Capabilities

Coding agents, MCP servers, and orchestrated subagents applied to real delivery: a working codebase, tests, and documentation at the end, not a demo.

• Agent-assisted build-out of full applications, themes, and integrations
• MCP servers that give agents safe, audited access to internal systems
• Subagent orchestration for parallel research, review, and implementation
• Human review gates at every point where an agent could get it wrong

Most enterprise AI programmes stall between the pilot and the platform. This is the work of choosing which workloads repay automation and putting governance around them before scale makes it costly.

• Assessment of which workflows repay automation, and which do not
• Tooling rollout for development teams, with standards and guardrails
• Governance and data-handling policy that survives an audit
• Enablement material so the capability stays with the team

Retrieval, tool use, and structured extraction built into applications that already exist, with the evaluation harness that shows whether it is actually working.

• Retrieval over an existing document and data estate
• Tool use and structured output wired into existing business logic
• Evaluation harnesses and regression suites for non-deterministic systems
• Cost, latency, and failure-mode engineering for production traffic

The unglamorous work AI is genuinely good at: reading a codebase nobody remembers writing, documenting it, testing it, and migrating it without a big-bang cutover.

• Codebase archaeology and documentation for systems that lost their authors
• Test coverage built retroactively so a refactor is safe to attempt
• Framework, language, and platform migrations staged for low risk
• Dependency, security, and end-of-life remediation at scale

Twenty-five years of building for the web: PHP and the LAMP stack, .NET and C#, JavaScript, and the database design underneath. Applications that get maintained, not just launched.

• PHP applications, APIs, importers, parsers, and integrations
• .NET and C# services alongside existing enterprise systems
• JavaScript front-ends, without a framework where none is warranted
• WordPress as an application platform rather than only a CMS

Python where it earns its place: automation, data processing, internal tooling, and the API and integration work that quietly keeps a business running.

• Automation and scripting that removes repeatable manual work
• Data processing, transformation, and reporting pipelines
• APIs, services, and scheduled jobs built on the standard toolchain
• Internal tooling a team can pick up, read, and extend

React Native applications built and shipped to both stores from a single codebase, including the parts that are never in the tutorial: release process, device variation, and store review.

• Cross-platform applications for iOS and Android from one codebase
• Native module integration where the platform bridge is unavoidable
• Release, signing, and store submission handled as a repeatable process
• Offline behaviour and sync against a server that is sometimes wrong

Work on data-heavy applications: schema design, query optimisation, migration between systems, and moving reporting off the spreadsheet nobody owns.

• Schema design and normalisation for applications that will grow
• Query optimisation and indexing on large, slow tables
• Data migration and import pipelines between systems
• Reporting layers that replace a spreadsheet nobody owns

The layer most application developers avoid: Linux administration, Apache and Nginx configuration, deployment, and the performance tuning users actually feel.

• Linux server administration, configuration, and hardening
• Apache and Nginx configuration, TLS, and caching strategy
• Deployment that is repeatable and written down rather than remembered
• Front-end and server-side performance measurement and tuning

The discipline that decides whether software ships at all: intake, architecture and security review, cross-team dependencies, vendor management, and status that reflects reality.

• Intake, approval, and change-control navigation
• Cross-team dependency management, where most delay actually lives
• Vendor and statement-of-work management, on both sides of it
• Steering-level reporting that does not hide bad news