Run AI agents like an self-improving engineering team.
Dev Forge is an adaptive Kanban control plane where specialized AI agents plan, build, review, ship, monitor, and learn inside your existing SDLC — orchestrated by a Tech Lead agent that turns every review, deploy, incident, and metric into a better next run.
Architecting 2
Building 3
Shipping 2
routing work · resolving blockers · enforcing WIP limits & gates
The thesis
AI is an amplifier — not an autopilot.
DORA's 2025 research, drawn from nearly 5,000 technology professionals and 100+ hours of qualitative data, frames AI as an amplifier of an organization's existing strengths and weaknesses.1 Teams without strong delivery practices don't get speed — they get faster instability. Dev Forge is the layer that makes AI acceleration governable, observable, and measurable.
Why now
The market converged
Every leading coding agent now follows the same path: ticket → branch → PR → human review.14 The frontier is no longer a single agent writing code — it's orchestrating many specialized agents with governance.
The gap
Speed without a control plane
Point agents accelerate coding but leave leaders blind to risk, cost, and quality across the team. There is no shared board, no audit trail, no quality gate spanning all agent activity.
The shift
From assistant to operations
Dev Forge treats agents as a managed workforce on a Kanban board — with roles, WIP limits, dependencies, approvals, and SLOs — so engineering leaders run agent work the way they run human teams.
The problem
Faster code is not faster delivery.
The evidence is sobering and it is exactly why a governance layer matters. Dev Forge is designed to convert raw AI speed into stable, measurable delivery.
The platform
Kanban as the agent operations layer.
The board is the control plane — but not a brittle rulebook. Columns express your SDLC, cards carry context, and the Tech Lead agent continuously tunes routing, prompts, checks, and handoffs from real outcomes: review feedback, test failures, deploy signals, incidents, and human corrections.
A board leaders already trust
WIP limits, swimlanes, dependencies, and blockers — the operating model of modern engineering, now applied to a fleet of agents.
Adaptive guardrails
Start with safe defaults, then let evidence tune permissions, review depth, and escalation thresholds instead of freezing the architecture behind too many rules.
Observable end to end
Trace every prompt, tool call, diff, test, approval, and deploy — with token and cost attribution per card, per agent, per team.
Inside your SDLC, not beside it
Connects to GitHub, GitLab, Bitbucket, Jira, Linear, Slack, and Teams. Work lands as branches, PRs, and tickets your team already reviews.
Closed delivery loops
The board doesn't stop at "merged." Deploy and Monitor stages keep agents accountable through canary, rollback, and SLO watch.
Self-improving by design
The Tech Lead agent reads board history, reviewer comments, CI failures, production signals, and human corrections to improve decomposition and routing over time.
The roster
One orchestrator. Six specialists.
Generalist agents create generalist risk. Dev Forge assigns scoped roles with scoped permissions — each agent does one job well, hands off cleanly, and leaves a trail.
Turns intent into a plan: system design, ADRs, interface contracts, and threat models. Maps dependencies before a line of code is written.
- ADRs
- API contracts
- threat models
- dependency mapping
Implements complex, cross-cutting features with tests. Owns correctness on the critical path — retries, data integrity, performance.
- feature impl
- unit + integration tests
- refactors
- perf
Handles well-scoped, high-volume work — wiring, flags, fixes, glue code — in well-tested repositories, freeing senior agents and humans for the hard problems.
- scoped tasks
- feature flags
- bug fixes
- glue code
Reviews every diff for correctness, security, and standards before it can advance. An independent agent — never the one that wrote the code.
- code review
- security checks
- standards
- blocking gate
Owns CI/CD, environments, and progressive delivery — canary, rollout, and automatic rollback — with deploys gated on approval and policy.
- CI/CD
- canary
- rollback
- infra policy
Watches production after release — SLOs, error rates, latency, regressions — and feeds incidents back onto the board as new, traceable work.
- SLO watch
- anomaly detection
- incident intake
- feedback loop
The workflow
From ticket to monitored production.
One adaptive pipeline the whole industry is converging toward — ticket → branch → PR → review14 — extended past the merge into deploy, monitor, and learn. The board improves from outcomes instead of relying on a frozen rule set.
Intake
Issue or request enters the board; Tech Lead decomposes and routes it.
Tech LeadDesign
Architecture, contracts, and a threat model — dependencies mapped up front.
ArchitectBuild
Code on a branch with tests; complex vs. scoped work split across agents.
Engineer · DeveloperReview
Independent review gate; PR-first, with human approval on high-risk changes.
Reviewer · HumanDeliver
Progressive deploy — canary, rollout, rollback — gated on policy and approval.
DevOpsMonitor
SLOs and errors watched in prod; regressions return to the board as new work.
MonitoringLearn
Outcomes tune future decomposition, routing, prompts, confidence thresholds, and guardrails.
Tech LeadThe architecture
A learning control plane over your delivery stack.
Dev Forge is model- and tool-agnostic. It observes agent work through your existing systems of record, learns which decisions created good outcomes, and adapts the operating model without hard-coding the team into a brittle architecture.
Architecture shown at the capability level. Underlying model and infrastructure choices stay configurable; the learning loop adapts operating behavior from evidence while guardrails keep risky actions reviewable and attributable.
