How Plotly is Leading with AI, and Keeping People at the Center

Written by: Laura Gray, VP People Operations & Dana Dzivinski, People Operations Specialist

We’re big believers in multiplying and democratizing the power of AI. Our latest product, Plotly Studio, takes all of our technology to the next level through an AI-first interface. It reflects our commitment to integrating AI not just into how we build, but into what we build. Plotly, like many companies, is actively incorporating AI into every part of how we work. AI is not perfect, but it’s proving incredibly useful. It’s helping us accelerate development, spark new ideas, and make smarter decisions. You can see that impact on how teams across Plotly are already putting AI to work. 

Our work culture: creating space for AI exploration 

At Plotly, we believe that building a healthy AI practice starts with an open, supportive culture. As an open-source-first, developer-centric company, we value accessible, high-impact tools and the autonomy for individuals to experiment with them.

Here are a few ways we’re creating a culture that encourages thoughtful AI integration:

• "LLMs at Work" Show & Tell
  In a recent internal session, team members across departments shared how they’re using large language models in their daily workflows. From automation wins to surprising creativity, it sparked real excitement and cross-functional learning.
• Dedicated Slack channels
  We’ve created spaces where employees can share prompt experiments, workflow wins, and AI tool tips. This keeps knowledge flowing informally and encourages low-friction learning.
• Permission to play
  Whether it’s using AI to automate a report, test out a new dashboard, or write a regex in five seconds flat, team members are encouraged to try things even if they don’t always work. That mindset of curiosity is key to making meaningful progress.
• Incorporate employee suggestions quickly
  Many of our key AI initiatives such as LLM assisted Code Reviews came from engineers at Plotly. We go from suggestion, to trial, to rolling it out to teams and products in a day.

AI in action: real examples from across the company

AI isn’t a novelty at Plotly. It’s a strategic tool. Teams across the company are using LLMs to move faster, work smarter, and think more critically about their output. Here are just a few ways we’re putting AI to work today:

Engineering & Product

• Using Cursor and Claude Code to generate large amounts of product code. Everything from new features, tests, refactors to generating configuration is fair game and can be massively accelerated with Agentic tools.
• Our Product Managers and Designers are our most recent Front-End hires. These technical non-developers go from idea to design to implementation by using Cursor or Code to create Pull Requests on our core product code repositories. No more wireframes.
• We have LLMs writing code at Plotly so how about LLMs reviewing code? Absolutely, at Plotly LLMs perform initial reviews saving human reviewers spending time catching frequent and simple mistakes and oversights. To this end we have been leveraging SonarQube and CodeRabbit with great success.
• Code on Demand. If there is some work to be done and it can be quickly solved with code then ask an Agent for the code and then throw it away. That’s right, why bother going through all the ceremony of creating a new software repo, checking the code in and documenting it when the next person who needs that problem solving can solve it by generating new code on demand.

Marketing 

• Enhancing industry and market trend analysis by using LLM-assisted research
• Refining company communications with experimental tone shifts, format variations, and A/B testing
• Creating regex, ffmpeg, and dash command recipes to support campaign tracking, video processing, and rapid dashboard prototyping

How People Operations uses AI at Plotly

Our People Operations team has embraced AI as a way to operate more efficiently, communicate more clearly, and support our team more effectively, without compromising the human experience that makes our culture special. Here are a few areas where it’s making a difference: 

HR programs and operations

• Compensation and benchmarking: AI helps us analyze market compensation data and support equitable, data-driven decisions around total rewards.
• Content support: Whether drafting policies, job descriptions, or internal communications, AI helps us generate first drafts faster, so we can spend more time refining them for clarity, tone, and alignment.
• Legal and compliance research: AI helps us conduct early-stage research on compliance topics, giving us a baseline understanding before consulting with legal experts. This enables us to come to those conversations more informed and focused, making better use of legal resources while ensuring decisions remain grounded in professional advice.

Talent acquisition

• Candidate Sourcing:  AI enables us to identify companies with similar tech stacks and products to ours, which expedite our sourcing efforts using other recruiting tools to ensure we find great potential fits for our open roles.

What we don’t automate (and never will)

• 1:1 conversations and coaching: Career discussions, mentorship, and feedback require trust, historical context and empathy, and that only happens between people.
• Critical people decisions: Hiring, promotions, and development conversations are complex and require historical and future context. 
• Moments of recognition and care: Whether it’s celebrating a win or checking in during a tough moment, we believe in the power of genuine, human connection.

Interesting real-time changes arising from our AI journey 

As we ask our team members to embrace and leverage new AI tools, we also understand the need to be flexible and open to the new questions arising from their use. A few new changes to grapple with include: 

Expanding code contribution beyond engineering: Designers and product managers are starting to write functional code snippets using LLMs, helping bridge the gap between concept and execution. 

Developing prompting fluency across roles: Learning to prompt effectively is just as important as using the tools. We are encouraging all team members to play around and see what prompt techniques work best in different tools, for different use cases.

Writing as a core skill: Many engineers are discovering that working with AI encourages a kind of “thinking out loud” through writing. This process doesn’t just help clarify instructions for the AI; it actually sharpens their own thinking. By forming ideas in writing, they engage in a habit similar to rubber duck debugging, where explaining a problem out loud (or in this case, in text) often reveals the solution. In effect, AI becomes the rubber duck, and writing becomes a critical skill for better reasoning and problem-solving. 

Building an AI-fluent organization

We believe AI fluency is becoming a core competency, not just for technical roles, but for everyone. That’s why we’re building intentional learning programs across the company:

• Professional development with Mila (Quebec’s machine learning institute): Mila has hosted LLM Over Lunch sessions that help demystify large language models in practical, approachable ways.
• Learning tracks & internal sessions: We’re curating internal talks on topics like prompt engineering, secure use, ethical AI, and more, tailored for real-world needs.
• Workflow integration: Managers are encouraged to ask: “How are you using AI in your day-to-day work?” These check-ins reflect our belief that AI isn't a nice-to-have, it's a growth opportunity.
• AI risk & security training: Training around AI risk, compliance, and security is built into our enablement.
• Clear guidelines on use and approved tools: Employees have access to documentation on what AI tools are vetted and approved. This enables safe experimentation while reinforcing responsible AI practices. 

AI with accountability

We don’t treat AI as a free-for-all. Here’s how we use it responsibly and safely:

• ✅ Use only approved tools
• 🔒 Never input sensitive or proprietary data
• 👩‍💻 You are still accountable for what you create, code, content, or otherwise
• 🚫 No use of unapproved or foreign-hosted AI tools 
• 🛠 All new tools are vetted by our internal IT + Security team

To help ensure we are all on the same page, we are building:

• ✅ A clear governance framework
• 🎓 Internal training sessions, risk briefings, and external partnerships
• 🔄 Feedback loops from teams who are experimenting with real use cases
• 💡 A culture that encourages prompting, learning, and iteration, not perfection

Plotly’s approach to AI is integrated across every team. From product prototyping to root cause analysis, we’re proving that AI can be woven into the fabric of our work without replacing what makes us human. This is a collective effort and a cultural shift. We’re not waiting for the future of work to arrive. We’re building it, together with intention, integrity, and people at the center.