DEV Community: Jake

How to switch from an internal tools PM to an AI PM

Jake — Tue, 02 Jan 2024 18:32:47 +0000

Transitioning from Internal Tools PM to AI PM: A Comprehensive Guide

As Artificial Intelligence (AI) continues to revolutionize industries and reshape the landscape of technology, the demand for skilled AI Project Managers (AI PMs) is skyrocketing. This burgeoning field presents a unique opportunity for experienced Internal Tools PMs to elevate their careers and contribute to the forefront of innovation.

However, successfully transitioning from an Internal Tools PM role to an AI PM role requires a strategic approach and a willingness to adapt to the nuances of AI projects. To guide you through this transformative journey, we've compiled a comprehensive guide that outlines key strategies and considerations for making this career move effectively.

1. Understanding the AI Landscape

The AI landscape is a vast and ever-evolving field. It encompasses a wide range of technologies and applications. Many of them are extremely niche. As an AI project manager, it's crucial to understand this landscape to guide and manage AI projects from ideation to deployment effectively. This section will help you build that understanding.

(Image source: Landscape Foundation)

Grasping AI Fundamentals

Immerse yourself in the fundamental principles of AI, including machine learning, neural networks, natural language processing, and other relevant technologies. This foundational knowledge will empower you to communicate effectively with technical teams, comprehend project requirements, and identify potential roadblocks.

Machine learning: Understand the core concepts of supervised, unsupervised, and reinforcement learning, as well as different machine learning algorithms.
Neural networks: Grasp the fundamental architecture of neural networks, including perceptrons, activation functions, and deep learning models.
Natural language processing (NLP): Learn about techniques for natural language understanding and generation, such as text classification, machine translation, and sentiment analysis.
Computer vision: Gain knowledge of image and video processing techniques, including object detection, image segmentation, and facial recognition.
Recommender systems: Understand the principles of recommendation algorithms, such as collaborative filtering and content-based filtering, and how they are used in various applications.

To go deeper, explore open-source AI frameworks and platforms like TensorFlow, Keras, and PyTorch for building AI models.

Foundational knowledge of AI helps effectively communicate with technical teams and understand project requirements to build such solutions.

Industry Applications of AI

AI is being applied across various industries, from healthcare to finance. Understanding how AI is used in different sectors can provide valuable insights into potential project challenges and opportunities.

Healthcare: In medical diagnostics, AI can be used to analyze medical images, such as X-rays and MRIs, to detect anomalies or abnormalities that human doctors may miss.
Finance: AI can be used for fraud detection. It analyzes financial transactions to detect fraudulent activity.
Manufacturing: AI can predict when equipment is likely to fail, allowing for preventive maintenance and avoiding costly downtime.

By understanding how AI is utilized in different sectors, you can anticipate the needs and expectations of stakeholders in diverse AI projects.

This knowledge aids in anticipating the needs and expectations of stakeholders in diverse AI projects.

2. Transitioning Skills and Knowledge

As a seasoned project manager, you've acquired invaluable skills and knowledge that can serve as a powerful foundation for success in the dynamic world of AI project management. This section will explore how your existing project management skills can be translated and adapted to AI projects' unique challenges.

(Image source: monday dev)

Leveraging Project Management Expertise

Your experience in project management, encompassing aspects like planning, organization, and stakeholder management, serves as a solid foundation for success in AI projects.

Translate your expertise in managing timelines, budgets, and team dynamics to the context of AI projects.

Planning: Adapt project planning methodologies to accommodate the iterative nature of AI development. Break down projects into smaller, manageable phases and establish clear milestones and deliverables for each phase.
Organization: Implement effective project management tools and techniques to organize and streamline development. Utilize tools like Gantt charts, Jira, and Trello to manage tasks, track progress, and foster collaboration among team members.
Stakeholder Management: Proactively engage with stakeholders throughout the AI project lifecycle. Communicate project updates regularly, promptly address concerns, and gather feedback to ensure project objectives are aligned.

Utilize your experience in managing timelines, budgets, and team dynamics, adapting these skills to the AI context.

Adapting to Agile Methodologies

AI projects often benefit from Agile methodologies due to their iterative nature. Familiarize yourself with Agile practices and consider how they can be applied to manage AI projects effectively.

Scrum: Divide projects into sprints with short iterations, allowing for rapid feedback and continuous improvement. A more rigid framework than Kanban.
Kanban: Visualize and manage tasks on a Kanban board, efficiently prioritizing and moving work items through the development pipeline. It is more flexible than Scrum and may be better suited to AI's hyper-iterative (and sometimes open-ended) nature.

Agile frameworks can accommodate the evolving nature of AI projects, allowing for flexibility and continuous improvement.

