PilotPlanPHASE 01
Source-backedTask-level evaluation
- Build a representative programming task set
- Compare iterative build-test-fix quality
Exit gate: Selected model meets correctness and review-effort threshold
Documented implementation, not a PilotPlan customer story
CREDAI-assisted engineering workflow
How CRED implemented an agentic engineering workflow
A documented fintech case covering model evaluation, solution discovery, build-test-fix loops, repository documentation, testing, and observability.
The problem
CRED wanted faster engineering execution while maintaining the quality and reliability expected of a financial technology platform.
How it was implemented
- 01Evaluated models for programming tasks and iterative build-test-fix work.
- 02Used Claude Code from solution discovery through coding, testing, documentation, and commits.
- 03Applied repository instructions and structured context to break complex work into smaller steps.
- 04Expanded testing and observability while enabling engineers to own lower-priority projects end to end.
Reported outcomes
Reported by Anthropic and the featured company. Not independently verified by PilotPlan.
- CRED reported two-times faster execution for features and fixes.
- The company reported a 10 percent increase in test coverage across existing codebases.
- The source reports greater testing and observability coverage and completion of work that had previously remained lower priority.
What another team can learn
- Evaluate models on the team's real development loop rather than generic benchmarks alone.
- Faster coding is useful only when tests, observability, documentation, and review also improve.
- Repository-level context and clear operating instructions are implementation work, not prompt decoration.
- Track quality and delivery outcomes alongside adoption.
Technical architecture
A simplified logical architecture reconstructed from the public case study. It is not claimed to be the company's private network diagram.
The build-test-fix loop, repository documentation, end-to-end use, and observability emphasis are documented. The exact CI system, sandbox, permissions, and deployment path are not public and are represented as recommended implementation controls.
Rollout plan
A practical sequence based on documented milestones where available, with inferred and recommended steps clearly marked.
PHASE 02
Source-backedBounded automation
- Automate a contained design workflow
- Document prompts, tests, failures, and cost
Exit gate: Stable output under repeated evaluation
PHASE 03
Source-backedDeveloper workflow
- Adopt repository instructions
- Expand from discovery through tests and commits
Exit gate: Coverage and delivery improve without higher incident risk
PHASE 04
InferredAgentic execution
- Assign lower-priority projects end to end
- Add repository-level indexing for multi-repository context
Exit gate: Review capacity, access controls, and ownership proven
Components and integrations
What the implementation needs, and how confidently the public evidence supports each element.
Claude API for parts of a design automation suite
Claude Code for discovery, implementation, testing, documentation, and commits
Repository instructions and structured context management
CI, policy checks, and human merge approval
Team and responsibilities
The accountable roles needed to build, approve, and operate this kind of system.
Engineers own task definition, review, and delivered behavior
Developer productivity team maintains instructions, evaluations, and enablement
Security and platform teams govern access, execution, and deployment
Security and operating controls
Controls explicitly documented or required to make the reconstructed implementation safe enough to operate.
Repository-specific instructions and allowed command boundaries
Required tests, observability checks, review, and rollback
No production or financial-system action without scoped authorization
Reliability and failure handling
What should happen when the model, integration, downstream system, or generated output is wrong.
Incomplete repository context: stop and request missing dependencies
Tests pass but behavior is wrong: add scenario, integration, and regression evaluations
Observability gap: block release until logs, metrics, and alerts exist
Success metrics
Published measures are separated from the additional metrics a responsible implementation should track.
Execution speed and test coverage
Review effort, defect escape rate, rollback rate, and observability coverage
Percentage of previously deferred work completed with acceptable quality
Assumptions and unknowns
Public case studies rarely disclose full architecture, permissions, evaluation data, cost, or failure rates. These gaps must be validated before treating this as an implementation specification.
- The source does not publish CRED's detailed development platform or security design.
- The two-times speed figure is company-reported and its calculation method is not disclosed.
- Future repository indexing described in the source was a roadmap item, not a confirmed completed capability.
What the source does not prove
- The figures are self-reported in an Anthropic customer story and are not independently audited here.
- The source does not disclose the evaluation dataset, baseline calculation, full costs, or production incident impact.
- Named model versions change, so teams should rerun evaluations against current options.
Primary source
PilotPlan summarized the implementation and added practical analysis. Read the original vendor-produced case study before relying on any claim.
CRED Claude case study by AnthropicQuestions about the CRED implementation
What was CRED trying to improve?
CRED wanted to accelerate research, solution discovery, implementation, testing, and fixes without reducing engineering quality.
What makes this more than code generation?
The documented workflow includes task breakdown, repository context, documentation, testing, observability, and end-to-end delivery.
How should teams compare coding models?
Use a private evaluation set based on real repositories and tasks, then measure correctness, review effort, test results, latency, cost, security, and developer acceptance.
Build an implementation plan for your actual workflow
Describe the challenge, constraints, current stack, budget, and timeline. PilotPlan researches the options and assembles a sourced implementation plan.