What we build, and why
each one is hard.
Capability and engagement model are different questions. These are what we build. How you buy them — augmentation, a managed pod, a transformation programme, a build–operate–transfer centre — is a separate decision, and the two combine freely.
Every discipline here is one we build and run ourselves. Where that is the only place we have run it, we say so.
Probabilistic systems
AI & Applied ML
LLM applications, retrieval systems, agents and applied ML built to a standard you can put in front of a regulator — with evaluation harnesses, cost controls and failure behaviour designed in rather than discovered in production.
Most AI projects do not fail on model quality. They fail because the team had no way to tell whether a change made the system better or worse, so every release was a judgement call and confidence decayed until the project was quietly shelved.
Software that acts
Agentic Systems & Automation
Systems that choose their own next step — tool-using agents, orchestrated workflows and automation that spans your existing systems — designed so that what they are permitted to do, and what happens when they are wrong, are decided up front.
The hard part of an agent is almost never the model. It is the boundary: what it may do unsupervised, how a half-finished multi-step action is recovered, and how you stop it. Most production systems marketed as agents are workflows with a model in them — and that is usually the correct design, chosen deliberately rather than by default.
Irreversible deployment
Blockchain & Smart Contracts
Protocol and application development where a deployment cannot be rolled back and a defect is a withdrawal. Contract engineering, security review, upgradeability design and the on-chain boundary decision.
Every delivery practice that assumes you can ship a fix breaks here. The response is not to slow everything down — it is to move the iteration upstream, where it is cheap, and make the irreversible step the smallest and best-verified thing you do.
Gated releases
Mobile & Cross-Platform
iOS, Android and cross-platform applications delivered continuously despite a third party sitting between your merge and your users — staged rollouts, feature flags, release trains and a native-versus-cross-platform decision made on economics.
Mobile is the one place where someone else owns your release path. Teams that treat store review as an immovable wall end up with monthly batches and mobile as the slowest thing they own. Teams that engineer around it ship weekly and decouple release from reveal.
The paved road
Platform & Data
The substrate the other three stand on: cloud infrastructure, deployment pipelines, observability, data platforms and the internal paved road that determines how fast every team above it can move.
Platform work is the highest-leverage investment available to a delivery organisation and the easiest to defund, because its return shows up as other teams being faster rather than as anything the platform team can point at. Measure it as adoption and friction removed, or it will be cut.
Software that moves
Robotics & Embedded
ROS2 applications, perception and state estimation, embedded and motor control, and the simulation-first workflow that lets behaviour be proven in a simulator where failure costs nothing before it meets hardware.
A bug in a web application prints a stack trace. A bug in a robot moves something. The response is not more caution at deployment time — it is to move the iteration into a simulator where it is cheap, and to measure the gap to the real system honestly rather than assert it is small.
Evidence over opinion
Delivery Telemetry & Observability
Checks, runs, metrics and incidents across web, publishing, AI and blockchain systems — flow metrics with their denominators, daily verification of live products, and alerting designed not to cry wolf.
Most organisations argue about delivery performance from memory. Telemetry ends the argument. A monitoring system that reports green because it has not heard anything is worse than no monitoring, and a flow metric reported without its denominator is worse than no metric.
The work between the systems
Workflow Automation & Integration
Integration between the systems you already run, scheduled jobs with named ownership, cross-system reactions and the auto-recovery that keeps them honest — because an automation that fails silently is worse than no automation.
The expensive work in most organisations is not inside any system. It is the copying, the chasing, and the scheduled job nobody owns. It is also the easiest of it to make disappear — and the easiest to make disappear badly, because an automation that fails silently is worse than the manual process it replaced.
Publishing at cadence
Content Platforms & CMS
Ghost and headless CMS work, editorial workflow and scheduled publication, membership and subscription publishing, and the migrations that move a publication between platforms without losing URLs or archives.
A publication is a delivery problem in different clothes. Something has to ship on a schedule, through review, under a brand, to an audience that notices when it does not. The practices that make a publication reliable are the same ones that make a software system reliable; the vocabulary is different.
How the two combine
Capability × engagement model
Any capability can arrive through any engagement model. The capability decides who we put on it; the model decides what we are accountable for and how it ends.
| Capability | Team Augmentation | Managed Pods | Delivery Transformation | Build–Operate–Transfer | AlphaScrum Academy |
|---|---|---|---|---|---|
| AI & Applied ML | Yes | Yes | Yes | Yes | Curriculum |
| Agentic Systems & Automation | Yes | Yes | Yes | Yes | Curriculum |
| Blockchain & Smart Contracts | Yes | Yes | Yes | Yes | Curriculum |
| Mobile & Cross-Platform | Yes | Yes | Yes | Yes | Curriculum |
| Platform & Data | Yes | Yes | Yes | Yes | Curriculum |
| Robotics & Embedded | Yes | Yes | Yes | Yes | Curriculum |
| Delivery Telemetry & Observability | Yes | Yes | Yes | Yes | Curriculum |
| Workflow Automation & Integration | Yes | Yes | Yes | Yes | Curriculum |
| Content Platforms & CMS | Yes | Yes | Yes | Yes | Curriculum |
The one exception is the Academy, which teaches delivery practice rather than supplying engineers — though each capability contributes its own module, because verification looks different when the thing you are verifying is probabilistic, irreversible or gated behind a third party.