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Dhruv Joshi
Dhruv Joshi

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Top 10 Agentic AI Tools for Developers to Speed Up Coding

Hey Devs, Dhruv Here. 👋

I've been building software and writing content about it for about 7 years now. I’ve witnessed the evolution of tooling, from writing repetitive code manually to having AI pair-programmers that feel almost magical.

We're not just getting code suggestions anymore, we’re delegating entire tasks to AI-powered agents.

In this post, I’m sharing 10 AI agentic tools that I personally find game-changing, the kind that save time, reduce context switching, and let me focus more on architecture and less on boilerplate.

🧠 What Is Agentic AI?

Quick detour for clarity — agentic tools are not just passive assistants like autocomplete or chatbots. These are task-completing, goal-oriented AIs. You give them intent (“write tests for this module” or “generate a PR”), and they act, often by chaining tools, APIs, and reasoning steps on your behalf.
Let’s dive in 🔽

🏆 1. Smol Developer (SmolAI)

🛠️ “Build entire apps from a single prompt.”

Why I use it: SmolAI takes a high-level prompt and scaffolds a working application using React, Next.js, Python, etc. It’s perfect for MVPs or exploring quick product ideas.

Best for: Indie hackers, prototypers, hackathon junkies.

Link: https://github.com/smol-ai/developer

🤖 2. GPT Engineer

🧠 “Engineer a codebase from natural language specs.”

Why I use it: It reads your project goal, asks clarifying questions, then autogenerates a full repo. It's less flaky than it sounds especially with well-defined inputs.

Great for: Bootstrapping internal tools and dashboards.

Link: https://github.com/AntonOsika/gpt-engineer

🛎️ 3. AgentOps

🧰 “Production-ready framework for running AI agents reliably.”

Why I use it: This is a playground for running and observing LangChain / AutoGPT-style agents. Great for teams that want to deploy agents in prod safely.

Use case: Automated task bots with retry logic and observability.

Link: https://www.agentops.ai

🔍 4. Continue.dev

🧠 “Autocomplete on steroids right inside VSCode.”

Why I use it: Local-first and customizable. Works like Copilot, but smarter and self-hostable. Bonus: integrates with GPT-4, Claude, and local models.

Ideal for: Privacy-focused devs and open-source lovers.

Link: https://continue.dev

🧪 5. Code Interpreter (aka “Advanced Data Analysis”)

📈 “Think: Excel + Python + AI.”

Why I use it: I use ChatGPT’s Code Interpreter plugin for data wrangling, visualizations, and even debugging stack traces. Think of it as an AI that writes + executes code in one go.

Cool use case: Refactor logs, generate graphs, analyze crash dumps.

Available in: ChatGPT Plus (GPT-4)

🧠 6. AutoDev

🧑‍💻 “Your AI teammate that takes tickets and gets stuff done.”

Why I use it: It takes issues from your backlog and completes them using LLMs and tools. Think of it as AI handling your TODOs, from bug fixes to new features.

Used for: Jira/GitHub integration, self-closing tickets.

Link: https://autodev.ai

🌐 7. Bloop AI

🧠 “Search and understand large codebases.”

Why I use it: Searching through legacy codebases is a nightmare. Bloop makes it conversational. I can ask things like “Where is the auth middleware initialized?” and it tells me precisely.

Killer feature: Multi-language code understanding + VSCode plugin.

Link: https://bloop.ai

📜 8. Sweep

🔄 “Auto-generates GitHub PRs from natural language issues.”

Why I use it: I just drop a GitHub issue like “Add loading spinner on login page”, and it spins up a PR with the changes. Wildly useful when juggling lots of small tasks.

For teams: Cuts down the time between ticket creation and code review.

Link: https://sweep.dev

⚙️ 9. OpenDevin

🧱 “Agentic dev environment with real-time task execution.”

Why I use it: Unlike ChatGPT, this is more of a workspace where AI can reason, write, and execute in a persistent shell environment. It’s like pair programming with a senior engineer who doesn’t sleep.

Link: https://github.com/OpenDevin/OpenDevin

🧼 10. Cody (by Sourcegraph)

🧑‍🏫 “Your AI codebase tutor.”

Why I use it: Cody helps me understand code deeply. It's ideal for navigating large codebases, understanding architectural decisions, and generating inline docs.

Favorite feature: “Explain this file to me like I’m new here.”

Link: https://sourcegraph.com/cody

✨ Final Few Lines

These tools don’t make us obsolete — they amplify us. With the right AI agent, you can move from idea to prototype in hours, not weeks.

But remember: agents are still learning. Keep your human-in-the-loop hat on 🧢.

If you’ve tried any of these or have others to recommend, drop a comment — always down to discover what’s working for real-world devs.

Follow me on dev.to 👉 @dhruvjoshi9
Let's keep shipping smarter.

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