3. Navigating AI Project Challenges

There’s a lot that goes into building AI solutions. To name just a few things, you must consider data management, LLM monitoring (to avoid bias, assure adherence to guardrails, monitor costs, etc.), and ethical considerations.

Data Management and Quality

AI models rely heavily on data. Understanding data quality, data collection, and processing challenges is vital. AI PMs should implement robust data governance practices to ensure data integrity, consistency, and compliance with data privacy regulations. They should also leverage AIOps platforms to monitor and manage the performance of AI models, flagging potential data quality issues early on.

LLM Monitoring

Large Language Models are AI systems that generate human-quality text. However, LLMs can also perpetuate biases and generate harmful or offensive content. To mitigate these risks, AI PMs should use LLM bias detection tools to identify and address potential biases in AI models.

Additionally, they can utilize LLM sentiment analysis tools to assess the emotional tone of text generated by LLMs, ensuring the production of respectful and appropriate content.

AIPMs can also implement LLM cost monitoring tools to track LLMs' usage and resource consumption, optimizing costs and preventing overspending.

Ethical AI

AI project managers play a crucial role in promoting responsible AI development. Develop and implement ethical guidelines for AI projects, outlining the principles that will guide the development and deployment of AI solutions. Regular ethical audits are also essential to assess potential risks and implement mitigation strategies.

The Role of an AI PM: Mixing Product and AI

Project management is undergoing a significant transformation, fueled by the rapid advancement of AI. As it becomes increasingly integrated into our products and services, the role of the project manager is also evolving.

AI project managers are a critical new breed of professionals who oversee the development and deployment of AI-powered solutions. They translate business needs into actionable AI strategies, manage AI projects from conception to launch, and ensure that AI is effectively integrated into the overall product or service.

monday.com, a leading project management platform, is a prime case study for how AI PMs will work in the future.

(Image source: monday AI)

The AI PMs at monday.com are leading the way in this emerging field. They have been responsible for developing monday AI and monday dev (powerful new products in their portfolio). monday AI powers the whole ecosystem, while monday dev focused on streamlining product development workflows and project management.

Here are some examples of how the AI PMs at monday have used their expertise to build and deploy AI-powered solutions:

Automated Task Generation: Developed an algorithm that automatically generates task lists based on client briefs and project goals. This saves time and ensures all tasks are accounted for from the start.
Intelligent Time Tracking: Built an AI-powered tool that monitors team members' activity and identifies potential productivity bottlenecks. This information can be used to improve resource allocation and make better-informed decisions about project scheduling.
Dynamic Resource Allocation: Created an AI-powered tool that matches team members with tasks based on their skills and experience. This can help to optimize resource utilization and improve team productivity.

The work of the AI PMs at monday.com is an example of the work that AI PMs will be doing in the future. As AI becomes more prevalent in our products and services, AI PMs will be needed to manage and deploy these AI-powered solutions.

Bonus Tips for AI Project Managers

In addition to the comprehensive guidance provided in this blog, below are some bonus resources for AI project managers to enhance their skills and expertise. Each of these will be incredibly valuable in your journey to becoming a top AI PM.

Deeplearning.ai: Provides comprehensive video courses on deep learning, covering topics such as TensorFlow, PyTorch, and natural language processing.
Siraj Raval: Delivers engaging lectures on AI, covering topics such as artificial general intelligence, robotics, and the ethical implications of AI.
Towards Data Science: A popular platform for sharing and discussing data science and AI-related articles and tutorials.
Kaggle: A platform for data science competitions where AI practitioners can exchange ideas and work on joint projects. Get your hands dirty on some real-life projects to solidify your knowledge!

The transition from an internal tools PM to an AI PM is exciting and rewarding but also demands dedication, adaptability, and a willingness to learn.

By immersing yourself in the AI landscape, expanding your project management toolkit, navigating AI-specific challenges, and continuously enhancing your AI competencies, you can successfully navigate this transition and significantly impact a dynamic and rapidly evolving field. EXCITING!

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The Top Tech Events to Attend in November and December 2023

Jake — Fri, 17 Nov 2023 00:43:52 +0000

The final months of 2023 are packed with can't-miss events for tech professionals. From global conferences to intimate meetups, there are countless opportunities to engage with the industry's sharpest minds.

While massive gatherings AWS re:Invent deliver stellar content, attending smaller events can provide unique access and insights. Keep an eye out for demo days spotlighting innovative startups in specialized fields like women-led companies or Black founders.

The regional AI & Big Data Expo, Cyber Security & Cloud Expo, and IoT Tech Expo in London are prime spots to network with European experts and explore key technologies up close.

And for those interested in startups and entrepreneurship, don't miss the virtual Google for Startups Accelerator demo days.

