Developer skills

Creating vector representations for semantic search, recommendations, and retrieval.

Designing data flow, model calls, tools, memory, and evaluation boundaries.

Running local models, choosing model sizes, managing inference servers, and monitoring resources.

Connecting agents to tools through Model Context Protocol clients and servers.

Diagnosing poor AI outputs by adjusting instructions, context, examples, and constraints.

Structuring instructions, context, and examples for reliable AI outputs.

Connecting LLMs to external knowledge with retrieval, ranking, and grounded responses.

Driving browsers safely for testing, research, and user workflow automation.

Breaking a task into reliable steps, checkpoints, retries, and human review gates.

Designing HTTP APIs, data contracts, auth boundaries, and error handling.

Loading, cleaning, chunking, and normalizing documents or structured data.

Modeling entities, relationships, indexes, migrations, and query access patterns.

Querying, joining, filtering, aggregating, and validating structured data.

Indexing and retrieving embeddings for semantic search and RAG applications.

Searching embeddings with indexes, metadata filters, and relevance tuning.

Writing concise setup, usage, troubleshooting, and reference documentation.

Understanding authentication, rate limits, request shapes, errors, and source attribution.

Using terminal commands, package managers, environment variables, and logs.

Version control, branches, pull requests, issues, and repository hygiene.

Working efficiently with editors, extensions, terminals, diffs, and code navigation.

Accounting for fees, slippage, liquidity, look-ahead bias, and out-of-sample validation.

Checking market data assumptions, survivorship bias, splits, symbols, and timestamps.

Managing hallucination, unsafe automation, prompt injection, and human review gates.

Handling private code, prompts, logs, documents, and user data safely.

Respecting robots.txt, API terms, licenses, trademarks, and attribution rules.

Using APIs, robots.txt, rate limits, attribution, and allowed collection methods.

Deploying apps and static sites to managed platforms with environment boundaries.

Shipping static sites, APIs, and background jobs with clear environment boundaries.

Containerizing and running tools consistently across local and server environments.

Running open-source tools locally or on controlled infrastructure.

Turning product intent into clear implementation constraints and acceptance checks.

Using structured spreadsheet workflows for finance, reporting, and operations.

General Python programming for automation, data, AI, and backend scripts.

Typed JavaScript for web apps, SDKs, and browser automation workflows.

Checking correctness, maintainability, edge cases, and security before merging changes.

Finding root causes through logs, reproduction, isolation, and targeted tests.

Testing LLM quality, retrieval quality, task completion, and regression behavior.

Creating repeatable checks for UI, API, integration, and regression behavior.

Testing web apps with deterministic browser, API, and UI checks.

Understanding sessions, OAuth, tokens, access control, and user identity flows.

Using browser DevTools, network logs, console errors, and DOM inspection.

Building reusable UI components with stable props, states, and styling contracts.

Building usable interfaces with component systems, routing, and responsive layouts.

Designing user flows, layout, hierarchy, accessibility, and mobile-friendly interfaces.