Agentic Development
Framework
Agile, secure, and deeply integrated with modern AI, Coa's Agentic Development Framework reimagines how federal systems are built and maintained.
AI Operating Principles
Future-Ready, Now
Agentic AI is shifting from early concept to mainstream. We treat tomorrow's tools as today's baseline, embedding agents wherever they can shorten cycles and raise quality instead of waiting for "the next wave."
Lean Overhead — Internal Operations
Inside Coa, multi-step automation handles finance, compliance, and people-ops chores, freeing our team for design, engineering, and client impact. We didn't outsource this, we built and designed it
Savings Forwarded — Client Benefit
A lean operating model lets us bid more competitively, redirecting efficiency gains to agencies without trimming oversight or quality. We did this by design before AI, and AI now accelerates the approach—full stop.
Stable, Secure Scale — Government Projects
We prototype in controlled environments, version-control every workflow, and scale only when the process is demonstrably resilient—an approach championed by Digital service playbooks inside and outside government. We understand the specific challenges of compliance and integrating into existing architecture.
Cornerstone Principle: Transparent and Accountable Partnership
Our founders grew up in and around federal procurement; transparency is built into every engagement. We share roadmaps, source references, and test results so agencies always understand how an agent makes decisions and how updates propagate.
Four Patterns of AI-Native Development
Producer → Manager
From typing every line to supervising code-producing AI agents, your team shifts focus from mundane coding to high-value review, architectural thinking, and setting guard rails.
Implementation → Intent
Specifications become living markdown, not mountains of prose. Agents consume intent files—functional, security, and accessibility requirements—and orchestrate multi-step plans end-to-end.
Delivery → Discovery
Rapid prototyping ("vibe coding") emerges as interactive design sprints. Teams and even end-users can "A/B test" interfaces and workflows on the fly, guided by multi-variant agent swarms.
Code → Knowledge
Every commit, incident post-mortem, and architecture decision is captured in a persistent knowledge graph, so "lessons learned" become fuel for continually smarter agents and teams.
Moldable Development Environments
Our IDE extensions adapt in real time—diagramming diffs for at-a-glance review, auto-committing low-risk changes, checkpointing long-running agent workflows, and dynamically locking or scoping agent permissions to meet your compliance posture.
Team of Agents as Co-Developers
Imagine waking up to a dashboard of agent-authored pull requests, compliance reports, and UX prototypes—all queued for human approval. Your engineers, product owners, and security leads become conductors of AI co-workers, not just code typists.
Specific Capabilities
Autonomous Multi-Agent Orchestration
Deploy "agent teams" that plan, code, review, test, and document in parallel.
Define high-level goals ("harden this API for PII data at rest") and let agents self-coordinate toolchains, stub generation, and automated test suites.
Intent-Driven Specification Engine
Author ".ai.yaml" spec files that encode functional, performance, and security requirements once—then reuse across sprint cycles.
Agents translate specs into step-by-step GitHub Issues and pull requests, minimizing cognitive overhead for architects and reviewers.
Retrieval-Augmented Compliance & Security
Embed NIST SP 800-53, FISMA, FedRAMP baselines into your private corpus.
Agents enforce policy by default—flagging non-compliant code patterns, generating audit-ready reports, and automatically remediating low-risk gaps under human supervision.
Dynamic Knowledge Capture & Playground Sandboxes
Every design decision, post-incident analysis, and test outcome is indexed into a federated knowledge graph.
New hires or rotating teams "time travel" through past design conversations via conversational agents that recall context and rationale.
Cost-Aware, Permissioned Agent Runtimes
Track long-running agent sessions by cost center, with real-time budget alerts.
Fine-grained scoping: lock down file or API access, set read/write permissions, and enforce approval workflows at each commit.
Compliance & Governance
While deep AI integration drives velocity, federal modernization demands uncompromising compliance.
Policy-Driven Guard Rails
Agents operate within your pre-approved policy modules—no unvetted code may traverse the pipeline. Deviations trigger automated risk assessments and route to designated reviewers.
FedRAMP & FISMA Alignment
Our cloud-native AI platform is architected to FedRAMP Moderate controls, leveraging continuous monitoring agents to validate encryption-at-rest, key management practices, and identity-and-access governance.
Audit-Ready Reporting
Every agent action, from intent ingestion to auto-commit, is immutably logged. Compliance officers can query the ledger via natural-language prompts ("Show me every agent that wrote to the '/secure-config' folder last 30 days").
Ethics & Data Handling
Built-in opt-out filters and provenance tracking ensure no unauthorized PII or classified material is ever used in LLM prompts or stored in ephemeral agent memory.
Ready to Transform Your Development?
Experience the future of government software development with our Agentic Development Framework. Let's discuss how AI-native development can accelerate your agency's mission.