When evaluating events, consider these factors:

• Relevant topics - Will you learn something useful?
• Impressive speakers - Who are the experts presenting?
• Intimate access - Can you easily connect with speakers and attendees?
• Location - Is it local or worth traveling to?
• Cost - Is it affordable or worth the investment?

And if you can't make a conference live but still want some kind of interaction with an expert to get your important questions answered, look out for monday.com's Reddit AMA on November 21st (10AM - 11:30AM EST). You can ask questions in advance and have them answered live by experts. It promises insightful discussions on monday.com's newest flagship product, monday dev (tailored for product development teams).

Below is a full list of the top tech events in November:

1. Elevate '23 by monday.com [Online]

This is monday.com’s annual online customer conference where you can learn how leading customers, industry thinkers, and platform experts are reenvisioning work.

When: December 14
Where: Virtual

2. AI & Big Data Expo [In-Person*, London]

Venture into the future of Artificial Intelligence and Big Data at this in-person expo in London. Gain invaluable insights into transformative technologies that are reshaping industries and the way we work.

When: November 30 - December 1
Where: London, UK (In-person)

*Some on-demand session recordings are available even if you cannot attend.

3. Cyber Security & Cloud Expo [In-Person*, London]

In an era where cybersecurity is non-negotiable, this in-person event is your opportunity to delve into the latest cybersecurity trends and solutions.

Elevate your security know-how by engaging with experts in a face-to-face setting.

When: November 30 - December 1
Where: London, UK (In-person)

*Some on-demand session recordings are available even if you cannot attend.

4. IoT Tech Expo [In-Person*, London]

The Internet of Things continues to revolutionize our world. Join the team in person to explore the latest developments, applications, and untapped potential of IoT technology.

When: November 30 - December 1
Where: London, UK (In-person)

*Some on-demand session recordings are available even if you cannot attend.

5. Google for Startups Accelerator: Black Founders Demo Day [Online]

Celebrate diversity in tech entrepreneurship at the Black Founders Demo Day.

Witness the brilliance of Black founders and their innovative startups, and be inspired by the solutions they bring to the tech landscape.

When: November 30
Where: Virtual

6. AWS re:Invent [In-Person and Online]

For cloud enthusiasts, AWS re:Invent is the ultimate gathering. With a hybrid format, you'll be at the forefront of cloud computing innovations, networking with industry experts, and diving deep into the future of technology.

When: November 27 - December 1
Where: Las Vegas, USA (Hybrid)

7. Black Hat Europe 2023 [In-Person]

Black Hat Europe is the paramount event for cybersecurity professionals. Connect with experts, explore cutting-edge cybersecurity advancements, and safeguard the digital world in person.

When: December 4-7
Where: London, UK (In-person)

8. monday.com Reddit AMA featuring monday dev experts [Online]

Get the inside scoop directly from the monday.com team! monday.com are hosting a Reddit AMA all about monday dev, their work OS designed for agile product development, R&D, and software development teams.

You can bring your toughest questions about sprint planning, release management, engineering workflows, integrations, and more.

Join live or ask questions beforehand via the official thread (they will get answered during the session).

When: Tuesday 11/21 from 10-11:30am EST
Where: Virtual

Summary

These events offer invaluable opportunities to learn, network, and fuel innovation. Be proactive in seeking out conferences and meetups that align with your goals.

For a quick recap, the main events (in chronological order) are:

monday.com Reddit AMA (Virtual, November 21)
AWS re:Invent (Las Vegas and Virtual, November 27 - December 1)
Google for Startups: Black Founders Demo Day (Virtual, November 30)
AI & Big Data Expo (London, November 30 - December 1)
Cyber Security & Cloud Expo (London, November 30 - December 1)
IoT Tech Expo (London, November 30 - December 1)
Black Hat Europe 2023 (London, December 4-7)
Elevate ’23 by monday.com (Virtual, December 14)

I hope you found this helpful! Stay tuned because I'll be dropping a list of AI-related events soon, too :)

Which events will you be attending? Have you heard of any other top events coming up? Let me know in the comments!

15 top AI tools for marketing, infrastructure, and LLMOps

Jake — Tue, 07 Nov 2023 19:44:30 +0000

Hey there, dev.to community!

Today, I'm sharing my top 15 AI tools that are must-haves for anyone looking to harness the full potential of AI in marketing and data analytics.

I'm Jake, a marketer turned data analytics enthusiast (no, not one of "those" "enthusiasts" – I actually went and got a masters degree in big data and data analytics).

Currently, I'm applying my passion for data in an AI startup, navigating the exciting challenges that come with transforming vast data sets into compelling marketing narratives and product features!

I've witnessed firsthand the transformative power of AI in our field.

Here's a rundown of top AI tools that you should consider incorporating into your tech stack.

