Thoughts about the future of AI - from the team helping to build it.
Discover how Claude 3.5 Sonnet compares to OpenAI o1 in coding, reasoning, and advanced tasks. See which model offers better speed, accuracy, and value for developers.
Lina Lam
What's the difference between CrewAI and Dify? Here's a comprehensive comparison of their main features, use cases and how developers can monitor their agents with Helicone.
Lina Lam
Released in December 2024, Gemini-Exp-1206 is quickly beating the performance of OpenAI gpt-4o, o1, claude 3.5 Sonnet and Gemini 1.5. Delve into key features, benchmarks, applications and what the hype is all about.
Lina Lam
Meta just released their newest AI model with significant optimizations in performance, cost efficiency, and multilingual support. Is it truly better than its predecessors and the top models in the market?
Lina Lam
OpenAI has recently made two significant announcements: the full release of their o1 reasoning model and the introduction of ChatGPT Pro, a new premium subscription tier. Here's a TL;DR on what you missed.
Lina Lam
GPT-5 is the next anticipated breakthrough in OpenAI's language model series. Although its release is slated for early 2025, this guide covers everything we know so far, from projected capabilities to potential applications.
Lina Lam
How do you measure the quality of your LLM prompts and outputs? In this blog, we talk about how you can evaluate LLM performance and effectively test your prompts.
Lina Lam
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
By focusing on creative ways to activate our audience, our team managed to get #1 Product of the Day.
Lina Lam
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
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
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
This guide provides step-by-step instructions for integrating and making the most of Helicone's features - available on all Helicone plans.
Lina Lam
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
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
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
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'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
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
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
We desperately needed a solution to these outages/data loss. Our reliability and scalability are core to our product.
Cole Gottdank
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
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
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
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
No BS, no affiliations, just genuine opinions from Helicone's co-founder.
Cole Gottdank
Lina Lam
No BS, no affiliations, just genuine opinions from the founding engineer at Helicone.
Stefan Bokarev
Lina Lam
Learn how to use Helicone's experiments features to regression test, compare and switch models.
Scott Nguyen
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
Both Helicone and LangSmith are capable, powerful DevOps platform used by enterprises and developers building LLM applications. But which is better?
Lina Lam
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
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
From maintaining crucial relationships to keeping a razor-sharp focus, here's how to sustain your momentum after the YC batch ends.
Scott Nguyen
Learn how Helicone provides unmatched insights into your OpenAI usage, allowing you to monitor, optimize, and take control like never before.
Scott Nguyen
Helicone is excited to announce a partnership with AutoGPT, the leader in agent development.
Justin Torre
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
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
How companies are bringing AI applications to life
Michelle Fradin
Lauren Reeder