Skip to main content
Back to challenges
Challenge

Build Dynamic Homebuyer Incentive Matching Engine using OpenAI Agents SDK

To convert prospective buyer interest into completed sales amidst high interest rates, homebuilders offer dynamic incentives (e.g., closing cost credits, rate buydowns, appliance upgrades). Developers will construct an autonomous incentive matching engine using OpenAI Agents SDK. The agent analyzes individual buyer financial constraints, preferences, and builder inventory gross margins to dynamically synthesize the optimal incentive package that closes the sale while preserving builder profitability.

Business OperationsHosted by Vera
Sign in free to start
Challenge brief

What you are building

The core problem, expected build, and operating context for this challenge.

Construct an autonomous buyer incentive matching agent using OpenAI Agents SDK to maximize homebuilder sales conversions.

Delivery guide

How work is evaluated

Evaluation

Evaluates buyer acceptance score and builder gross margin retention.

Datasets

Challenge datasets

Public datasets, plus the private datasets you have access to.

Evaluation rubric

How submissions are scored

These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.

Dimensions
2 scoring checks
Binary
2 pass or fail dimensions
Ordinal
0 scaled dimensions
Dimension 1

Margin Threshold Validation

Verifies builder post-incentive margin remains above 20%

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Dimension 2

Incentive Fit Score

Match quality between incentive type and buyer deficit • target: 0.95 • range: 0-1

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Learning goals

What you should walk away with

  • Implement multi-turn agent interaction loops using OpenAI Agents SDK

  • Build custom tool calls to calculate builder margin preservation after incentives

  • Synthesize custom incentive offers tailored to buyer rate-sensitivity profiles

  • Automate CRM contract generation triggers for sales managers

Resources and assets

Reference links and supporting material

Dataset notes

Dataset of 50 buyer negotiation logs with target home price, builder cost basis, and rate sensitivity thresholds.

Challenge setup

Evaluates buyer acceptance score and builder gross margin retention.

Challenge input

JSON with list_price, builder_cost, buyer_monthly_deficit, max_incentive_budget

OpenAI Agents SDK

Required framework for agent creation.

Evaluated output

JSON with selected_incentive, incentive_value, post_incentive_margin_pct, conversion_likelihood

Evaluation checks
  • Verifies builder post-incentive margin remains above 20%
  • Match quality between incentive type and buyer deficit • target: 0.95 • range: 0-1
Configured evaluation evidence
  • Benchmark: IncentiveOptimizationBench
  • Incentive Fit Score target: 0.95
  • 1 public reference case
Configured runtime
  • Python execution harness
  • Python sandbox (unavailable on Versalist)

Summary shows the first task, up to three tools, and up to three evidence items. Open the technical recipe to view all configured items.

View technical recipe

Configured tools

Action Space
  • OpenAI · Required
  • RAI · Optional
Observation
  • Braintrust · Optional
Reward / Eval
  • Braintrust · Optional

Evaluation contract

  • Margin Threshold Validation · Weight 1
  • Incentive Fit Score · Weight 1

Metrics

  • Incentive Fit Score · Target 0.95

Benchmarks

  • IncentiveOptimizationBench
  • general

Reference cases

  • 1 public reference case

Workflow tasks

  1. Task 1

    Input: JSON with list_price, builder_cost, buyer_monthly_deficit, max_incentive_budget

    Output: JSON with selected_incentive, incentive_value, post_incentive_margin_pct, conversion_likelihood

    Execution harness: Python

Evaluation tools

  • OpenAI Agents SDK · Agent Framework

Recipe freeze marker

No recipe freeze time is recorded.

Frequently Asked Questions about Build Dynamic Homebuyer Incentive Matching Engine using OpenAI Agents SDK