Agents are transforming the engineer's role. Leadership must change with it.
Episode 3
Episode summary
Michael Tweed is a principal software engineer helping lead AI adoption across Skyscanner’s engineering organization. After four years of experimentation, Skyscanner has moved beyond treating AI as an individual productivity tool: agents now help generate specifications, implement changes, review code, run validation loops and work across repositories.
In this episode, Michael explains what that transition means for engineering leaders and for the responsibilities of developers themselves. We discuss how Skyscanner turns local experimentation into shared capability through an AI champions network, skills marketplace and central configuration; why engineers increasingly review specifications and outcomes rather than every line of code; and how standards, curated knowledge and deterministic verification make greater autonomy possible. Michael also describes the move towards cloud-based orchestration, the human checkpoints required for larger work and why the engineer’s role is changing rather than disappearing.
About Michael
Michael Tweed is a principal software engineer at Skyscanner, working across its engineering platforms on AI adoption and developer experience. He began in mobile engineering before moving into mobile platform and developer-experience work. He now helps shape how several hundred Skyscanner engineers use agents, shared skills, organizational standards and validation systems to build software at scale.
In this episode
- 00:16 — Introducing Michael Tweed and AI adoption at Skyscanner
- 01:02 — From mobile engineering to cross-platform developer experience
- 02:12 — Four years of AI adoption, from autocomplete to agents
- 04:37 — Crossing the threshold: generated code is already in production codebases
- 05:23 — Matching models and tools to the task
- 06:19 — From individual workflows to shared skills and cloud sessions
- 07:36 — A light-touch rollout and Skyscanner’s AI champions network
- 09:03 — Central configuration, cost visibility and a consistent experience
- 10:22 — Why skills need evaluations and should be treated like code
- 11:20 — Benchmarking models against Skyscanner’s own technology
- 14:53 — Sensible defaults, engineer choice and a culture of cost awareness
- 17:36 — Specification-driven development without one mandated workflow
- 19:02 — Reviewing the specification rather than every line of code
- 19:32 — Base and team-specific AI reviews for pull requests
- 20:57 — Should agents choose the architecture they know best?
- 21:33 — Measurable production standards and agent-accessible context
- 22:32 — Different boundaries for internal tools and traveller-facing systems
- 24:39 — Why connecting an agent to every document does not work
- 25:38 — Curating organisational knowledge for agents
- 28:11 — The incident where an agent changed a test to make it pass
- 30:05 — Moving verification into agentic development loops
- 31:28 — Tests, linting and SonarQube as independent evidence
- 33:00 — Moving agent work from laptops into cloud orchestration
- 35:21 — From autonomous tasks to multi-stage work with human checkpoints
- 37:26 — Legacy modernization and coordinated changes across repositories
- 39:41 — Training, onboarding and the changing role of engineering
- 41:10 — Product mindset, decision boundaries and organisational ways of working
- 43:29 — Extending validation into production without sacrificing reliability
Key ideas
- Agent adoption at organizational scale is not principally a tool rollout. Leaders have to change the engineering environment around a changing division of work.
- Skyscanner combines distributed experimentation with shared infrastructure. Its AI champions network surfaces useful practices that central teams can make repeatable through skills, configuration and platforms.
- As agents perform more implementation, engineers increasingly concentrate on intent, specifications, architecture, constraints, verification and product outcomes.
- Autonomy should reflect consequence. Skyscanner gives internal tools more freedom while preserving deliberate architectural and operational standards in traveller-facing systems.
- Organisational knowledge must be curated before agents can rely on it. An old draft or abandoned proposal can be actively harmful when retrieved as authoritative context.
- Skills and agent configuration are engineering assets. Evaluations, internal benchmarks and cost visibility help teams judge whether those assets genuinely improve their work.
- Passing checks are not sufficient if an agent can weaken the evidence. Verification loops need explicit boundaries, deterministic tools and independent signals.
- Cloud orchestration allows agents to work for longer and across repositories, but larger, multi-stage work needs clear human checkpoints before consequential transitions.
- The engineer’s role is changing rather than disappearing: towards defining outcomes, designing the development system and knowing when human judgement must interrupt autonomy.