AI Marketing & Content Creation Tools

- Q-ueue.ai: "Turn your Knowledge into digital assets. At scale". Generating diverse content with AI writing assistance.
- Pictory: "Turn lengthy content into engaging visual stories". Distill articles, documents, and scripts into concise videos with the power of AI
- AdCreative AI: "Generate ad creatives that outperform your competitors". Pioneering ad creation with generative AI.
- MarketMuse: "Own your topic in the SERP". Optimizing long-form content with AI-driven insights
- DALL·E: "allowing you to easily translate your ideas into exceptionally accurate images". Crafting custom images with an AI-powered imagination. DALL·E 3 is a game changer.

AI Data Management & Infrastructure Tools

- Pinecone: "Long-Term Memory for AI". Managing scalable AI solutions with a cloud-native vector database.
- Deep Lake by Activeloop: "Data infrastructure optimized for computer vision. Deep Lake is the fastest data loader for PyTorch". Tailoring databases for deep learning and large language models.
- FlowiseAI: "Build LLMs Apps Easily". A user-friendly platform for constructing LLM workflows and developing LangChain apps with a drag-and-drop UI
– Cohere: "Give your technology language". Deep natural language understanding and generation, transforming the way applications interact with human language.
– Langchain: "Get your LLM application from prototype to production". Sstreamlines the process of connecting multiple LLMs and utilities. Enables developers to create AI applications easily.
– LlamaIndex: "Unleash the power of LLMs over your data". A storage mechanism that enables data querying for various LLM use cases like question-answering and summarization

LLMOps and Prompt Management Tools

- Comet's LLM SDK: "Less friction, more ML". Facilitating LLMOps with extensive open-source functionality
- Arize AI: "The ML Observability Platform for Practitioners". Enhancing prompt engineering workflows with real-time iteration capabilities.
- PromptHub.us: "Level up your prompt management". Streamlining prompt writing with comparative testing features.
- LangTail: "Seamlessly Manage, Test, and Integrate Your LLM Prompts". Offering comprehensive change management for LLM prompts.

Wrapping up

These tools represent just the tip of the AI iceberg. Of course, we also have the old trustworthy tools of PyTorch, Keras/Tensorflow, Hugging Face and its many tools, and more.

As we continue to push the boundaries of what's possible with AI, the synergy between these tools and human creativity will undoubtedly lead to even more innovative solutions.

Did you like this post?

Join me as we dive into the world of data-driven marketing and uncover the potential of AI to revolutionize our approach.

Whether you're a marketer looking to up your data game, a data scientist interested in the application of analytics in business, or just AI-curious, I believe we can all learn from each other.

Looking forward to sharing, learning, and growing with all of you!

Bridging Data and Marketing in the AI Arena: My Journey

Jake — Tue, 07 Nov 2023 17:15:48 +0000

Hello, dev.to community! My name is Jake, and I'm thrilled to share my first post here.

With a decade of experience in marketing & analytics (mostly content and product marketing) and a Master's degree in Big Data and Data Analytics, I've found myself at the confluence of two fascinating fields: marketing and data science.

Currently, I'm channeling this blend of skills into my role at an AI startup, and I'd love to dive into how these worlds intersect and why it's such an exciting time to be in this space.

The Symbiosis of Data and Marketing

Marketing has always been about understanding the audience, but the rise of big data has taken this to a whole new level.

Data analytics offers insights that are reshaping how we approach marketing strategies.

At our AI startup, I leverage large datasets + AI to tailor marketing efforts that we more or less know will make an impact.

Campaigns resonate on a deeper level with our audience, because they're informed by a wealth of data-driven insights.

The AI Startup Experience

Working for an AI startup is as challenging as it is exhilarating. The pace is fast, the technology is cutting-edge, and the potential for innovation is vast.

AI is enhancing how we analyze data and execute marketing strategies.

One of the most exciting aspects is seeing firsthand how AI can identify patterns and trends that even experienced marketers might miss.

Not to mention it just speeds up the workflow remarkably. You can test and iterate more ideas in less time to narrow in on the right content and marketing angles. And you don't spend anywhere near as much of your mental energy to do the same amount of work. Writers block, brain fog, you can get through it all and get to the 20% that you like doing and that moves the needle with way less effort.

Looking Ahead

I'm passionate about sharing my journey and learning from others in this space. Whether you're in data, marketing, or just AI-curious, we all have valuable insights to contribute.

In future posts, I'll delve into specific cases, the challenges we face, the successes we celebrate, and the lessons learned along the way.

I'm eager to explore topics like the ethical use of data, the integration of AI into traditional marketing roles, and much more.

Let's Connect

I'm here to learn, grow, and connect with like-minded professionals. So, drop your thoughts in the comments, share your experiences, and let's start a conversation.

If you're interested in the intersection of data and marketing in the AI world, give this post a ❤️ and follow me for more.

Looking forward to this new adventure on dev.to!