Governance & security
Built for the enterprise risk bar.
Autonomy without control is a liability. Dev Forge maps directly to the frameworks your security, risk, and compliance teams already use to evaluate AI systems.
Control plane & RBAC
Role-based access, repo policies, scoped agent sessions, and admin dashboards — the enterprise agent-management model leaders now expect.10
OWASP LLM risk coverage
Defenses targeting the OWASP Top 10 for LLM applications — prompt injection, insecure output handling, supply-chain risk, sensitive-information disclosure, and excessive agency.9
End-to-end auditability
Every prompt, tool call, diff, test, approval, PR, and deploy is recorded as immutable, attributable events — mirroring the agentic audit-log model emerging across the industry.11
Human-in-the-loop gates
A PR-first workflow with approval gates on high-risk actions keeps humans in command of consequential changes.15
NIST AI RMF alignment
The platform is organized around the NIST AI Risk Management Framework functions — Govern, Map, Measure, Manage — so AI delivery fits your existing risk program.12
EU AI Act readiness
Record-keeping and human-oversight capabilities aligned to the EU AI Act's logging (Art. 12) and human-oversight (Art. 14) concepts.13
Observability
Measure the work, not the hype.
You cannot govern what you cannot see. Dev Forge gives leaders agent-level telemetry and ties it back to the delivery outcomes that matter — the DORA metrics.
Agent telemetry
Distributed tracing across the agent fleet — every step instrumented and attributable, aligned to emerging GenAI observability standards.16
DORA outcomes
Agent activity is rolled up into the four key delivery metrics, so you can prove AI is improving — or catch regressions early.2
Tracking these directly counters the throughput/stability regressions AI adoption can introduce.3
Competitive positioning
Point agents vs. an operations layer.
Today's leading tools are powerful single agents — autonomous engineers that take an issue to a PR. Dev Forge is the layer above them: a governed board orchestrating a specialized team end to end. The categories are complementary, not identical.
| Capability | Single coding agents17 | GitHub-native agents18 | Dev Forge |
|---|---|---|---|
| Issue → branch → PR | ✓ Yes | ✓ Yes | ✓ Yes |
| Multiple specialized agent roles | Mostly single | Single | ✓ 6 + orchestrator |
| Kanban control plane & WIP limits | — | — | ✓ Native |
| Cross-agent dependencies & routing | — | Partial | ✓ Orchestrated |
| Independent reviewer quality gate | Self-review | PR checks | ✓ Separate agent |
| Deploy + monitor in the loop | Varies | Via Actions | ✓ Built-in stages |
| Unified audit trail across all agents | Per-agent | ✓ Audit logs | ✓ Fleet-wide |
| Cost / token attribution per task | Limited | Limited | ✓ Per card & agent |
| DORA outcome reporting | — | — | ✓ Built-in |
| Model / tool agnostic | Often locked | Platform-bound | ✓ Portable |
Comparison reflects publicly documented product capabilities of representative tools — Devin, GitHub Copilot coding agent, Cursor Background Agents, Replit Agent, Factory Droids, Codegen, Atlassian Rovo Dev, OpenAI Codex, Google Jules, and Anthropic Claude Code.17 Vendor capabilities evolve quickly; verify current state before procurement.
ROI & the evidence
Upside is real — but only if it's governed.
Independent research shows meaningful productivity gains from AI coding tools. Dev Forge's role is to capture that upside without the stability and trust costs seen when AI runs ungoverned.
The pilot plan
Prove it in six weeks, on your repos.
A structured, low-risk pilot with a baseline, guardrails, and a measurable outcome — designed so your team owns the evidence at the end.
Baseline & connect
- Integrate 2–3 repos & issue tracker
- Capture current DORA baseline
- Define RBAC, policies & gates
- Pick 1–2 service scopes
Run the board
- Agents take scoped, well-tested work
- PR-first with human approval gates
- Reviewer gate enforced on all diffs
- Full audit & cost tracing on
Close the loop
- Add deploy & monitor stages
- Canary + rollback on a real change
- Incident feedback onto the board
- Tune gates & WIP limits
Decision pack
- DORA before/after, with caveats
- Cost per delivered change
- Gate pass/reject & quality data
- Go / no-go with the evidence
Pilot scope and timeline are a recommended template and are adjusted to your environment, security review, and change-management requirements.
The roadmap
Where the board is heading.
A direction, not a promise. Sequencing reflects current priorities and will adapt to pilot feedback and the broader market.
- Kanban control plane & orchestration
- Six specialist agents + Tech Lead
- RBAC, policy & approval gates
- Full audit trail & cost metering
- GitHub / GitLab / Jira / Slack
- DORA dashboards & benchmarks
- Custom gate & policy authoring
- Deploy + monitor loop GA
- SSO, SCIM & advanced RBAC
- Expanded tracker integrations
- Customer-defined agent roles
- On-prem / VPC deployment
- Compliance evidence exports
- Marketplace of governed agents
- Cross-team portfolio view
Give your agents an operations layer.
Bring AI delivery under one governed board — orchestrated, observable, and measured. Start with a six-week pilot on your own repositories and let the evidence decide.