A self-contained senior delivery unit — engineering, product, QA, architecture — running with Metacto's purpose-built agents at one fixed monthly price. Work ships to production continuously, not on a release calendar. You buy the unit and its output, not a roster.
Bring the system and the problem · Leave with our read on the real constraint
the output of a traditionally staffed team
Senior-only pods running purpose-built agents, without the coordination drag of a bigger team. Work ships when it is ready, not when a sprint ends.
of changes clear AI review and senior sign-off
Agent-run code review, eval suites, regression coverage, and security scanning on every change, with a senior engineer accountable for what ships.
metrics every pod is measured on
Throughput shipped, cycle time from request to production, escaped defects, and movement on your business metric.
Purpose-built agents carry the work from plan to production while senior engineers own the outcome and sign off on everything that ships.
Agents carry the work, plan to production
Planning, implementation, testing, and release run as one continuous flow, not handoffs between roles waiting on stage gates.
Senior engineers own what ships
Every agent output passes senior review, and a senior engineer is accountable for the outcome. Judgment is the job, not oversight after the fact.
Pace applied to your highest-value work
Throughput goes to the roadmap items that move a business metric, executed inside your repos and release flow rather than around them.
We weight the pod around whatever is actually slowing delivery down, and the weighting changes as that does. Answer the questions in each column — the one you keep saying yes to is where you start.
Ask yourself
How the pod lands
Senior leadership carries the early weeks — roadmap triage, tech-debt reckoning, architecture decisions — while production changes are already landing. Throughput scales as the foundation sets.
It shifts when
The roadmap is trustworthy and the constraint becomes throughput.
Ask yourself
How the pod lands
Build throughput runs high and steady from day one, shipping to production continuously on a stable release flow, covering backlog ownership, feature delivery, migrations, and system expansion, with leadership held thin and constant.
It shifts when
A new system or a new bet moves the constraint back upstream.
Ask yourself
How the pod lands
A defined surge runs in parallel to whatever is already in flight, yours or ours, scoped to the date it exists for. The baseline never blinks, and the surge ends when the window does.
It shifts when
The date passes. Capacity steps back down, by design.
Product engineering
Admin portals, internal tools, workflow integrations, data pipelines.
Working systems in production.AI & agents
Copilots, AI features, and production agents with evaluations built in.
Live in production with an eval framework.Roadmap execution
Backlog ownership, releases, migrations, system expansion.
The roadmap keeps moving.Every agent is managed by the pod, not running autonomously. Senior engineers direct the work and sign off on the outcome. Agents carry it.
Planning
Opens every week with a current plan — sequenced work, estimates, and what changed — re-planned continuously as delivery reports back.
Build
Accelerates implementation inside your codebase and environment, with migration notes and a rollback path attached to the work.
Quality
Runs eval suites and regression coverage against every increment, with results attached to the weekly demo, not filed away.
Release
Carries changes to production through security scanning and release gates, with an audit trail on every ship.
How seniors and agents pair
The monthly price is fixed. What we optimize is how much shipped work fits inside it, so the question is never "how many hours did that take," it is how much moved this month.
Focused workstream
Consistent roadmap burndown: one prioritized workstream moving into production every week.
Pick this if: the backlog is clear and you need it to just keep moving.
Parallel delivery
Multiple features in parallel: two or more workstreams progressing at once without stealing from each other.
Pick this if: sequencing everything one-at-a-time is what's holding the quarter back.
Complex systems
System integration and data-heavy workloads: work crossing multiple systems, data pipelines, or ML components.
Pick this if: the hard part is everything the work touches, not the feature itself.
Platform-scale
Embedded programs: several parallel tracks run as one coordinated effort.
Pick this if: this is a program, not a project.
Each pod shape has one fixed monthly rate. What we size together is which shape and how many months, confirmed in a short scoping pass and refined as delivery reports back.
Good fit
Not a fit
A pattern joins our internal library only after it has shipped in a client's production environment, so your pod starts ahead because previous pods finished — without carrying client code, data, or proprietary IP between environments.
A working session with the people who'd run your pod. Leave with our read on the real constraint, the flavor and size that fit, and where the first production change lands — whether or not we work together.
We'll be in touch within one business day to discuss next steps.
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