Studio
Build AI agents on a visual canvas
Drag, connect, and run. Design multi-step agent workflows on a canvas instead of wiring SDKs and glue code.
From zero to shipped in three steps
- Step 1
Pick a plan
Choose a credit plan. Credits are a universal balance across every Developers Digest app, so nothing is stranded in one tool.
- Step 2
Do the work in one place
One workflow wraps the underlying models. No API keys, no SDK setup, and the credit cost is always shown before you commit.
- Step 3
Ship the result
Export web-ready output and move on. Everything you make keeps its full recipe, so you can reproduce or iterate later.
Built for shipping, not fiddling
Workflows you can see
Every agent is a graph of nodes and edges on a canvas. The logic is visible at a glance, so you and anyone you share it with can understand the flow without reading code.
Models, tools, and logic as nodes
Drop in LLM steps, your connected tools, branches, and loops. Mix models within one flow and route each step to whatever handles it best.
Run and watch it think
Execute a flow and watch data move through the graph live. Every node shows its input and output, so debugging means clicking the step that went wrong.
Iterate without rebuilding
Swap a model, tweak a prompt, or reroute a branch and rerun from any node. The canvas keeps prior results so you only re-execute what changed.
From sketch to shipped agent
Publish a flow as a reusable agent with its own trigger: run it on demand, on a schedule, or from an event. The canvas is the source of truth either way.
Credits that travel
Designing and editing is free. Runs are metered by the universal Developers Digest credit balance shared with chat, images, voice, and more.
Common questions
What is Agent Builder?
Agent Builder is a visual tool for building AI agents. You design workflows as a graph of nodes on a canvas, connecting models, tools, connectors, and logic, then run and debug the whole flow before shipping it as a reusable agent.
Do I need to write code?
No. Flows are built by dragging nodes and connecting them. If you want code, optional script nodes let you drop in custom logic, but everything from prompts to branching works without it.
Which models and tools can a flow use?
Flows can mix multiple LLMs in one graph and call your connected tools like Gmail and Slack, plus logic nodes for branching and loops. Each step routes to whatever handles it best.
How do I debug a flow that goes wrong?
Every node records its input and output for each run. You click the step that misbehaved, see exactly what it received and produced, fix it, and rerun from that node without repeating the rest of the flow.
From the blog
Agents 101: How to Build and Deploy Anything with AI Agents
A behind-the-scenes walkthrough of building and deploying AI agents fast, plus the map of what to learn and where to go next.
Read postAgent Architecture: Multi-Step AI Workflows That Survive Production
Loop patterns, state management, and error recovery for the multi-step flows you assemble on the canvas, so a five-step demo holds up at scale.
Read postAgent Workflows as Code: Why State Machines Beat Prompt Checklists
Typed gates, validated evidence, and controlled transitions. Why agent processes want a real graph, not a prompt checklist.
Read post