coding plugins, which are external to the editors, Cursor is built around AI collaboration, i.e. autocomplete, multi-file editing, agentic task execution and codebase-wide context are part of the editor, rather than extensions of the editors.

Cursor was founded by Michael Truell, Sualeh Asif, Arvid Lunnemark, and Aman Sanger, and is the fastest SaaS company to date to achieve $100 million in annual recurring revenue, having done so 12 months after its founding by MIT graduates in 2023.

"The best LLM applications have an autonomy slider: you control how much independence to give the AI. In Cursor, you can do Tab completion, Cmd+K for targeted edits, or you can let it rip with the full autonomy agentic version." — Andrej Karpathy, CEO, Eureka Labs

Why Software Teams Are Moving to Cursor AI in 2026

The numbers are hard to ignore. In a 2025 survey by Pragmatic Engineer, at least 85% of professional developers currently use some form of AI tool in their workflow. A Stack Overflow survey also indicates that 84% of professional developers currently use or intend to use an AI coding assistant.

What makes Cursor stand out is the depth of integration. Rather than suggesting the next line in isolation, Cursor understands how your entire codebase fits together. That difference produces measurable results:

20–25% time savings on common activities like debugging and refactoring
30–50% reductions in development cycle time on complex, full-stack projects
40% reduction in context switches during coding sessions
30–50% faster developer onboarding firm-wide

NVIDIA's CEO Jensen Huang called Cursor his "favorite enterprise AI service" and reported that 100% of NVIDIA's engineers now use AI coding assistance with a "remarkable boost" in productivity.

"At Innostax, Cursor AI is now part of our everyday engineering workflow. In practice, roughly 90–95% of the code written across projects is AI-assisted, helping teams move faster while maintaining consistent code quality standards."

Main Features of Cursor AI

Tab Completion (Cursor Tab)

Cursor Tab is Cursor's proprietary autocomplete model — not a generic code suggestion engine. It doesn't just complete the current line; it understands your next move based on surrounding code context and recent changes. Developers describe it as autocomplete on steroids.

Inline Edit (Cmd/Ctrl + K)

Inline Edit is Cursor's precision tool for making specific changes to a selected block of code. Highlight a function, describe the change you want in natural language, and Cursor presents a color-coded diff you can accept, reject, or partially apply.

Multi-File, Multi-Step Execution (Agent Mode)

Cursor's flagship capability. Agent Mode accepts a high-level goal in natural language and autonomously writes, edits, tests, and runs code across multiple files. This is Cursor's greatest point of difference from tools like GitHub Copilot.

Codebase Context Chat (Cmd/Ctrl + L)

Cursor uses codebase indexing — reading and mapping your entire project — so AI suggestions account for all files, not just the open one. This powers an AI Chat panel that acts as a project-sensitive collaborator you can query in natural language.

Background Agents and Automations

Released in 2025, Cursor's Automations platform enables teams to configure AI agents that respond to events — not only when triggered manually by a developer.

Cursor AI Pricing: Plans Compared (2026)

In June 2025, Cursor transitioned from a fixed-request model to a credit-based billing system tied to actual model API costs. Current plans:

Plan	Price	Best For
Hobby	Free	Individual exploration
Pro	$20/month	Individual developers
Business	$40/user/month	Engineering teams
Ultra	$200/month	Heavy Agent Mode, large context needs

When to choose Cursor: Teams that want deep, multi-file agent workflows, flexible model selection, and a full IDE experience. Best for complex greenfield or large legacy codebases.

When to choose GitHub Copilot: Teams already embedded in the GitHub ecosystem, or those who primarily need fast autocomplete within existing IDE setups without switching editors.

When to choose Windsurf: Organizations that want on-premise deployment, open-model support, or are cost-sensitive and need a capable free tier.

Integrating Cursor AI Into Your Development Process

Step 1: Installation and Configuration

Download Cursor from cursor.com. Because it is a VS Code fork, all existing VS Code extensions, themes, keybindings, and settings transfer automatically. Integrate your version control (GitHub, GitLab, Bitbucket) and current CI/CD pipelines during initial configuration.

Step 2: Begin with Tab, Advance to Agent

Tab completion is where new users should start — no prompting needed and typing speed improves immediately. Once comfortable, use Inline Edit (Cmd+K) for case-by-case refactors. Reserve Agent Mode for high-level goals where you want Cursor to arrange the implementation autonomously.

Step 3: Pair with Continuous Integration

Integrate Cursor's ability to propose and generate test cases into your CI pipeline. Set up Cursor to run automatic tests at the end of Agent-generated commits. This closes the feedback loop between AI-generated code and verified behavior.

Step 4: Review Every Diff

Never merge AI-generated code without reviewing it. Use Cursor's color-coded diff previews to check every change. For high-stakes refactors, work in a feature branch and commit frequently. Use the built-in bug finder (Cmd+Shift+P → bug finder) to surface regressions before shipping.

Real-World Use Cases

Rapid Prototyping

Cursor Agent Mode can scaffold full features — login systems, REST API endpoints, database models — from a high-level natural language description. Teams report compressing work that previously took days of prototyping into hours.

Legacy Code Modernization

Individual engineers at Coinbase refactored and upgraded entire codebases in days rather than months using Cursor. The codebase-wide context window allows Cursor to recognize outdated patterns and propose modern replacements without sacrificing business logic.

Automated Testing

Cursor analyzes existing function signatures and generates unit test suites, proposing edge cases developers might miss. Combined with CI automation, this significantly reduces the testing bottleneck on high-velocity teams.

Onboarding New Developers

New engineers can explore and understand unfamiliar codebases through natural language queries, without waiting for documentation or senior engineer walkthroughs. Teams report 30–50% faster onboarding using Cursor systematically.

Limitations and Honest Caveats

Cursor AI is powerful, but it cannot substitute engineering judgment. Teams should be aware of the following:

Hallucinated Code — Like any LLM, Cursor can produce plausible-looking but incorrect code, particularly with niche APIs or complex algorithmic logic. Every output requires human review.

Context Window Limits — Large monorepos can exceed context window limits, causing the AI to lose track of distant files. Scoping Agent Mode tasks to specific modules alleviates this.

Privacy Risk of Sensitive Code — While Privacy Mode disables code retention, teams working with trade secrets or regulated data should confirm Cursor's data handling with their legal team before onboarding sensitive codebases.

Internet Dependency — All Cursor AI features depend on cloud API calls. Standard plans do not support offline or air-gapped development.

How This Cursor AI Guide Was Built

This guide was developed by Sahil Khurana, CEO of Innostax, based on direct experience integrating Cursor AI into production engineering workflows across SaaS products, enterprise platforms, and fast-moving startup teams since its mainstream adoption in 2023.

The patterns outlined here — from Tab completion and Agent Mode workflows to CI/CD integration, code review guardrails, and real-world limitations — are drawn from live engineering environments, not demo projects. At Innostax, roughly 90–95% of code written across projects is AI-assisted using Cursor, making this an operational perspective rather than a theoretical one.

Innostax is a managed software development partner that has built AI-native engineering workflows into its core delivery model. We work with CTOs, SaaS founders, and product leaders who want to move faster without sacrificing code quality — typically in situations where development velocity is stalling, AI tooling is being adopted without proper guardrails, or teams need senior engineering oversight on AI-generated output before it ships.

If you're looking to integrate Cursor AI into your engineering workflow in a way that actually improves delivery — without accumulating technical debt — explore our work at innostax.com, or connect directly at innostax.com/contact.

Originally published on the Innostax Engineering Blog.