1
About you
This is a self-assessment, not a test. There are no right answers. Rate each capability honestly based on your current, real-world experience. Your responses are anonymous and help shape the team's learning priorities.
Please enter your role
Please select your experience level
Please select your AI experience
Please select at least one area
2
AI Tooling & Workflow
How you use AI coding assistants and integrate them into your daily workflow.
1. I use AI assistants effectively for code generation and editing.
2. I use AI assistants effectively for debugging.
3. I can choose between different AI tools or models based on task tradeoffs.
4. I have a repeatable workflow for working with AI, not just one-off prompting.
5. I can independently adopt a new AI development tool with minimal guidance.
3
LLM Fundamentals & Token Economics
Your understanding of how large language models work and the tradeoffs involved in using them.
6. I understand tokens and context windows well enough to design around them.
7. I can reason about latency and cost tradeoffs in LLM-based features.
8. I understand core model controls such as temperature and output constraints.
9. I can choose between smaller/faster and larger/slower models appropriately.
10. I understand common LLM failure modes such as hallucination and prompt injection.
4
Prompting, Evaluation & Model Control
How you design prompts, evaluate output quality, and control model behavior systematically.
11. I can design prompts that are reusable and robust.
12. I can define quality criteria for an AI feature.
13. I can compare prompts or models in a structured way.
14. I am comfortable using structured outputs or schema-constrained responses.
15. I have a repeatable process for improving prompt or model behavior over time.
5
RAG & Retrieval
Your ability to design, build, and troubleshoot retrieval-augmented generation systems.
16. I understand the end-to-end structure of a RAG system.
17. I can make reasonable chunking and retrieval design choices.
18. I can diagnose why a RAG system is retrieving poor context.
19. I am comfortable with vector search or hybrid retrieval concepts.
20. I know when RAG is the wrong solution.
6
Tool Use, Integration & Agent Workflows
Designing and orchestrating multi-step AI workflows with tool calling, state, and human oversight.
21. I can design workflows where an LLM uses tools or APIs to complete tasks.
22. I understand when to use a simple tool-calling workflow instead of a multi-agent design.
23. I understand state, memory, or checkpointing needs in multi-step AI workflows.
24. I can design AI workflows with retries, branching, or human review steps.
25. I can judge when "agentic" patterns add value versus unnecessary complexity.
7
APIs, GitHub & Developer Operations
Integrating external services, managing environments, and operational developer workflows.
26. I can integrate third-party AI or model APIs into an application.
27. I can handle auth, retries, and rate limits for external APIs.
28. I can set up a reproducible development environment for an AI project.
29. I use GitHub effectively for collaboration and review.
30. I can instrument systems for logs, tracing, or debugging.
8
Core Engineering Systems
Foundational software engineering skills that underpin AI development work.
31. My Python skills are strong enough for production engineering work.
32. I understand concurrency patterns such as threading, multiprocessing, or async execution.
33. I understand event-driven or pub/sub system patterns.
34. I can design or maintain scheduled batch or orchestration workflows.
35. I am comfortable with databases and indexing fundamentals.
9
Research, Ambiguity & Product Judgment
Navigating uncertainty, making technical decisions, and communicating tradeoffs effectively.
36. I can turn vague requirements into a workable technical plan.
37. I can independently research unfamiliar technical problems.
38. I can judge when AI is the right solution versus a simpler approach.
39. I can explain technical tradeoffs clearly to non-specialists or stakeholders.
40. I can make progress in ambiguous projects without a highly detailed PRD.
10
Development Priorities
Which areas would you most like to develop in the next 6 months? Select up to 3.
0 of 3 selected
✓
Thank you

Your responses have been recorded. They'll be used to map team capabilities and shape learning priorities for the next quarter.

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