[ Agent library ]

An agent for every role on the team.Run them as shipped, or build your own.

The library covers the delivery lifecycle role by role, from backlog readiness to release evidence. Every agent is a versioned definition that runs inside your Azure DevOps project, reads only the scope you configure, and pauses for a named approver wherever your policy says so.

Business Analyst Agent avatar
[ The catalog ]

Agents for
everything DevOps

[ Agents by role ]

22 roles in six groups.

Pick the group that matches your team. Each role lists the workflows it can hand over, from Definition of Ready checks to evidence packages, and the seven featured agents have full pages with example runs.

Role pages organize workflows and vocabulary. They are not employee-replacement pages, and no agent holds professional accountability. The role owner keeps judgment, approval and regulated determinations: agents prepare, validate, trace and assemble review-ready outputs, and qualified people decide.

[ Build your own ]

The exact agent you need, in plain language.

Start from a library agent or a blank definition. No coding is needed: the platform generates what runs behind the instructions, and you never write or see that code.

  1. Start from the library, or describe it.

    Add a library agent with Use, or choose Create with AI and describe the job in plain English. The platform drafts the agent and matches it to skills from the library, and you review the result before anything is saved.

  2. Give it your rules and its scope.

    Edit the instructions in plain English, attach your SOPs, templates and standards as knowledge, choose the model and see its credit rate, and scope the agent to a project, area path or work item type.

  3. Align it to your process template.

    Library agents are built on predefined process templates. Compatibility Alignment maps their work item types, fields and allowed values to yours, suggests matches, flags type mismatches, and blocks invalid mappings until every conflict is resolved.

  4. Set the trigger and save a version.

    Choose a manual, event or scheduled trigger and decide whether Required Approval is on. Every save is a version you can preview and restore. When a library template changes, you choose Keep Existing or Review & update, and the previous version stays in Version history.

[ Two agent types ]

Match the agent to the shape of the work.

Execution Agents run a fixed rule your team can read. Assisted Autonomous Agents reason over context and draft for review. Most teams use both, and every plan includes both.

Execution Agents compared with Assisted Autonomous Agents
Execution AgentsAssisted Autonomous Agents
How it decidesApplies a fixed, versioned rule. Deterministic code, the same result for the same input.Plans with model-based reasoning inside the configured tool and data scope.
Model at run timeNone. No model call when the agent runs.A model call on every run, on the model you chose for that agent.
Cost per run4 credits flat, about $0.04, however many Azure DevOps calls the rule makes.Scales with the work: invocation, model tokens, tool calls and orchestration steps.
Writes to Azure DevOpsUpdates fields, tags, states, links or scores directly, because the rule is fixed.Leaves a draft or analysis on the item, and writes back once the reviewer approves.
ApprovalThe approval is the rule itself: your team wrote it, can read it, and versions it.With Required Approval on, the run pauses and opens a task for the named approver.
Best suited toHigh-frequency checks: required fields, linkage, readiness flags, nightly hygiene sweeps.Drafting criteria, decomposing epics, pipeline diagnosis, change impact, evidence assembly.
How it is createdGenerated from a plain-language prompt, with model credits charged once at creation, or written by hand at no model cost.From a library agent, from a plain-English description, or from instructions you write yourself.
Run guardrailsExecution-time and API-call limits. A run that reaches one is stopped.Maximum steps, retries and sub-agents per run. A run that reaches one is stopped.
[ Industry persona agents ]

78 persona agents for six more industries.

Each industry is its own section under Assisted Autonomous Agents, with 13 role-based personas such as Product Owner, Business Analyst, Systems Architect, Compliance & Risk Officer and Requirements Engineer, plus engineering and delivery roles specific to the domain. Add one with Use, and Compatibility Alignment maps it to your process template.

  • 13 personas

    Defence

    Capability backlogs under JCIDS, DoDAF 2.02 architecture viewpoints, and NIST SP 800-171, CMMC 2.0 and DFARS cybersecurity compliance.

  • 13 personas

    Oil & Gas / Energy

    Process control and Safety Instrumented Systems under IEC 61508/61511 (ISA-84), IEC 62443 zone and conduit security, and OSHA PSM and API RP 754 compliance.

  • 13 personas

    Hardware & Electronics

    Backlog and requirements rigour aligned with IPC-2221, IPC-6012, IPC-A-610, JEDEC and IEC 62368-1.

  • 13 personas

    Rail Infrastructure

    EN 50126 RAMS, EN 50128 software, EN 50129 signalling safety and EN 50159 safe transmission, covering interlocking, train detection, ETCS/ERTMS and CBTC architecture.

  • 13 personas

    Construction & Civil Engineering

    ISO 19650 information management, BIM federation, and Eurocode, IBC and ASCE 7 compliance.

  • 13 personas

    Nuclear

    Safety-classification-aware design basis, system and software requirements, I&C and plant architecture with independence and single-failure criteria, and Part 21 evaluability screening.

  • 150+agents in the library
  • 200+core capabilities
  • 800+industry-tuned skills
  • 15industry packs

[ Trusted by Microsoft and industry leaders ]

  • Info-Tech Research Group Top Rated 2025
  • Info-Tech Research Group Emotional Footprint Champion 2025
  • SoftwareReviews Champion 2025, Requirements Management
[ FAQ ]

Questions about the library.

Execution Agents run deterministic code with no model call at run time, so every run costs a flat 4 credits. Assisted Autonomous Agents use a model on each run to read context, reason and draft, and their cost scales with the work performed. Put rule-shaped, high-frequency work on Execution Agents and spend credits where reasoning adds value.

No. Describe the agent in plain English, write the instructions yourself, or start from a library agent. The platform generates the code behind it. If you prefer to write an Execution Agent's code yourself, you can, and there is no model cost at all.

Yes. Run it as shipped, or fork it: edit the instructions in plain English, attach your SOPs and templates as knowledge, narrow its scope and change its model. Every save is versioned, and you can preview and restore any earlier version.

Your agent is flagged with a Library Update icon and shows the Updated tag in the library. Choose Keep Existing to stay where you are, or Review & update to open the new library content in the editor. If you edited the agent, a warning says the update replaces those edits, and your previous version stays in Version history.

Compatibility Alignment checks the agent's work item types, fields and allowed values against your project when you add it. It maps what matches automatically, suggests matches for the rest, and lets you map each value individually before the agent is saved.

No. Qualified people keep architecture, safety, compliance, certification and go/no-go decisions. Agents prepare, validate, trace and assemble review-ready outputs, and anything with side effects follows the approval policy your team configured.

Yes. Every plan includes both agent types, the full agent catalog and every industry pack. Plans differ in execution capacity and operating capabilities, not content.

Put one agent on one real workflow.

Start the free trial with 2,000 credits and no card, or bring a backlog, a pull request or a failed pipeline to a 30 minute demo and watch the agent run inside Azure DevOps.