The technology and methodology behind Agently Works.
Managers refine workflows in their own AI tools. Agently Works distills those workflows into persistent, purpose-specific agents that serve the entire team — with enterprise-grade governance.
The Iterate-Distill-Deploy Flywheel
Most AI platforms ask you to start from scratch on their system. Agently Works starts from the work you're already doing — in the AI tools you already use — and turns your proven workflows into organizational infrastructure.
You work with your AI tools.
Use Claude, Cursor, Copilot, or whatever fits your workflow. Handle operational tasks — reviews, compilations, triage, monitoring — the way you already do. We help you set up context files, integrations, and configurations that make your tools dramatically more effective.
You correct and refine.
When the output doesn't meet your standard, you tell it. "This missed the error handling convention." "This should flag the customer tier." "This summary needs to lead with blockers." Each correction sharpens the workflow. Over days and weeks, your AI goes from generally useful to deeply aligned with your standards.
Agently Works distills.
When a workflow is stable — when corrections have converged and the AI consistently meets your bar — we extract it into a skill. A skill isn't a prompt template. It's a codified unit of your expertise: your quality standard, your escalation logic, your definition of "good enough."
Agently Works deploys.
The skill becomes a persistent, purpose-specific agent on the Agently Works platform. Always-on. Accessible to your team members and other agents. Governed with access controls and audit trails. It runs without your laptop being open.
Skills compound.
A code review skill built by one engineering manager can be adopted across all engineering teams. A deal review skill built by a sales director cascades to every AE. The organization's quality standards become infrastructure, not tribal knowledge that lives on individual laptops.
You iterate locally. We deploy organizationally.
Two layers of technology.
Agently Works operates across two distinct layers:
The Manager Layer (Your Tools)
Managers use their preferred AI tools — Claude, Cursor, Copilot, VS Code — for daily work. Agently Works enhances this layer by providing:
Context design. Structured context files that encode your company's standards, conventions, domain knowledge, and organizational context — so your AI tools actually understand the work.
Integration support. Connections to your repositories, channels, dashboards, and data sources — so your AI assistant has access to the information it needs.
Workflow configuration. Best-practice setups for specific operational tasks, customized to your role and industry.
This layer is tool-agnostic. Whatever AI tools your managers prefer, we make them work better.
The Platform Layer (Agently Works)
When skills are distilled and deployed, they run on the Agently Works platform. This is where individual manager workflows become organizational capabilities:
Persistent agents. Always-on, not session-bound. A deployed code review agent reviews PRs as they arrive, 24/7.
Team-aware architecture. Every deployed agent knows what other agents exist in the organization, what they're responsible for, and how to route work to them.
MCP integration. Team members access deployed agents from their own tools through the Model Context Protocol. No new interface to learn.
Access controls. Role-based permissions define who can access which agents. Permissions are managed centrally and enforced at the agent level.
Gateway agents. Sensitive resources are never exposed directly. Dedicated gateway agents act as intermediaries, enforcing granular access policies.
Model routing: the right model for the right task.
Complex reasoning and code review
Leading frontier models for tasks requiring deep analysis.
Structured data processing
Efficient models for parsing, compilation, and formatting.
Triage and routing
Fast, lightweight models for classification and prioritization.
Sensitive data processing
Local, open-source models for work that can't leave your infrastructure.
This keeps costs manageable and ensures sensitive data is handled appropriately — without compromising quality where it matters.
For organizations: the fastest path to value.
An FDE is not a consultant who writes a report and leaves. They embed with your team — typically for 3-6 months — and do the hands-on work of building your agentic capability:
The FDE engagement is designed to transfer capability, not create dependency. By month 3-6, your team runs the system independently. The FDE's success is measured by how unnecessary they become.
Security architecture.
Role-based access controls
Every deployed agent, every user, every resource has explicitly defined permissions. No implicit access.
Gateway agents
Sensitive resources are accessed through dedicated intermediary agents that enforce policies, log queries, and limit exposure. Your database agent can provide aggregates without exposing rows.
Audit trails
Every action is logged with full context: who triggered it, what agent executed it, what data was accessed, what the output was, and what it cost.
Encryption & isolation
Data encrypted in transit (TLS 1.3) and at rest (AES-256). On-premise deployments use your existing key management infrastructure. Air-gapped deployments have zero network connectivity.
Learn more about enterprise deployment, compliance, and security →
Ready to see how it works for your team?
Whether you're a manager looking to deploy your first skill or an organization designing your agentic transformation.