The Helicone Blog
Thoughts about the future of AI - from the team helping to build it.
Comparing CrewAI vs. AutoGen for Building AI Agents
CrewAI and AutoGen are two notable frameworks in the AI agent landscape. We will cover the key differences, example implementations and share our recommendations if you are starting out in agent-building.
Lina Lam
Out with Golden Datasets: Here's Why Random Sampling is Better
Crafting high-quality prompts and evaluating them requires both high-quality input variables and clearly defined tasks. In a recent webinar, Nishant Shukla, the senior director of AI at QA Wolf, and Justin Torre, the CEO of Helicone, shared their insights on how they tackled this challenge.
Lina Lam
Building a RAG-Powered PDF Chatbot with LLMs and Vector Search
Build a smart chatbot that can understand and answer questions about PDF documents using Retrieval-Augmented Generation (RAG), LLMs, and vector search. Perfect for developers looking to create AI-powered document assistants.
Kavin Desi
Choosing Between LlamaIndex and LangChain
Building AI agents but not sure which of LangChain and LlamaIndex is a better option? You're not alone. We find that it’s not always about choosing one over the other.
Lina Lam
Top 10 AI Inferencing Platforms in 2024
In this guide, we compare features, pricing, and performance of top OpenAI alternatives to help you choose the best AI Inference APIs for your projects.
Lina Lam
The Case Against Fine-Tuning
Discover the strategic factors for when and why to fine-tune base language models like LLaMA for specialized tasks. Understand the limited use cases where fine-tuning provides significant benefits.
Justin Torre
Debugging RAG Chatbots and AI Agents with Sessions
Have you ever wondered at which stage in the multi-step process does your AI model start hallucinating? Perhaps you've noticed consistent issues with a specific part of your AI agent workflow?
Lina Lam
Braintrust Alternative? Braintrust vs Helicone
Compare Helicone and Braintrust for LLM observability and evaluation in 2024. Explore features like analytics, prompt management, scalability, and integration options. Discover which tool best suits your needs for monitoring, analyzing, and optimizing AI model performance.
Cole Gottdank
Optimizing AI Agents: How Replaying LLM Sessions Enhances Performance
Learn how to optimize your AI agents by replaying LLM sessions using Helicone. Enhance performance, uncover hidden issues, and accelerate AI agent development with this comprehensive guide.
Cole Gottdank
What We've Shipped in the Past 6 Months
Join us as we reflect on the past 6 months at Helicone, showcasing new features like Sessions, Prompt Management, Datasets, and more. Learn what's coming next and a heartfelt thank you for being part of our journey.
Cole Gottdank
Prompt Engineering: Tools, Best Practices, and Techniques
Writing effective prompts is a crucial skill for developers working with large language models (LLMs). Here are the essentials of prompt engineering and the best tools to optimize your prompts.
Lina Lam
Five questions to determine if LangChain fits your project
Explore five crucial questions to determine if LangChain is the right choice for your LLM project. Learn from QA Wolf's experience in choosing between LangChain and a custom framework for complex LLM integrations.
Cole Gottdank
6 Awesome Platforms & Frameworks for Building AI Agents (Open-Source & More)
Today, we are covering 6 of our favorite platforms for building AI agents — whether you need complex multi-agent systems or a simple no-code solution.
Lina Lam
Portkey Alternatives? Portkey vs Helicone
Compare Helicone and Portkey for LLM observability in 2024. Explore features like analytics, prompt management, caching, and integration options. Discover which tool best suits your needs for monitoring, analyzing, and optimizing AI model performance.
Cole Gottdank
5 Powerful Techniques to Slash Your LLM Costs by Up to 90%
Building AI apps doesn't have to break the bank. We have 5 tips to cut your LLM costs by up to 90% while maintaining top-notch performance—because we also hate hidden expenses.
Lina Lam
Behind 900 pushups, lessons learned from being #1 Product of the Day
By focusing on creative ways to activate our audience, our team managed to get #1 Product of the Day.
Lina Lam
How to Win #1 Product of the Day on Product Hunt
Discover how to win #1 Product of the Day on Product Hunt using automation secrets. Learn proven strategies for automating user emails, social media content, and DM campaigns, based on Helicone's successful launch experience. Boost your chances of Product Hunt success with these insider tips.
Cole Gottdank
Helicone vs. Arize Phoenix: Which is the Best LLM Observability Platform?
Compare Helicone and Arize Phoenix for LLM observability in 2024. Explore open-source options, self-hosting, cost analysis, and LangChain integration. Discover which tool best suits your needs for monitoring, debugging, and improving AI model performance.
Cole Gottdank
Langfuse Alternatives? Langfuse vs Helicone
Compare Helicone and Langfuse for LLM observability in 2024. Explore features like analytics, prompt management, caching, and self-hosting options. Discover which tool best suits your needs for monitoring, analyzing, and optimizing AI model performance.
Cole Gottdank
4 Essential Helicone Features to Optimize Your AI App's Performance
This guide provides step-by-step instructions for integrating and making the most of Helicone's features - available on all Helicone plans.
Lina Lam
How to redeem promo codes in Helicone
On August 22, Helicone will launch on Product Hunt for the first time! To show our appreciation, we have decided to give away $500 credit to all new Growth user.
