Podcast Summary: Software Engineering Daily - Palantir with Akshay Krishnaswamy and Christopher Jeganathan

Release Date: November 26, 2024

In this engaging episode of Software Engineering Daily, host Sean Falconer sits down with Akshay Krishnaswamy, Chief Architect, and Christopher Jeganathan (JEG), Group Lead at Palantir Technologies. The discussion delves into Palantir's evolution, technological transformations, platform innovations like Apollo and AIP, and the integration of AI and Large Language Models (LLMs) into their offerings. Below is a detailed summary of the key topics, insights, and conclusions from their conversation.

1. Introduction to Palantir Technologies

The episode begins with Akshay providing an overview of Palantir:

Akshay Krishnaswamy [00:00]: "Palantir Technologies is a data analytics and software company specializing in building platforms for integrating, analyzing and visualizing large data sets..."

Palantir's focus spans intelligence, defense, and commercial sectors, aiming to facilitate data-driven solutions for complex problems.

2. Evolution of Palantir and Its Technology Stack

Sean Falconer initiates the conversation by exploring how Palantir has transformed over Akshay's 12-year tenure.

Chris Jeganathan [01:10]: "The company was founded in the aftermath of September 11, very much focused on a set of counterterrorism missions across US and allied governments..."

Initially built to address national security challenges, Palantir's core technology centered around data integration and enabling frontline analysts.

Transition from Desktop to Cloud

Chris elaborates on the technological shift from early Java Swing clients to modern web-based interfaces:

Chris Jeganathan [03:01]: "It started off as a set of Java services and a Java Swing client... Now, we're using a browser-based set of interfaces..."

Akshay adds:

Akshay Krishnaswamy [04:06]: "We were still using the Java Swing client when I joined, which has only recently been completely removed..."

This transition highlights Palantir's move to accommodate diverse deployment environments, including edge devices and legacy hardware.

3. Apollo Platform and Continuous Delivery

Sean inquires about managing deployments in regulated and conservative environments like government and military.

Chris Jeganathan [05:46]: "This is why we built our Apollo platform... Apollo allows us to handle continuous delivery across various constraints and environments."

Key Features of Apollo

• Microservices Architecture: Supports incremental code shipping.
• Deployment Flexibility: Manages updates in classified or disconnected networks.
• Risk Tolerance Settings: Enables tailored deployment strategies for different customers.
• Commercial Adoption: Commercial partners like Cisco leverage Apollo for complex deployments.

Akshay praises Apollo's impact on development efficiency:

Akshay Krishnaswamy [08:03]: "Apollo makes my life ridiculously easy... I can predictably manage feature deliveries and stack freezes based on customer needs."

4. Ontologies and Data Integration

Sean shifts the focus to Palantir's use of ontologies, a foundational aspect of their platform.

Chris Jeganathan [14:38]: "Our ontology started as a way to represent the world... It evolved into a decision-centric system modeling data, logic, and actions together."

Core Components of Palantir's Ontology

• Objects, Links, Properties: Traditional semantic elements.
• Behavior Modeling: Incorporates business logic and operational workflows.
• Security and Provenance: Ensures granular access controls and data lineage tracking.

Akshay emphasizes the importance of permissions:

Akshay Krishnaswamy [12:57]: "We built everything with permission as a primitive... Our system is grounded in data provenance, enhancing security and trust."

This ontology framework allows Palantir to maintain consistency across diverse industries, from defense to manufacturing.

5. Expansion into the Commercial Sector

Chris discusses Palantir's strategic shift towards commercial markets:

Chris Jeganathan [02:35]: "We've moved from defense to sectors like financial services, manufacturing with Airbus and BP, leveraging our core data integration and ontology technologies."

This diversification is driven by the adaptability of Palantir's platforms to various regulated and data-intensive industries.

6. AIP Platform and AI Integration

Sean introduces the topic of Palantir's AI platform, AIP.

Chris Jeganathan [21:02]: "AIP connects generative AI models with our existing services, enabling AI to interact with data, logic, and actions within the enterprise ontology."

Features of AIP

• Integration with LLMs: Supports models from partners like Azure (OpenAI), AWS (Anthropic), and Google Gemini.
• Security and Governance: Maintains data security within AI interactions.
• Developer Support: Provides SDKs and APIs for building AI-enabled applications.

Akshay describes the developer experience:

Akshay Krishnaswamy [28:14]: "With AIP, building AI-powered applications is streamlined... APIs are abstracted, allowing developers to focus on functionality rather than infrastructure."

7. Building AI-Powered Applications

The conversation explores how developers can leverage AIP to create intelligent applications.

Akshay Krishnaswamy [28:20]: "We can create a notes app with retrieval augmented generation, linking user queries to specific notes with provenance."

