Popular AI tools
View all →NotebookLM
NotebookLM ingests PDFs, docs, and slides you provide, answers with inline references, and can turn dense material into spoken audio overviews—aimed at students, researchers, and analysts who need traceability more than generic chat.
Bolt
Bolt targets rapid UI shells, marketing sites, and mobile prototypes with hosting and GitHub sync—use it when speed matters more than bespoke backend complexity.
Gemini
Gemini pairs conversational answers with strong Google Workspace and Search adjacency—useful when your prompts mix text, images, and quick research across languages.
GitHub Copilot
Copilot meets developers where PRs and issues already live—inline suggestions, workspace-aware chat, and agent flows that can touch multiple files inside VS Code or JetBrains.
Replit Agent
Describe a product, iterate in the design canvas, and let Replit Agent scaffold code, dependencies, and deploys—popular with students and indie hackers validating ideas in hours.
ChatGPT
ChatGPT spans everyday Q&A, long-form writing, code explanation, and image or file inputs—plus GPTs and connectors when you need repeatable workflows instead of one-off chats.
Claude
Claude shines when you need to load large PDFs, compare versions, or iterate on nuanced prose—team features and projects help keep institutional knowledge in one thread.
DeepSeek
DeepSeek is a go-to when you want chain-of-thought style answers, math-heavy prompts, or repository-scale coding help without burning premium credits.
MCP picks
More →Kubernetes MCP
Go-native MCP server that talks to the Kubernetes API directly—no kubectl shell-outs—so agents can inspect workloads, events, Helm releases, and logs with RBAC-aware toolsets instead of copy-pasting cluster dumps.
Neon MCP
Exposes Neon’s Management API and Postgres workflows through MCP so agents can branch databases for safe migrations, run SQL, compare schemas, and tune slow queries—pairing serverless Postgres ergonomics with explicit human approval for destructive steps.
Context7 MCP
Pulls version-tagged READMEs and API references from Context7 so assistants cite current library docs instead of hallucinating method names from stale training cutoffs—especially valuable when dependencies move fast.
Prisma MCP
Offers local and remote MCP entry points so assistants can reason about Prisma schemas, propose migrations, and manage Prisma Postgres workflows with explicit guardrails instead of ad-hoc SQL in chat.
Netlify MCP
Exposes Netlify CLI and API operations to MCP clients so agents can scaffold sites, wire build settings, trigger deploys, and inspect domains from the same editor session.
Sentry MCP
Connects coding assistants to Sentry issues, stack traces, releases, and performance data through a hosted MCP endpoint with OAuth—so triage starts from real error context instead of a pasted message string.
Skills to try
More →Observability baselines
Defines golden signals, SLO windows, and dashboard checks before agents automate deploys—so assistants know what "healthy" means instead of guessing from noisy logs.
Postmortem writing
Captures timeline, blast radius, contributing factors, and concrete follow-ups after incidents—so teams learn from outages instead of repeating the same surprise.
Library docs in the loop
Pins assistant answers to the README, changelog, and typed exports you actually ship—using MCP doc retrieval or pasted snippets—so refactors start from real signatures instead of confident guesses.
Contract testing
Locks API expectations between services with consumer-driven contracts so refactors fail in CI instead of during a coordinated deploy weekend.
Canary rollouts
Ships a small percentage of traffic to a new build first, watches error budgets and latency, then widens or rolls back—so surprises stay small when agents touch deploy pipelines.
Structured logging
Defines a small set of log fields (request id, user id, feature flag, latency bucket) so production debugging does not depend on grep across inconsistent printf strings.