Why Is Your Project Still Late After Adopting AI Coding?

1. Work Backwards from Customer Acceptance

Choose a recently completed requirement and record approval, implementation, integration, testing, review, release and business acceptance. A request date is not necessarily the start of development, and merging code is not delivery. Record waits for client decisions, third-party access and historical-data investigations separately.

A contract lookup feature in a client portal may have a simple screen, yet require customer ownership rules, masking, API access and revocation behavior. Without owners for those dependencies, faster page generation merely creates more unvalidated work. Confirm responsibility, availability and alternative test methods before changing the toolchain.

2. Make Project Knowledge Usable for the Next Change

Manage business rules, data definitions, API contracts, build instructions, acceptance examples and past decisions separately, with owners and effective versions. Provide only relevant, authorized context for each task. Conflicting rules require business clarification; plausible model choices can produce working code that implements the wrong policy.

Reusable task instructions should specify when they apply, required inputs, permitted changes, tests and stop conditions. They may be packaged as Skills or ordinary templates. Neither grants production access. Changes to shared APIs, database structures or authorization require additional review rather than the acceptance rules for a simple page change.

3. Give Engineering Agents Reliable Validation Conditions

Define runtime versions, dependencies, build steps, sanitized data and API mocks. A fresh execution environment must not depend on hidden local files or credentials. Agents may inspect logs, change authorized files, run tests and propose patches. Missing access or test data is a blocker, not a reason to delete failing tests. Distinguish simulated tests from real integration.

As a design example, reproduce an access-control defect with an unauthorized user, add a regression test, then validate both allowed and denied roles after the fix. This is not a measured ZhiHua client result. The agent provides a proposed patch and test evidence; existing processes govern merging, migration and release. Document failures and untested conditions as well as successes.

4. Measure Delivery Outcomes, Not Code Volume

Compare similar requirements using delivery time, active effort, rework, escaped defects and total cost. Record differences in complexity, integrations and release windows before attributing changes to AI. Tool usage indicates adoption, not earlier delivery of usable features. Ranking people by generated code can encourage unnecessary output and undervalue testing or coordination.

Illustrative calculation: a task previously required 12 hours of active work. A pilot uses 7 hours for implementation and testing, 3 for review and 1 for additional maintenance, saving 1 hour rather than 5. A separate 16-hour wait for API access still affects elapsed delivery time. These fictional figures are not performance claims. Include subscriptions, model usage and environments in costs.

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5. What Outsourcing Clients Should Receive

Deliver source code with usable rights, dependencies and licenses, build and deployment instructions, migration and rollback limits, tests and known issues. For AI-assisted work, also define data access, account charges and handover of project knowledge or templates. Clients need inspectable changes and test evidence, not private model reasoning or chat histories in place of engineering records.

Do not replace every tool by default. Integrate with the client's repositories, pipelines and reviews, starting with one repository and task type. Agree which work belongs to the supplier, client business team, API provider or security administrator. Initial inquiries can use sanitized workflows and symptoms without production credentials; arrange controlled access after scoping.

Official information and scope of verification

Reference check date: 2026-10-06. Platform capabilities change with the version, the package, the area and the authority; information is used to describe technical capabilities and does not represent search volumes, the results of the customer in Sino-China or the original cooperative qualifications.

• Alibaba Technology: AI Native Engineering Handbook (external reference, not a ZhiHua case study)