The agent operations layer for software delivery

Run AI agents like an engineering team — under governance.

Dev Forge is a governed Kanban control plane where specialized AI agents plan, build, review, ship, and monitor software inside your existing SDLC — orchestrated by a Tech Lead agent, with audit trails, quality gates, and human-in-the-loop approvals on every move.

7
specialized agents, one orchestrator
Govern·Map·
Measure·Manage
aligned to NIST AI RMF12
100%
actions logged & attributable11
Sits inside your stack GitHubGitLabBitbucketJiraLinearSlackTeamsCI/CD

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.

19% slower
In a 2025 randomized controlled trial, experienced open-source developers on real tasks expected AI to speed them up — but AI-allowed tasks took 19% longer.
SOURCE — METR RCT, 20258
−7.2% stability
DORA 2024 associated increased AI adoption with an estimated 1.5% decrease in delivery throughput and a 7.2% reduction in delivery stability.
SOURCE — DORA 2024 report3
Only 3%
Of developers say they highly trust the accuracy of AI output; 46% actively distrust it versus 33% who trust it (Stack Overflow 2025).
SOURCE — Stack Overflow Survey 20257
The Dev Forge position: we do not promise that agents magically ship faster. We make AI delivery governed, observable, and accountable — so coding speedups don't turn into delivery instability, and trust is earned through evidence, not claims.

The platform

Kanban as the agent operations layer.

The board is the control plane. Every column is a stage of your real SDLC; every card is a unit of work owned by an agent; every transition passes through policy, quality gates, and — where you require it — a human. Nothing moves invisibly.

A board leaders already trust

WIP limits, swimlanes, dependencies, and blockers — the operating model of modern engineering, now applied to a fleet of agents.

Governance on every transition

Policy-as-code, role-based permissions, and approval gates decide what each agent may do — and require sign-off before high-risk actions.

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.

Orchestrated, not chaotic

The Tech Lead agent routes work, sequences dependencies, resolves blockers, and enforces gates — so the fleet behaves like a team, not a swarm.

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.

Orchestrator

Tech Lead agent

The conductor of the board. It decomposes incoming work, routes each task to the right specialist, sequences dependencies, enforces WIP limits and quality gates, resolves blockers, and governs execution — escalating to humans whenever policy or confidence thresholds demand it. Everything else on this page reports to it.

Architect
design & decisions

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
Software Engineer
build the hard parts

Implements complex, cross-cutting features with tests. Owns correctness on the critical path — retries, data integrity, performance.

  • feature impl
  • unit + integration tests
  • refactors
  • perf
Developer
ship the steady stream

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
Reviewer
the quality gate

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
DevOps
deliver safely

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
Monitoring
close the loop

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 governed pipeline the whole industry is converging toward — ticket → branch → PR → review14 — extended past the merge into deploy and monitor, with a human gate wherever you place one.

01

Intake

Issue or request enters the board; Tech Lead decomposes and routes it.

Tech Lead
02

Design

Architecture, contracts, and a threat model — dependencies mapped up front.

Architect
03

Build

Code on a branch with tests; complex vs. scoped work split across agents.

Engineer · Developer
04

Review

Independent review gate; PR-first, with human approval on high-risk changes.

Reviewer · Human
05

Deliver

Progressive deploy — canary, rollout, rollback — gated on policy and approval.

DevOps
06

Monitor

SLOs and errors watched in prod; regressions return to the board as new work.

Monitoring
Human-in-the-loop by design. Following the PR-first pattern established across the industry, high-risk actions require explicit human approval before an agent can proceed.15

The architecture

A control plane over your delivery stack.

Dev Forge is model- and tool-agnostic. It governs and observes agent work through your existing systems of record — without replacing them, and without locking you to any single underlying model.

Experience layerhumans + leaders
Kanban board
Approvals & gates
Observability dashboards
Admin & RBAC console
Agent control planeorchestration · governance · audit
Tech Lead orchestrator
Policy & permission engine
Quality-gate engine
Audit & trace ledger
Cost & token metering
Architect
Software Engineer
Developer
Reviewer
DevOps
Monitoring
Systems of recordyour existing stack
Source control & PRs
Issue trackers
CI/CD & environments
ChatOps
Secrets & identity
Telemetry & SLOs

Architecture shown at the capability level. Underlying model and infrastructure choices are configurable and deliberately abstracted from the board so the platform remains portable across providers.

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

Traces prompts · tool calls · diffs Cost token & $ per card / agent Failures retries · errors · timeouts Latency step & end-to-end Quality gate pass / reject rates

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

Deployment frequency Lead time for changes Change failure rate Failed-deployment recovery time

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 rolesMostly singleSingle✓ 6 + orchestrator
Kanban control plane & WIP limits✓ Native
Cross-agent dependencies & routingPartial✓ Orchestrated
Independent reviewer quality gateSelf-reviewPR checks✓ Separate agent
Deploy + monitor in the loopVariesVia Actions✓ Built-in stages
Unified audit trail across all agentsPer-agent✓ Audit logs✓ Fleet-wide
Cost / token attribution per taskLimitedLimited✓ Per card & agent
DORA outcome reporting✓ Built-in
Model / tool agnosticOften lockedPlatform-bound✓ Portable
built-inpartial / varies— not a focus

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.

55.8%
faster task completion in a controlled Copilot study (JavaScript HTTP server task).
GitHub / Microsoft Research4
+84%
more successful builds in an enterprise Copilot study; 90% felt more fulfilled, 95% enjoyed coding more.
GitHub / Accenture5
up to 2×
faster on some tasks with genAI — docs 45–50%, new code 35–45%, refactoring 20–30% faster.
McKinsey6
84%
of developers use or plan to use AI tools — adoption is already mainstream.
Stack Overflow 20257
Read these honestly. These figures come from specific studies and tasks; results vary by team, codebase, and process — and other research (METR8, DORA3) shows AI can slow delivery or hurt stability when ungoverned. Dev Forge is the governance, observability, and measurement layer that tilts the odds toward the upside. All Dev Forge performance figures are targets to validate in your pilot — not guarantees.

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.

Weeks 1–2

Baseline & connect

  • Integrate 2–3 repos & issue tracker
  • Capture current DORA baseline
  • Define RBAC, policies & gates
  • Pick 1–2 service scopes
Weeks 3–4

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
Weeks 5–6

Close the loop

  • Add deploy & monitor stages
  • Canary + rollback on a real change
  • Incident feedback onto the board
  • Tune gates & WIP limits
Outcome

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.

Now
  • Kanban control plane & orchestration
  • Six specialist agents + Tech Lead
  • RBAC, policy & approval gates
  • Full audit trail & cost metering
  • GitHub / GitLab / Jira / Slack
Later
  • 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.