Help users build a sustainable habit of regular customer interaction to ensure product development is driven by real-world needs rather than internal assumptions.
npx skills add https://github.com/RefoundAI/lenny-skills --skill continuous-discovery
Turn customer feedback from a periodic chore into a high-frequency engine for product decisions.
Help the user with continuous product discovery using insights from 23 guests and posts across Lenny's Podcast and Newsletter.
Teresa Torres: "I can tell you that opportunity is an unmet need pain point or desire, and that's great. But I can tell you that 98% of people that write opportunities write them as solutions. So we tend to just really struggle with this distinction between the problem space and the solution space."
True discovery requires defining every opportunity strictly as an unmet customer need rather than a pre-conceived feature idea.
Brian Tolkin: "Talking to customers every single day like one-on-one onboarding drivers responding to support tickets, there's no centralized support team, there was no closer to the customer, right? And so I think that foundation actually for really understanding what moves the business and being super close to the customer actually is a pretty good foundation for them going on to say, okay, what do we actually want to build in a more scalable technology way?"
Deep empathy is built by eliminating centralized filters and having product teams engage directly in onboarding and support.
Itamar Gilad: "Google, was what I call an evidence guided company. So essentially it put a high premium on focusing on customers, coming up with a lot of ideas on looking at the data, looking at how these ideas actually worked out. They weren't shy about launching betas and things that were very rough and incomplete and learning from that and then they expected people to take action based on the results."
Launch rough, incomplete versions to gather real-world data that dictates whether to pivot or proceed with the engineering task.
Jeff Weinstein: "The moment the customer felt compelled enough to go out of their way to talk about some problem, that's a unbelievable gift. I will leave a meeting to just get one message back to them. If you're text message friendly with five or 10 of those, you are going to have so much direct signal that is infectious."
Direct, informal communication with motivated users, such as text messaging, often provides higher quality signals than structured research.
Judd Antin: "Well, the solution is simple but not easy to me. It's that we need to restructure the way we make products in a way which integrates research much more fully. It looks like consistent relationships in which researchers, and the work, and the insights they provide are a part of the process from beginning to end."
Research should be an integrated partner throughout the entire development process rather than a reactive service used at the start.
From "The unconventional Palantir principles that catalyzed a generation of startups": "You have to be the user to unlock this concept. I don’t mean that spiritually as in “think like the user”; I mean literally do their same job with your product as an extended member of their team and see what you learn."
Perform the customer's actual work alongside them to reveal the operational friction that interviews alone cannot uncover.
Nabeel S. Qureshi: "There was a different type of engineer which you sent into the field. You would spend maybe Monday to Thursday and you would actually go into the building where the customer worked and you would work alongside them. You would literally get a desk there and so, that engineer became known as a forward deployed engineer."
High-value enterprise discovery is best achieved by having engineers work on-site at customer offices to identify tactical bottlenecks.
See references/artifacts.md for the full list with details.
For all 27 sourced insights from 23 guests, see references/guest-insights.md
Integration with protocols.io API for managing scientific protocols. This skill should be used when working with protocols.io to search, create, update, or publish protocols; manage protocol steps and materials; handle discussions and comments; organize workspaces; upload and manage files; or integrate protocols.io functionality into workflows. Applicable for protocol discovery, collaborative protocol development, experiment tracking, lab protocol management, and scientific documentation.
Analyzes job descriptions and generates tailored resumes that highlight relevant experience, skills, and achievements to maximize interview chances
Generate Excalidraw diagrams from natural language descriptions. Use when asked to "create a diagram", "make a flowchart", "visualize a process", "draw a system architecture", "create a mind map", or "generate an Excalidraw file". Supports flowcharts, relationship diagrams, mind maps, and system architecture diagrams. Outputs .excalidraw JSON files that can be opened directly in Excalidraw.
Build and distribute Expo development clients locally or via TestFlight
Use when you have a written implementation plan to execute in a separate session with review checkpoints
Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.
Benchling R&D platform integration. Access registry (DNA, proteins), inventory, ELN entries, workflows via API, build Benchling Apps, query Data Warehouse, for lab data management automation.
Comprehensive molecular biology toolkit. Use for sequence manipulation, file parsing (FASTA/GenBank/PDB), phylogenetics, and programmatic NCBI/PubMed access (Bio.Entrez). Best for batch processing, custom bioinformatics pipelines, BLAST automation. For quick lookups use gget; for multi-service integration use bioservices.
Take refoundai/continuous-discovery from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.