Build AI search that can show where its answer came from
Design retrieval around authoritative sources, useful passages, current permissions, and separate tests for search quality and answer quality.
A practical field guide to delegating real work to AI agents, with an example operating contract, review gates, and evidence that a task is actually complete.
Go beyond the generated demo with a small build brief, an end-to-end acceptance matrix, and an operating handoff for an application someone can maintain.
Design a workflow around completed work, with stable identities, durable state, safe retries, owned exceptions, and a practical failure-test matrix.
Build a reusable context packet that connects the decision, source evidence, examples, and evaluation criteria instead of relying on a growing list of prompt tricks.
Design retrieval around authoritative sources, useful passages, current permissions, and separate tests for search quality and answer quality.
An agent can find the right tool and still make the wrong change. Design the contract that connects intent, permission, execution, and a verifiable result.
The hard part of AI media is deciding what belongs in the finished piece. Build a production process for consistent assets, truthful claims, accessible delivery, and measurable usefulness.
Natural speech is only one part of a good voice experience. Design interruptions, confirmations, tool failures, and human handoffs before giving an agent a real phone line.
Reading a PDF is not the same as producing a trustworthy business record. Keep the source, extracted value, validation, and review decision connected from intake to export.
A model that runs on your laptop is only the beginning. Evaluate the whole local workflow: task quality, memory, privacy boundaries, operating effort, and recovery when it fails.