DeopShift · A Deop Framework · Agentic SDLC

Make agents part of the team.

AI coding agents now take issues and open pull requests. The question stopped being “should developers use AI” — it’s “how does a team work when some of its members are agents.” DeopShift gets you there safely: assessment first, quality-gated rollout, measured results.

Microsoft Solutions Partner — Cloud & AI Platforms — Specialist: Agentic DevOps with Microsoft Azure and GitHub
GitHub Verified Partner

+21%

individual task output with AI assistants — the real, measured lift

Flat

organizational delivery on unmanaged rollouts — the bottleneck moved

~27%

of new production code industry-wide is AI-generated

46–90%

task-level gains on tests, docs, and migrations — when teams are set up for it

Honest numbers, said out loud — and the teams that build with Deop

Globys
iMDsoft
Volaris Group
Vela Software Group
Intellicene
Optimal Blue
Trisura
The research behind these numbers: Agentic SDLC, explained →

The idea

Treat agents like hires, not features.

New team members get onboarding docs, scoped responsibilities, a review bar, and performance measurement. DeopShift gives agents the same: instructions files that teach your repos, custom agents with defined roles, one review standard for human and agent code, and team-level scorecards baselined before rollout.

Licenses are bought. Autocomplete is adopted. Delivery hasn’t moved — because the bottleneck relocated into work definition, review capacity, and governance. More tooling can’t fix that. Team design can. That’s what DeopShift installs.

How it works

Five levels, one gated path

Where teams start

L0 Unassisted

L1 Assisted · autocomplete

Plateaued Copilot pilots

Unmanaged agent use

Review bottlenecks

No baseline metrics

The DeopShift path

Assess — 2 weeks: every team placed on the maturity model, weakest link named

Pilot — 14 weeks: L2 Delegated → L3 Orchestrated, behind quality gates

Scale — onboarding waves run by your own certified champions

L4 Team-integrated

✓ Agents hold real team responsibilities

✓ One review bar — human and agent

✓ Team scorecards vs. baseline

✓ Expansion gated on change failure rate

Your level is your

weakest dimension

— adoption is gated by the weakest link, so that’s what gets fixed first

The offers

Start with two weeks — every step earns the next

1 · Assessment — start here

Two weeks, fixed fee — C$18–30K / US$15–25K. The entry point, fully credited against a pilot within 60 days.

Every team placed on the 5-level maturity model

Weakest link named per team, with evidence

Repo scan + flow baseline from your own data

A 90-day roadmap that’s yours regardless

2 · Pilot

Fourteen weeks standard (12–16 by team count). One to three teams to safe delegation — and a scale decision backed by your own data.

Governance & working agreements installed

Starter kit: instructions files, custom agents, CI gates

Role-based training + weekly coaching

Monthly team scorecards vs. baseline

3 · Modernization

Agent-accelerated legacy work — run entirely inside your GitHub org.

Estate discovery: 3–6 weeks, fixed fee

Requirements reverse-engineered from code

Migration waves priced per unit

Characterization tests before any change

4 · Scale

Waves of team onboarding run increasingly by your own people — self-sufficiency is the promise.

Onboarding waves: 5–10 teams per 6 weeks

Champions certified to run the framework

Advisory: two quarters, renewed against exit criteria

Deop’s involvement tapers by design

Gated, not hyped

Quality gates are in the contract

Delivered with

Microsoft

+

GitHub

1

Baseline

Two weeks: maturity scored across six dimensions, flow metrics pulled from your own repos — before any rollout.

2

Gate

Expansion freezes if change failure rate rises — it’s in the contract. Team-level metrics only; never individual surveillance.

3

Delegate

Agents take real issues behind branch protection, required reviews, and CI gates — one review bar for human and agent code.

4

Measure

Monthly scorecards against the baseline: DORA four keys, review latency, agent share — a scale decision on your own data.

The path

Six months to a scale decision — on your own data

2 wks → 14 wks → decision

Two weeks to know where you stand. A 14-week pilot takes two teams to safe delegation. Then a scale decision backed by your own scorecards — not vendor benchmarks.

Weeks 1–2 · Assessment

maturity scored · weakest link named · 90-day roadmap delivered

Weeks 3–16 · Pilot

starter kit installed · delegation ramps behind gates · monthly scorecards

Quarter 3+ · Scale

waves of 5–10 teams · champions certified · advisory tapers

↻ Every phase earns the next — the assessment fee is fully credited against the pilot

How we’re different

Native, proven, and audited

Native, not locked-in

Delivered on GitHub Copilot, coding agent, Agent HQ, Actions, and Spec Kit — the stack you already license. Every artifact lands in your repos and your tenant. No Deop platform, by design.

Proven on ourselves

We run DeopShift on Deop’s own repositories — same starter kit, same working agreements, same scorecards. Ask to see the delegation log, including the failures.

The audited specialization

Deop holds the Microsoft Agentic DevOps with Azure and GitHub specialization — independently audited, and exactly this work. Delivered with Microsoft and GitHub.

We went first

Deop ran DeopShift on Deop

Every

delegation logged — predicted vs. actual, iterations to merge

Both

merges and rejections kept — rejection is cheap by design

1

review bar — the same one we install with clients

“Before asking any client to work this way, we did — on our own repositories, with the same starter kit, working agreements, and scorecards we install with clients. The log is real: merges, rejections, and the instructions-file fix each failure produced. Ask to see it — especially the failures.”

Questions leaders ask us

The objections we hear first

Will this replace our developers?

No — it changes what they spend time on. Work shifts toward definition and review; those become the scarce skills, and DeopShift trains and measures for them explicitly.

We rolled out Copilot and plateaued. Why would this be different?

A plateau after autocomplete is the normal L1 wall — a team-design problem, not a tooling problem. The assessment locates the weakest dimension per team; the pilot fixes that first, behind quality gates.

Do you measure individual developers?

Never. Team-level metrics only, baselined before rollout — and that’s contractual. Surveillance metrics kill the trust adoption depends on.

We’re in a regulated industry. Can we do this safely?

Yes — everything runs inside your GitHub org and your tenant, under your existing controls. PIPEDA and Quebec Law 25 alignment is documented in every governance deliverable.

What does it cost?

The assessment is fixed-fee — C$18–30K / US$15–25K by team count — and fully credited against a pilot within 60 days. Pilot and modernization are quoted precisely after a 30-minute discovery call.

Which tools does this cover?

GitHub-native first: Copilot, coding agent, Agent HQ, Actions, Spec Kit, and GitHub’s enterprise AI controls. The framework itself is tool-agnostic — Claude Code and other agents slot into the same working agreements when your teams sanction them.

Start with two weeks.

One fixed price, one fixed calendar — every team placed on the maturity model, the weakest link named, and a 90-day roadmap you keep either way.

Book the 2-week assessment →