Replit Introduces Free Mode to Expand What is Possible with AI

With OpenAI, Replit now helps you accomplish even more, every day.

Replit | Databricks Integration is Now Generally Available with Native Lakebase Support

The Replit | Databricks integration gives enterprise teams a faster path to utilizing governed data for production-ready applications. Today, we’re excited to announce the integration is generally available alongside a new capability: native Databricks Lakebase support. This builds on the foundation introduced from our public preview announcement this past June.

The result is one seamless path from idea to production: Replit accelerates application creation, while Databricks hosts and provides governed access and security to live enterprise data. Through Lakebase, Databricks also delivers a managed database for storing and updating application data.

With native Lakebase support, teams can build full-stack, context-rich apps that combine live Databricks warehouse data with information created and updated through the app. When an app built with Replit is ready to deploy, Replit Agent automatically provisions its Lakebase database, eliminating the need for manual setup.

New Capabilities for a Faster, Safer Launch

Automated Preview Deploys: Test your apps before they go live. Replit automatically creates a separate preview environment that keeps test data isolated from live business data in Databricks, giving teams a safe place to build, review changes, and make adjustments.

Intelligent Model Routing on Replit

Replit now picks the best model for every task, automatically.

Black-box pen tests on Replit

See how Replit's new black-box pen testing simulates real attacks to find vulnerabilities hidden from code-only scans.

Govern Replit at scale

New Enterprise Governance tools for Replit.

AI adoption starts with truth

The semantic layer is the foundation. AI adoption is limited by trust. A user who gets burned by a confidently wrong answer will double-check the next one, eventually routing consequential work around the system entirely. Once that happens, AI remains a tool at the edges rather than infrastructure at the center… useful, but never trusted with the workflows where its value compounds. Before a company can benefit from more capable agents, those agents need a reliable way to know what the company considers true.

A semantic layer tells an agent which tables are sources of truth and how they relate. That's the floor. It is necessary, and it isn't sufficient.

A semantic layer is not plumbing. It is the first act of governance for an AI-native company: the shared definitions of the business, the canonical metrics, the sources of truth, and the relationships an agent is allowed to rely on. Without it, an agent does not have a data problem. It has a language problem: several tables can each look plausible, and the model has no grounded way to know which one means "revenue," "active user," or "customer."

Getting that floor right changes the shape of everything above it. A semantic layer is not the product; it is the shared contract that lets a company safely add a system of specialized capabilities instead of one generic chatbot. Once an agent can ground itself in the right entities, metrics, and relationships, it can reliably run multi-step workflows, call focused tools, retain reviewed knowledge across runs, reuse validation and analysis code, and operate through durable services where work already happens.

Introducing Replit Design

The next era of design, for everyone.

The Self-Driving Company

We are beginning to see what happens when a company learns to operate itself.

Closing the loop: Evaluating and improving Replit Agent at scale

Most Replit Agent users start with an idea. They describe the goal in natural language — without a repo, test suite, or chosen framework — and expect the agent to turn it into a functioning app. The result might be a website, slide deck, mobile app, several connected artifacts, or something else entirely.

Vibe coders are not usually checking diffs or test output. Success for Replit Agent is deceptively simple: the app should work when users click around.

That changes the job of evaluation. A single score can help with a specific shipping decision, but it cannot tell us, week over week, whether Replit Agent is getting better for users. To answer that question, evaluation must become part of the improvement loop.

Vibe Coding's Coachella Moment Just Happened. Inside Replit's Inaugural Vibecon.

Powerful energy on New York’s Lower East Side, where the crowd was the one creating, vibe-coding and manifesting ideas into real things all day.

Replit is now available in Claude

Replit is now available directly inside Claude, making it easier than ever to go from a conversation to a fully built, shipped product - without losing context, in one seamless workflow.

Design in Claude, Build in Replit

You can now design on-brand, beautiful apps in Claude Design using natural language. Once your design is ready, send it directly to Replit to continue building, refining, and shipping your app—all through natural language and in one seamless workflow.

No copy-pasting, no context switching, no friction.

Customize Replit Agent with Skills & Custom Instructions

Every team has conventions. How you structure a project, how you handle secrets, your design system, your testing standards, your code style.

The problem: AI Agents don’t know your conventions. So you explain it again on every prompt, paste in your standards doc, or just hope someone remembered to add the context. It is one of those small frictions that compiles quietly until you are spending more time re-teaching the Agent than building.

Custom Instructions

Custom Instructions are always-on guidelines injected automatically into the agent's context on every project, every session, before anyone types a single word. Write them once, and the Agent applies them to every project in the workspace, automatically.

Replit | Databricks: Where fast app building meets granular data governance

Today, we're excited to announce two significant updates to the Replit and Databricks integration we launched in February: the user-to-machine (U2M) connector feature is now live, and the integration is now open for public preview sign-up.

Package Firewall: Blocking 8,000+ malicious packages daily

Replit already scans your projects for vulnerable dependencies and audits your dependencies before you publish. But risk shows up earlier than that, while you are developing, the moment a malicious package gets installed.

Today we're launching Package Firewall, in partnership with Socket (a software supply-chain security company). Package Firewall blocks malicious and compromised packages from ever being installed into your app, even while you are building. This network-level security protection eliminates any window for malware to be installed into your project. It's on by default for every builder, with nothing to set up.

Build a custom Shopify storefront on Replit

Starting today, anyone can design and launch a custom Shopify storefront by chatting with the Replit Agent. Describe the store you want, and Agent generates a custom front end, creates a new Shopify store, and adds your products from the same conversation. When you're ready to sell, claim the store in Shopify, activate payments, and use Replit to deploy your storefront to a domain. From the first prompt to taking real orders is roughly ten minutes.

Why we built this

Replit builders already ship real software, from internal tools to side projects to full businesses. But selling physical products is different: managing physical inventory, fulfillment, tax compliance, shipping, and multi-channel selling. Shopify is the gold standard for that, powering retail businesses of every size. What was missing was a way to design a storefront for Shopify with the same conversational workflow Replit builders already use for everything else.