How to do AI product management? Phospho’s approach:

othmane khadri

Jul 14, 2024 • 6 min read

If Mobile or Cloud technology were waves, then Artificial Intelligence would be a tsunami. Because of its potential to affect every aspect of our lives, its place within Product and Product Management cannot be overstated.

AI has become an integral part of product management, transforming how products are developed, launched, and maintained in the market. AI’s role in product management is multifaceted, encompassing data analysis, customer insights, automation, and predictive modeling, among other areas.

Managing AI products is complex, needing both technical skills and a strategic view. According to a study by Airfocus, 92% of product managers believe AI will have a huge impact on their work in the future. However, this enthusiasm is accompanied by concerns, as 70% of PMs are concerned AI might take their jobs, while 21% feel they don’t have adequate skills to use AI effectively.

LLM app startups face issues like data quality and following rules. We'll look into the tools and methods needed for success in AI product management. We'll see how Phospho's approach helps LLM app startups, focusing on text analytics and always improving.

Importance of AI Product Management

AI is helping product managers obtain and analyze far more user data than traditional methods to gain fresh insights into patterns, trends, and opportunities for improving the product directly in line with users’ needs and pains.

These insights can then help product managers better prioritize the backlog of features to have more confidence in the effectiveness of each iteration cycle. This AI data-driven approach is particularly powerful today because of how fast AI technology evolves and the market with it. Staying on the forefront of user needs and technical capabilities with fast responses has never been more imperative to stay competitive. Enriching data from AI analytics also creates the opportunity for more personalization of user experiences through better understanding and visibility into their app usage.

Continuous improvement and evaluation of these products are vital. Phospho also automates insights extraction and monitors the performance of LLM apps for near hands-off data analysis in real time, keeping you on the pulse of market demands and user needs.

If you’re creating an LLM app and want to gain untapped insights from your text data, sign up here!

Challenges in AI Product Management for LLM app Startups

The main task of a product manager, in more simple terms, is to take cutting-edge technology and turn it into user-friendly, market-ready products people want to use. LLM app startups face certain hurdles now in managing AI products and achieving this. These challenges include:

Startups often find it hard to get enough high-quality data for training AI models to achieve this quickly enough, given the average startup’s runway.
Startups need to balance technical demand with financial feasibility almost daily, which can lead to difficult choices about where to use their resources.
Scaling AI startups with limited budgets requires careful planning given costs and concerns around robust data security.

To tackle these challenges head-on, startups desperately need to focus on what users really need, not just the AI tech. Practical adoption and use of AI product analytics such as Phospho can streamline the iteration cycle without harming the user experience when adding AI LLMs to apps.

To confidently iterate according to user needs and create more efficient, accurate, and user-centric LLM apps, sign up here and try out Phospho on your data.

Lack of Tools for Effective AI Product Management

The field of AI product management is facing a big challenge. There's a lack of tools made just for its needs. Even as AI changes many industries, the tools to manage AI products must be kept up. This creates problems for product managers of AI startups in obtaining actionable data with which to operate.

There aren't many AI product management tools around, and the ones we have don't always cut it. Despite 92% of product managers thinking AI will change their work, 21% feel they don't know how to use AI well. This shows we need better, easier-to-use AI product management tools.

That’s exactly why we built Phospho, an open source text analytics platform specifically designed to help AI startups building LLM apps gather real-time data and extract rich insights from their users interactions.

At Phospho, we also considered the importance of accessibility across startup teams, granting engineers and non-technical product owners alike the leverage to action the rich insights from their LLM apps with custom metrics and KPIs.

With this level of accessibility in mind, we built Phospho to be as seamless as possible to add text analytics to your LLM app and get started:

Create your Phospho account
Import your data in a project (as easy as Excel or CSV)
Set up events and get insights on your dashboard

It’s that simple to streamline your insights gathering and iteration cycle.

If you want to understand your users closely and optimize your LLM app accordingly, sign up here and try out Phospho using your own data. It’s as simple as importing a CSV or Excel file!

Phospho’s Approach to AI Product Management

AI won’t replace product managers, but they will be replaced by product managers who can use AI effectively.

Our text analytics tool has special features for product managers. It lets PMs monitor their products' performance in real-time, track important metrics, and get feedback immediately.

This helps PMs make quick decisions and keep their AI products aligned with business goals.

Phospho's features for managing products include:

Real-Time Monitoring: This lets you track and log user inputs to identify issues or trends and continuously fine-tune the performance of your LLM app.
Custom KPIs Extraction: Create your own KPIs and custom criteria to ‘flag’ for, and you can label whether it was a successful or unsuccessful interaction.
Continuous Evaluation: use our automatic evaluation pipeline that runs continuously to keep improving your model’s performance.
Easy Integration: simply add Phospho to your tech stack with any popular tools and languages like JavaScript, Python, CSV, OpenAI, LangChain, and Mistral.
User Feedback Linking: collect, attach, and analyze user feedback in context to make targeted improvements toward overall app performance.

By effectively using Phospho’s features, we envisioned AI product managers, whether code-savvy or not, being able to handle the complex world of AI development while still keeping their products competitive and valuable to users.

So if you’re a product manager creating an LLM app and want to gain untapped insights from your text data, sign up here. It’s as simple as importing a CSV or Excel file!

How to integrate Phospho into your LLM app

Here’s a quick step by step guide we’ve made to help you implement Phospho into your LLM app:

Set up and integration: Sign up for a Phospho account on our website here and configure your environment variables using the API key you have given.
Use the log function to log your LLM app’s interactions (input and output messages).
Head to the Phospho dashboard and, view your real-time analytics and insights, and evaluate your LLM app’s performance.

Next, have clear goals for your AI product in mind to then use Phospho's tools to define targets and key performance indicators. This is key for making your AI products better and checking how well they do over time.

To do that we’ve made it really simple - use Phospho's real-time monitoring to keep an eye on how users interact and how well your AI model performs. You can also flag any early detected problems or bottlenecks automatically with our custom KPIs which are configurable by you and your team’s own definitions. In doing so, by fine tuning with an automated data driven approach you can have confidence your product is being optimized in the best possible way.

If you want to integrate Phospho into your LLM app, sign up here. We have plenty of documentation to support you as well.

All PMs will be AI PMs one day (soon)

AI is changing how companies make and improve their products fast. To create responsible AI products that provide real value, PMs need to be part engineer, ethicist, and translator. The key is using AI to augment human judgment - not replace it. AI, for product managers, isn’t just about another career choice, it’s about future-proofing your career.

Looking forward, AI will keep getting more involved in managing products. Product managers will focus more on big-picture tasks like planning and understanding what customers want, as AI handles the day-to-day tasks. This change shows how vital it is to analytics platforms like Phospho that help manage AI in products.