Description:

This 8-hour intensive introduces Devin, Cognition's autonomous AI software engineer, and its 2026 product suite: Devin Cloud, Devin Desktop, Devin CLI, and Devin Review. Participants move from watching Devin plan and execute a task end to end, to delegating real work through Interactive Planning, to orchestrating parallel Managed Devins on larger jobs. The day closes with the governance and review discipline needed to run Devin safely inside a real engineering workflow.

Duration: 

8 Hrs

Course Code: BDT633

Learning Objectives:

After this course, you will be able to:

1. Explain Devin's agent-native architecture and how the Atlas-style reasoning loop plans, executes, and verifies a coding task inside a sandboxed VM.
2. Configure a Devin account, connect a GitHub repository, and set up Devin Desktop or the Devin CLI for local, agent-assisted development.
3. Apply Interactive Planning and Devin Search / DeepWiki to scope an engineering task accurately before execution begins.
4. Orchestrate Managed Devins to break a large task into parallel, independently verified sub-tasks.
5. Evaluate Devin-generated pull requests using Devin Review and apply governance practices appropriate to the organization's security and compliance needs.

1. Software engineers and development teams evaluating autonomous coding agents for their SDLC.
2. Engineering managers and tech leads assessing AI-agent ROI, cost, and governance.
3. DevOps and platform engineers responsible for CI/CD and code-review workflows.

1. Working knowledge of Git and GitHub (clone, branch, commit, pull request).
2. Basic familiarity with the software development lifecycle and reading code in at least one language.
3. A free GitHub account and a laptop meeting the system requirements.

Course Outline:

Module 1: Devin Foundations 

1. What Devin is: Cognition's cloud agent that plans, codes, tests, and opens pull requests with minimal supervision.
2. The agent-native shift: each session runs in its own sandboxed VM with a terminal, browser, and code editor.
3. Devin's product surfaces: Devin Cloud (autonomous sessions), Devin Desktop (the IDE, formerly Windsurf), Devin CLI, and Devin Review.
4. Free tier versus paid plans: what Free unlocks for exploration, and where Pro, Max, Teams, or Enterprise become necessary.

Module 2: Delegating Work - Interactive Planning & Task Assignment

1. Writing an effective task brief for Devin: scope, acceptance criteria, and constraints.
2. Interactive Planning: how Devin proposes a plan and asks clarifying questions before it starts executing.
3. Assigning tasks through Slack, Jira or Linear, a GitHub issue, or directly in the Devin web app.
4. Observing a live session: reading the terminal, browser, and editor activity as Devin works.

Module 3: Advanced Capabilities - Search, Wiki & Managed Devins 

1. Devin Search and DeepWiki: auto-generated, auto-refreshing codebase documentation with cited answers.
2. Managed Devins: one Devin coordinating a team of parallel sub-agents, each in its own isolated VM.
3. Devin Fusion: a multi-model harness pairing a frontier model with a lower-cost sidekick model to cut task cost.
4. Scheduled, recurring sessions: using Devin as an ongoing background teammate rather than a one-off tool.

Module 4: Review, Governance & Deployment 

1. Devin Review: AI-assisted pull request review; public GitHub PRs can be reviewed for free at devinreview.com.
2. Treating Devin's output like a junior engineer's work: review discipline and the real-world PR merge-rate.
3. Security and compliance posture: SOC 2, ISO 27001, and VPC/private-cloud deployment for Enterprise customers.
4. Choosing a plan for your team: Free, Pro, Max, Teams, or Enterprise, and the cost/governance trade-offs of each.

Hands-On:

1. Create a Devin account on the Free tier, sign in with GitHub, connect a sample repository, and tour the Devin Cloud workspace.
2. Assign a small bug-fix or feature request to Devin, review its plan, and let it run to a completed pull request.
3. Ask Devin Search a question about the sample codebase, then split a multi-part task across two Managed Devins running in parallel.
4. Run an end-to-end workflow: submit a task, review Devin's plan, inspect the resulting pull request with Devin Review, and merge it.