Augmenting human capabilities with intelligent automation
Your personal AI growth view — how you're using Claude, where you're trending, and the training picked for your level.
Where you and your colleagues stand — your level, by function, with 30-day adoption trends.
Delivery, speed, quality and developer experience for engineering — in one view.
How ready each codebase is for agentic work — scored, with what to fix first.
How Commercial used AI in the last 14 days — Fin support automation, AI sales-call processing, and tool adoption by function.
How Product & Technology used AI across everything we shipped in the last 14 days — Jira cross-referenced with Claude Code telemetry, plus how to use AI even more.
Policies, approved tools, model guides, and responsible AI usage guidelines for all Aiske.ai team members.
Four-session training programme, setup guide, reference diagrams, and team showcases — from first login to power user.
Pairing with Claude on collaborative work — meetings, docs, async threads, and cross-functional tasks beyond engineering.
Using Claude for design work — mockups, design systems, copy, UX review, and creative collaboration for designers.
The spectrum of AI-assisted coding — six modes from autocomplete to autonomous background agents, with guidance on which to use when.
How Claude Code builds its own multi-agent harness on the fly — the building blocks, the orchestration patterns, and when fan-out-and-verify beats a single pass.
Plugins, agents, and scheduled remote routines — automate hourly tasks and post results to Slack, no GitHub account required.
The official Claude marketplace — role-shaped Anthropic plugins and SaaS-integration partner plugins, with picks for each Aiske.ai team.
How Aiske.ai's tools connect — Mission Control, HubSpot, Intercom, Slack and the engineering stack, all stitched into Claude through MCP.
The customer AI assistant — LangGraph supervisor + 10 worker nodes streaming answers to mobile and web. Click any node to see how it works.
Aiske.ai's internal AI agent for analytics and Confluence questions — exposed to Claude via MCP, queries the datalake and internal docs.
Per-task model selection across Aiske and the Internal AI Agent — Sonnet 4.5, Nova Lite/Pro, Gemini, Titan embeddings — with links to official provider docs.
Visual guide to MCP, A2A, AG-UI, A2UI, AP2 and UCP — how the layers stack and when to add each one. Animated end-to-end example.