Habi AI Challenge 2025:

Prompt Engineering for AI-supported Local Climate Change Adaptation Planning for BARMM

The Prompt Engineering for AI-Supported Local Climate Change Adaptation Plans (LCCAPs) Challenge invites innovators, AI practitioners, local government leaders, researchers, and climate advocates to develop effective AI prompts that enable local government units (LGUs) in the Philippines to co-create data-driven, actionable, and community-driven climate adaptation plans using generative AI models.

By leveraging prompt engineering, participants will optimize AI tools to support evidence-based decision-making, multi-stakeholder engagement, and localized climate resilience strategies for municipalities facing climate-related challenges such as flooding, drought, rising sea levels, and extreme weather events.

Challenge Objectives

1. Enhance Climate Adaptation Planning: Develop AI-driven prompts that assist Philippine municipalities in generating high-quality climate vulnerability assessments, risk mitigation strategies, and adaptation policies aligned with national and international climate frameworks.

2. Optimize AI for Local Contexts: Ensure that AI-generated outputs reflect local realities, indigenous knowledge, and grassroots priorities, enabling LGUs to develop community-centered adaptation strategies.

3. Improve Data Accessibility & Usability: Facilitate LGUs’ use of AI to analyze climate data, geospatial information, and risk projections, making climate adaptation planning more accessible and actionable.

4. Foster Open Innovation & Collaboration: Encourage cross-sector partnerships among local government units, academia, civil society, and AI developers to co-create adaptive climate solutions.

Who Can Participate?

This challenge is open to:
AI enthusiasts, developers, and prompt engineers
Local government officials and planners
Climate scientists and environmental researchers
Academics and students in AI, data science, and public policy
Civil society organizations (CSOs) and community leaders
Startups and tech companies focused on AI for good

Challenge Scope & Tracks

Participants can choose to develop AI prompts in any of the following tracks:

Track 1: Climate Vulnerability & Risk Assessment

Develop AI prompts that guide LGUs in generating localized risk profiles, identifying climate hazards, vulnerable populations, and critical infrastructure at risk.

Track 2: Policy & Governance for Climate Adaptation

Create prompts that assist LGUs in drafting evidence-based climate adaptation policies, including funding mechanisms, governance structures, and local ordinances aligned with the Philippine Climate Change Act and global frameworks.

Track 3: Nature-Based Solutions & Resilience Building

Engineer prompts that help LGUs identify, design, and assess the feasibility of nature-based solutions such as mangrove restoration, agroforestry, and sustainable land-use planning.

Track 4: Community Engagement & Participatory Planning

Develop AI-generated tools that help LGUs facilitate community consultations, integrate indigenous and local knowledge, and promote climate literacy among stakeholders.

Track 5: AI-Powered Decision Support Systems

Optimize AI prompts that enhance LGU decision-making by synthesizing climate datasets, generating scenario-based analyses, and recommending tailored adaptation interventions.

Challenge Formats: No Code and Code for AI-Supported Local Climate Change Adaptation Plans in BARMM

The Prompt Engineering for AI-Supported Local Climate Change Adaptation Plans (LCCAPs) Challenge is designed to empower Local Government Units (LGUs) in the Bangsamoro Autonomous Region in Muslim Mindanao (BARMM) with AI-driven tools to develop their Local Climate Change Adaptation Plans (LCCAPs).

Participants can choose between two tracks based on their expertise:

1. No Code Track: AI-Powered Climate Planning through Prompt Engineering

This track is for local government officials, planners, researchers, community leaders, and climate advocates who want to use AI for climate adaptation planning without needing coding skills.

What Participants Will Do:

• Develop AI prompts that guide generative AI models (e.g., ChatGPT, NotebookLM, Gemini, Bard, Claude) to create LCCAPs tailored for BARMM municipalities.

• Test and refine AI-generated content to ensure contextual relevance, alignment with BARMM’s environmental and socio-political realities, and usability for LGUs.

• Submit a set of AI prompts and sample AI-generated outputs for key sections of an LCCAP, including climate risk assessment, adaptation strategies, and policy recommendations.

Ideal Participants:

Local government officers in BARMM
Academics, researchers, and policy experts in climate adaptation
Urban and rural planners
Community leaders and CSOs
AI enthusiasts with no coding experience

Example Outputs:

• A prompt sequence that generates climate risk profiles for BARMM municipalities based on location-specific hazards.

• A structured prompt that helps LGUs draft BARMM-compliant climate adaptation policies integrating Islamic environmental stewardship principles.

• An AI-generated public consultation guide for engaging communities in adaptation planning.

2. Code Track: AI-Powered Tools for Climate Adaptation Planning

This track is for AI engineers, developers, data scientists, and software innovators who want to build custom AI-powered applications that help LGUs in BARMM develop and implement their LCCAPs.

What Participants Will Do:

• Build AI-powered web tools, dashboards, or mobile applications that assist LGUs in analyzing climate data, identifying risks, and drafting their LCCAPs.

• Develop custom AI models, APIs, or machine learning tools that generate localized climate adaptation recommendations for BARMM municipalities.

• Integrate geospatial climate data, disaster risk maps, and policy frameworks into AI-driven platforms for LGU decision-making.
  
  

Ideal Participants:

AI engineers and developers
Data scientists and GIS specialists
Climate-focused tech startups
University research teams
Software developers interested in AI for governance

Example Outputs:

• A chatbot assistant that helps LGUs create customized LCCAPs based on AI-generated insights.

• An AI-powered dashboard that integrates BARMM climate data, early warning systems, and best practices for adaptation planning.

• A machine learning model that predicts flood risks, drought patterns, or storm surges for BARMM municipalities.
  
  

Empowering BARMM LGUs with AI-Driven Climate Solutions

Both tracks contribute to equipping BARMM municipalities with AI-driven LCCAPs, ensuring that their adaptation strategies are:
Data-driven and informed by climate science
Contextually relevant to BARMM’s socio-political and ecological landscape
Community-centered and inclusive of indigenous and local knowledge

Choose your track and help BARMM LGUs build climate resilience through AI! 

Challenge Format & Timeline

 Launch Date: [To be determined]
Submission Deadline: [To be determined]
Evaluation & Selection: [To be determined]
Winners Announcement & Showcase: [To be determined]

Submission Guidelines

Participants must submit:
A set of AI prompts tailored to a specific track
A brief explanation (max 1,000 words) of how the prompts function and their expected impact
(Optional) Sample AI-generated outputs using the prompts
(Optional) Case study applications in a specific municipality

Evaluation Criteria

Submissions will be assessed based on:
Effectiveness & Clarity – How well the prompts generate relevant, actionable, and localized AI outputs
Usability for LGUs – How accessible and practical the prompts are for municipal governments
Innovation & Creativity – How unique and forward-thinking the approach is
Scalability & Replicability – Potential for adaptation across different Philippine municipalities

Prizes & Opportunities

 Winning teams will receive:
Opportunities to collaborate with Philippine LGUs on real-world implementation
Opportunities to showcase their projects at climate action summits and innovation forums 

How to Join?

 Stay tuned for registration details! Interested participants may pre-register at [Website or Email] to receive updates.

 Join us in revolutionizing climate adaptation planning through AI and prompt engineering!

Local Climate Change Adaptation Manuals

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