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Going from prompts to self-healing agents in production
See how to build a useful, self-healing agent from prompts in under five minutes using PostHog's no-code agent builder, with insights for creating your own agent builders.
I’m going to demo PostHog’s new agent builder product, which is a no-code (do we even still say that? are we even coding anymore?) tool for turning your prompts into running agents without needing to know or care about the underlying infrastructure. My demo is to just build an example agent – we should be able to ship a useful one in less than 5 minutes.
Generated 6 days ago
Dylan, an AI team lead, presents a pre-release agent builder designed to simplify agent creation and deployment. Addressing the complexity of managing infrastructure, execution runtimes, and tool integrations, the system allows developers to define agents using simple prompts, tools, and custom models. Dylan demonstrates a command-line interface that generates agent configurations and provisions a runtime environment. He showcases a user interface for monitoring active sessions, tracking tool calls, analyzing execution logs, and calculating API costs. The audience learns how this platform abstracts backend complexities, enabling developers to easily build, test, and monitor non-deterministic agents.
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- PostHog AI GatewayPostHog AI Gateway is a developer-focused observability and routing pipeline that captures, traces, and monitors LLM application performance directly alongside user product analytics.PostHog AI Gateway unifies your AI engineering stack by bridging the gap between LLM performance and real-world user behavior. Instead of managing separate, disconnected silos for LLM metrics and product telemetry, the gateway captures every prompt, response, and token count (including spans and traces from providers like OpenAI, Anthropic, and Vercel AI SDK) and automatically maps them to your existing PostHog user profiles. This setup lets you trace an LLM hallucination directly to a user's session replay, run prompt A/B tests on live traffic, and monitor exact token costs down to the individual customer account.
- NodeNode.js is a high-performance JavaScript runtime built on the V8 engine for executing scalable network applications.Ryan Dahl launched Node.js in 2009 to rethink server-side concurrency. It utilizes an event-driven, non-blocking I/O model to manage thousands of concurrent connections on a single thread. The system runs on Google's V8 engine (C++) and provides access to npm (a registry with over 2 million packages). Companies like Netflix and LinkedIn use it for its speed and scalability: it remains the top choice for real-time data streaming and microservices.
- DjangoDjango is the 'batteries included' Python web framework: high-level, secure, and engineered for rapid, pragmatic development.Django is a high-level Python web framework, built on the 'Don't Repeat Yourself' (DRY) principle, designed to expedite the creation of complex, database-driven applications. It ships with a comprehensive suite of components out-of-the-box: a powerful Object-Relational Mapper (ORM), a robust authentication system, URL routing, and a dynamic, automated admin interface (CRUD operations). This integrated approach minimizes boilerplate code and development time, which is why major platforms like Instagram, Mozilla, and Disqus trust Django for scalable, secure web services.
- KafkaApache Kafka is the distributed event streaming platform: it publishes, stores, and processes trillions of events per day with high-throughput and low-latency performance.Kafka is your core nervous system for data: a distributed, fault-tolerant platform for real-time stream processing. It handles data ingestion and delivery at scale, moving millions of records per second across a cluster of brokers. We manage event streams via partitioned Topics, leveraging the core Producer and Consumer APIs for high-volume exchange. For complex ETL and microservices, the Kafka Connect and Kafka Streams APIs provide built-in tools for integration (e.g., Postgres, S3) and stateful processing (joins, aggregations). Over 80% of Fortune 100 companies trust Kafka for mission-critical, event-driven architectures.
- ClickHouseAn open-source, columnar OLAP DBMS: engineered for lightning-fast, real-time analytics on petabytes of data.ClickHouse is the high-performance, open-source columnar DBMS built for Online Analytical Processing (OLAP). Its architecture, featuring columnar storage and vectorized query execution, is specifically engineered to handle massive data volumes: think billions of rows and petabytes of data. This design enables lightning-fast, real-time analytical queries using standard SQL. It is a proven solution for real-time monitoring, log analytics, time-series data, and large-scale business intelligence (BI) workloads.
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