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Challenge

Automated Market Intelligence Sentinel with OpenAI Agents SDK

Develop an autonomous intelligence agent designed to monitor market shifts, such as infrastructure capacity constraints mentioned in recent Seagate and energy-sector reports. Using OpenAI Agents SDK, you will build an agent capable of tracking supply-side bottlenecks and utility mergers that impact AI buildouts. The agent will autonomously route insights through Hyperbolic workflows and trigger notifications via Voiceflow interfaces when specific market thresholds are breached. This system emphasizes agent-based reasoning over static data retrieval, focusing on real-time event interpretation.

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Challenge brief

What you are building

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

Build an event-driven market monitoring agent using OpenAI Agents SDK, Gemini 3.1 Pro, and Hyperbolic orchestration to interpret AI hardware capacity news.

Delivery guide

How work is evaluated

Evaluation

Evaluation of agent autonomy in reacting to pre-defined market news events

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

LatencyCheck

Agent response under 5s

Binary check

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

Dimension 2

Accuracy

Relevance of AI insights • target: 0.9 • 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

  • Master the initialization of the OpenAI Agents SDK to manage multi-turn task loops

  • Implement Gemini 3.1 Pro as the primary inference engine for real-time market data analysis

  • Orchestrate agent state transitions using Hyperbolic to handle asynchronous market updates

  • Build a Voiceflow integration to push strategic business alerts to human stakeholders

  • Optimize agent autonomy cycles using Azure-based compute resources for low-latency response

  • Design structured tool-calling patterns using the Kiln AI agent development platform

Resources and assets

Reference links and supporting material

Dataset notes

Dataset will be provided

Challenge setup

Evaluation of agent autonomy in reacting to pre-defined market news events

Challenge input

JSON event feed

OpenAI

OpenAI AI model provider

Hyperbolic

AI infrastructure platform

Kiln AI

Tools for building AI products including

Evaluated output

Voiceflow trigger command

Evaluation checks
  • Agent response under 5s
  • Relevance of AI insights • target: 0.9 • range: 0-1
Configured evaluation evidence
  • Accuracy target: 0.9
Configured runtime
  • Python execution harness

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
  • Hyperbolic · Optional
  • Kiln AI · Optional

Evaluation contract

  • LatencyCheck · Weight 1
  • Accuracy · Weight 1

Metrics

  • Accuracy · Target 0.9

Workflow tasks

  1. Task 1

    Input: JSON event feed

    Output: Voiceflow trigger command

    Execution harness: Python

Recipe freeze marker

No recipe freeze time is recorded.

Frequently Asked Questions about Automated Market Intelligence Sentinel with OpenAI Agents SDK