Question 1

What is an AI harness?

Accepted Answer

An AI harness is a structured platform layer that connects models, tools, workflows, business context, and permissions into one coherent, governed operating layer. Instead of teams building one-off agents and fragmented experiments, a harness gives an organisation reusable internal AI capability — shared skills, routing, governance, and feedback loops that every business vertical can build on.

Question 2

What does “agent proposes, verifier gates” mean?

Accepted Answer

“Agent proposes, verifier gates” is an operating pattern for dependable AI automation: the AI performs the flexible reasoning — research, drafting, transformation, generation — while deterministic validators, rules, schemas, tests, and human review gates decide whether the output is safe to proceed. It is what makes automation dependable in finance, data migration, and compliance workflows where “mostly correct” is not good enough.

Question 3

How do you move from AI pilots to production?

Accepted Answer

By treating the workflow, data, and governance as the product — not the demo. I start with the commercial problem and the operational workflow, design the architecture around data access, permissions, auditability, and failure modes, build with verifier-gated automation patterns, and then help teams actually adopt the system. Production over prototypes is the first delivery principle of every engagement.

Question 4

What does a forward-deployed AI engineer do?

Accepted Answer

A forward-deployed AI engineer works inside the client's business rather than at arm's length: sitting in the leadership conversation, defining the opportunity, designing the architecture, building the system hands-on, and rolling it out across the organisation. The role spans strategy and execution — C-suite discovery on Monday, shipping production code by Friday.

Question 5

Do you work outside IR35?

Accepted Answer

Yes. 1AYM operates as an independent consulting practice outside IR35, based in Stoke-on-Trent and working with organisations across the UK and remotely. Engagements are structured as defined-outcome consulting — discovery sprints, fixed-scope builds, platform buildouts, and rollout support — rather than disguised employment.

Question 6

Do you offer fractional AI engineering?

Accepted Answer

Yes. Alongside fixed-scope sprints, 1AYM can operate as a fractional AI engineer or fractional head of AI platform — a part-time, ongoing arrangement where I own the AI platform roadmap, build alongside your team, and provide the senior engineering judgment without a full-time hire.

Question 7

How quickly can you deliver a proof of concept?

Accepted Answer

A CFO-ready proof of concept typically takes seven days. In a recent enterprise engagement, a senior leadership conversation became a working multi-vertical AI platform proof of concept within one week — including the product architecture, demo environment, executive narrative, and rollout roadmap used to align stakeholders and secure budget.

Question 8

Which systems do you integrate AI with?

Accepted Answer

Recent work spans Snowflake, BigQuery, NetSuite, Xero, Zoho, QuickBooks, HubSpot, Greenhouse, Slack, Notion, and SCIM identity workflows, with middleware on Cloud Run, Airflow, FastAPI, and Node.js. The principle is that integration is the product: AI must live inside the tools teams already use, with idempotency, dry-run modes, audit logs, and rollback paths engineered in.

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