Honeycomb is a service defining observability and enhancing developer tools, collaborating with notable companies across various industries. They are seeking a Staff Product Manager for their AI Team to define product strategy, synthesize customer needs, and enable AI innovation across the product portfolio.
Responsibilities:
- Define AI product strategy in service of Honeycomb's vision
- Synthesize AI trends, customer needs, and technical capabilities into clear strategic recommendations
- Help the product organization understand where and how AI creates genuine customer value vs. where it's hype
- Identify emerging observability challenges created by AI adoption (e.g., LLM drift, prompt regression, low-context generated code)
- Make informed bets about which AI technologies and approaches warrant investment
- Conduct research that bridges technology and customer reality
- Build deep understanding of how customers are adopting AI in their engineering workflows
- Identify patterns across customer conversations that signal future market needs
- Stay current with AI/ML developments (RAG, fine-tuning, agentic systems, etc.) and translate implications for observability
- Engage with technical communities, researchers, and early adopters to spot trends before they go mainstream
- Enable AI innovation across the product portfolio
- Partner with product teams to identify high-value opportunities to leverage AI capabilities
- Provide guidance on AI approaches, trade-offs, and best practices without centralizing all decisions
- Help teams understand how their work fits into our broader AI strategy and how to leverage shared capabilities
- Synthesize cross-portfolio learnings and socialize what's working (and what isn't)
- Evangelize the AI-observability connection
- Articulate Honeycomb's point of view on AI observability both internally and externally
- Help customers understand how observability needs evolve as they adopt AI
- Contribute to thought leadership through writing, speaking, and community engagement
- Build credibility with technical audiences who care deeply about how we use AI, not just that we use it
Requirements:
- Experienced in product management with at least 1+ year shipping AI-powered products
- Track record of taking AI features from concept to customer impact, including things that didn't work
- Deep understanding of how engineering teams actually build, deploy, and operate AI systems (not just theoretical knowledge)
- Familiarity with current AI/ML techniques and the judgment to know when they're applicable vs. overhyped
- Ability to synthesize disparate signals (research, customer feedback, technical trends) into coherent strategy
- Comfort operating with ambiguity and making decisions without perfect information
- Pattern recognition across conversations—spotting what customers aren't yet saying clearly
- Strong judgment about when to say 'no' or 'not yet' despite exciting technology
- Enough technical depth to have earned respect from engineers and architects and the collaborative approach to drive work forward in tandem with the triad
- Genuine curiosity about how things work, paired with humility about what you don't know
- Ability to evaluate trade-offs between different AI approaches (RAG vs. fine-tuning, model selection, etc.)
- Understanding of observability principles and why they matter in production systems
- Excellent written and verbal communication—can explain complex ideas clearly to varied audiences
- Ability to influence without authority across product, engineering, and go-to-market teams
- Comfort presenting to customers, executives, and technical audiences
- Collaborative mindset that elevates others' work rather than centralizing control
- Demonstrated ability to stay current in fast-moving domains (AI is evolving weekly, not yearly)
- Intellectual humility—you're more interested in learning than being right
- Excitement about the intersection of AI technology and real customer problems
- Energized rather than exhausted by the pace of change in AI