Topic: 2026 non-GAAP operating margin upside and AI impact on analytics budgets
Key points:
Implied non-GAAP operating margin for 2026 is roughly 2.5%.
Revenue growth is outpacing expense growth via go-to-market changes, process improvements, and application architecture modernization.
AI makes analytics a higher-urgency bottleneck; iteration cycles are now weeks/days, requiring constant direction validation.
Customers are "desperate for education" on AI reformulation of analytics, not just feature requests.
Mgmt stance: Bullish — sees structural efficiency gains (sales/marketing, G&A) as ongoing, not one-time; AI increases analytics value and urgency.
Q7 — Ian Black (on for Scott Berg)
Topic: Monetization of AI agents under new pricing and packaging
Key points:
Most AI agents are embedded in the core platform, driving increased data ingestion and module expansion.
New products with separate fees will be introduced; company is "not worried" about monetization ability.
AI capabilities are expected to expand use cases and platform usage.
Mgmt stance: Bullish — excited about monetization opportunities from AI-driven platform expansion and new product fees.
Q8 — John Gomez (on for Nick Altmann)
Topic: Impact of Agentic democratization on new end users and go-to-market strategy
Key points:
No new end-user types; same product, marketing, engineering, and data teams.
Customers are "desperate for education" on AI capabilities (Global Agent, MCP, AI feedback, LLM analytics).
Go-to-market focus is on training, education, vision sharing, and demoing products to drive customer success.
Mgmt stance: Neutral — no shift in user base; go-to-market adapts to education-heavy selling, not new segments.
Q9 — Lucas Cerisola (on for Elizabeth Porter)
Topic: Balancing new demand from smaller customers with move-up-market go-to-market strategy
Key points:
Start-ups are "bleeding edge," pushing capabilities; innovation from them is brought to enterprise deliberately.
Rise of "Vibe Coded apps" creates opportunity for "Vibe-Coded analytics"; early but big potential.
7-figure deal pipeline in 2026 includes a contract with one of the largest foundational model labs (customer since last year).
25 AI companies are over $100,000 in spend.
Mgmt stance: Bullish — sees massive opportunity across all customer sizes, with AI analytics as a universal need.
Q10 — Yitchuin Wong
Topic: Competition from data platforms (Snowflake, Databricks) and 2026 free cash flow expectations
Key points:
Amplitude claims 76% accuracy on analytics benchmarks vs. ~10% for Cortex/Databricks Genie (text-to-SQL only part of solution).
Key differentiators: context layer (multiple data sources) and iterative query tool calls; Amplitude has largest user behavioral data repository.
Free cash flow outperformed in 2025, expanding ~4 points; structural drivers include longer contract duration (RPO growing rapidly), reducing renewal workload for sales.
Full-year 2026 revenue guidance range is $8 million wide; management says it reflects breadth of opportunities, not a specific signal.
Mgmt stance: Bullish on competitive position (accuracy gap vs. platforms); bullish on FCF durability from structural efficiency and contract duration improvements.