Lina Lam
The LLM Stack: A New Paradigm in Tech Architecture
Explore the emerging LLM Stack, designed for building and scaling LLM applications. Learn about its components, including observability, gateways, and experiments, and how it adapts from hobbyist projects to enterprise-scale solutions.
Justin Torre
The Evolution of LLM Architecture: From Simple Chatbot to Complex System
Explore the stages of LLM application development, from a basic chatbot to a sophisticated system with vector databases, gateways, tools, and agents. Learn how LLM architecture evolves to meet scaling challenges and user demands.
Justin Torre
What is Prompt Management?
Iterating your prompts is the #1 way to optimize user interactions with large language models (LLMs). Should you choose Helicone, Pezzo, or Agenta? We will explore the benefits of choosing a prompt management tool and what to look for.
Lina Lam
Meta Releases SAM 2 and What It Means for Developers Building Multi-Modal AI
Meta's release of SAM 2 (Segment Anything Model for videos and images) represents a significant leap in AI capabilities, revolutionizing how developers and tools like Helicone approach multi-modal observability in AI systems.
Lina Lam
What is LLM Observability & Monitoring?
Explore LLM observability and monitoring in production. Learn how it differs from traditional observability, key challenges in LLM systems, and common features of observability tools. Discover insights on ensuring reliability and improving AI applications.
Lina Lam
Compare: The Best LangSmith Alternatives & Competitors
Observability tools allow developers to monitor, analyze, and optimize AI model performance, which helps overcome the 'black box' nature of LLMs. But which LangSmith alternative is the best in 2024? We will shed some light.
Lina Lam
Handling Billions of LLM Logs with Upstash Kafka and Cloudflare Workers
We desperately needed a solution to these outages/data loss. Our reliability and scalability are core to our product.
Cole Gottdank
Best Practices for AI Developers: Full Guide (June 2024)
Achieving high performance requires robust observability practices. In this blog, we will explore the key challenges of building with AI and the best practices to help you advance your AI development.
Lina Lam
I built my first AI app and integrated it with Helicone
So, I decided to make my first AI app with Helicone - in the spirit of getting a first-hand exposure to our user's pain points.
Lina Lam
How to Understand Your Users Better and Deliver a Top-Tier Experience with Custom Properties
In today's digital landscape, every interaction, click, and engagement offers valuable insights into your users' preferences. But how do you harness this data to effectively grow your business? We may have the answer.
Lina Lam
Helicone vs. Weights and Biases
Training modern LLMs is generally less complex than traditional ML models. Here's how to have all the essential tools specifically designed for language model observability without the clutter.
Lina Lam
Insider Scoop: Our Co-founder's Take on GitHub Copilot
No BS, no affiliations, just genuine opinions from Helicone's co-founder.
Cole Gottdank
Lina Lam
Insider Scoop: Our Founding Engineer's Take on PostHog
No BS, no affiliations, just genuine opinions from the founding engineer at Helicone.
Stefan Bokarev
Lina Lam
A step by step guide to switch to gpt-4o safely with Helicone
Learn how to use Helicone's experiments features to regression test, compare and switch models.
Scott Nguyen
An Open-Source Datadog Alternative for LLM Observability
Datadog has long been a favourite among developers for its application monitoring and observability capabilities. But recently, LLM developers have been exploring open-source observability options. Why? We have some answers.
Lina Lam
A LangSmith Alternative that Takes LLM Observability to the Next Level
Both Helicone and LangSmith are capable, powerful DevOps platform used by enterprises and developers building LLM applications. But which is better?
Lina Lam
Why Observability is the Key to Ethical and Safe Artificial Intelligence
As AI continues to shape our world, the need for ethical practices and robust observability has never been greater. Learn how Helicone is rising to the challenge.
Scott Nguyen
Introducing Vault: The Future of Secure and Simplified Provider API Key Management
Helicone's Vault revolutionizes the way businesses handle, distribute, and monitor their provider API keys, with a focus on simplicity, security, and flexibility.
Cole Gottdank
Life after Y Combinator: Three Key Lessons for Startups
From maintaining crucial relationships to keeping a razor-sharp focus, here's how to sustain your momentum after the YC batch ends.
Scott Nguyen
Helicone: The Next Evolution in OpenAI Monitoring and Optimization
Learn how Helicone provides unmatched insights into your OpenAI usage, allowing you to monitor, optimize, and take control like never before.
Scott Nguyen
Helicone partners with AutoGPT
Helicone is excited to announce a partnership with AutoGPT, the leader in agent development.
Justin Torre
Generative AI with Helicone
In the rapidly evolving world of generative AI, companies face the exciting challenge of building innovative solutions while effectively managing costs, result quality, and latency. Enter Helicone, an open-source observability platform specifically designed for these cutting-edge endeavors.
George Bailey
(a16z) Emerging Architectures for LLM Applications
Large language models are a powerful new primitive for building software. But since they are so new—and behave so differently from normal computing resources—it's not always obvious how to use them.
Matt Bornstein
Rajko Radovanovic
(Sequoia) The New Language Model Stack
How companies are bringing AI applications to life
Michelle Fradin
Lauren Reeder