Example Use Case: Notes App

• Semantic Embedding: Enables context-aware responses.
• Provenance Linking: Ensures answers are traceable to their sources.
• Developer Flexibility: Allows the use of various frontend frameworks and languages.

Akshay highlights the ease of integrating new AI technologies:

Akshay Krishnaswamy [30:30]: "Our platform abstracts complex AI components, letting developers integrate AI functionalities seamlessly into their applications."

8. Security and Governance in AI Integration

Sean probes into how Palantir's ontology aids in addressing LLM challenges like hallucinations and data governance.

Chris Jeganathan [38:55]: "The ontology serves as a grounding system, ensuring that AI interactions adhere to defined security and operational protocols."

Mitigating LLM Risks

• Consistent World Model: Ensures AI operates within the same context as human users.
• Action Constraints: Limits AI actions to predefined, secure pathways.
• Provenance Services: Tracks AI decision-making processes for transparency.

Akshay adds to the discussion on developer confidence:

Akshay Krishnaswamy [39:08]: "We've built evaluations and test suites to ensure AI behaves deterministically where necessary, maintaining system integrity."

9. Handling LLMs and Non-Determinism

Sean raises the challenge of incorporating non-deterministic LLMs into traditional engineering workflows.

Akshay Krishnaswamy [45:15]: "We minimize risky interfaces and constrain AI interactions to safe, validated paths, akin to introducing new software tools."

Strategies Employed by Palantir

• Deterministic Testing: Ensures AI outputs meet expected criteria.
• Workflow Integration: Embeds AI within established, secure workflows.
• Risk Management: Defines clear boundaries for AI operations to prevent unpredictable behavior.

10. Target Users and Competitive Landscape

Chris elaborates on Palantir's diverse user base and how it differentiates from competitors.

Chris Jeganathan [41:47]: "Our users range from data engineers and analysts to operational personas like network operations and electrical engineers. We cater to complex, regulated environments better than typical data and analytics software."

User Personas

• Operational Users: Engineers and analysts making critical decisions.
• Technical Personas: Data engineers, application developers, and data scientists supporting operational workflows.

Competitive Edge

Palantir positions itself not just as a data platform but as an enabler for building comprehensive, secure applications tailored to complex enterprise needs.

11. Developer Platform and Customization

The discussion moves to Palantir's commitment to flexibility and customization within their developer platform.

Chris Jeganathan [35:49]: "Our platform supports various data computing engines and allows integration with existing enterprise architectures, providing seamless customization."

Key Customization Features

• Container Support: Enables users to bring their own containers.
• Language and Framework Agnostic: Supports multiple programming languages and frontend frameworks.
• API Flexibility: Offers RESTful APIs and SDKs for Python, TypeScript, and Java.

Akshay shares his developer experience:

Akshay Krishnaswamy [37:57]: "Users can bring their own models and databases, integrating them effortlessly into the ontology-driven platform."

12. Future Directions and Excitement Around AI Integration

Sean asks about the most exciting aspects of Palantir's ongoing transformation with AI.

Chris Jeganathan [47:13]: "LLMs acting as symbiotes, enhancing every part of the ontology system, allowing more interactive and intelligent applications."

Anticipated Developments

• Enhanced Application Experiences: New AI-driven interfaces and workflows.
• Deeper Integration Points: Identifying critical junctions for AI value addition.
• Continuous Learning: Leveraging forward-deployed engineers' insights to refine AI capabilities.

Akshay adds:

Akshay Krishnaswamy [49:06]: "With Palantir, setting up AI infrastructures is streamlined, accelerating the adoption of new technologies into meaningful workflows."

13. Conclusion

As the episode wraps up, Sean thanks Akshay and Chris for their insights, highlighting the transformative journey of Palantir from a defense-focused data integration company to a versatile platform harnessing the power of AI and ontologies to serve diverse, complex enterprise needs.

Key Takeaways:

• Adaptive Evolution: Palantir has effectively transitioned from desktop-based applications to cloud and edge deployments, ensuring flexibility across various environments.

• Robust Platforms: Apollo facilitates continuous delivery in regulated settings, while AIP integrates advanced AI capabilities seamlessly into enterprise workflows.

• Ontology-Centric Approach: A well-defined ontology framework underpins data integration, security, and AI interactions, providing a consistent and secure operating model.

• AI Integration with Governance: Palantir addresses LLM challenges by embedding AI within secure, deterministic workflows, enhancing trust and reliability.

• Developer Empowerment: The platform offers extensive customization and developer-friendly tools, accelerating the creation of AI-powered applications.

• Diverse User Base: Serving a wide range of operational and technical personas, Palantir stands out in accommodating complex, regulated industries.

This comprehensive discussion underscores Palantir's commitment to leveraging cutting-edge technologies to empower enterprises in making informed, data-driven decisions while maintaining stringent security and governance standards.