Agents that learn from every conversation and get better over time.
Install in one command. They build their own knowledge pages, remember what you like, and keep themselves current — across Claude Code, Claude Chat, OpenClaw, and NemoClaw.
npx @vectorize-io/self-driving-agents install marketing/seo --harness claude-codePick your harness above, or replace the agent slug with any template you want.
How it works
You never tell the agent to "save" or "remember." It decides what matters and keeps itself current.
You chat with the agent
Use it like any normal assistant. Ask questions, give feedback, share context.
Memory is retained
Conversations are auto-summarized into Hindsight as durable, structured memory.
Knowledge pages update themselves
After each session the agent rewrites the pages it owns — playbooks, references, preferences.
Next session it remembers
On the next chat the agent reads its current pages — it knows what works and what you prefer.
Want the deeper picture?
See how the harness, the agent, and Hindsight fit together — what crosses the boundary, what stays server-side, and why pages and memories live in two layers.
Available agents
Install the whole department or pick a specialty.
Academic
Extract scholarly arguments, source citations (primary vs secondary), methodological choices, period/regional context, contested claims, and the user's research questions and writing voice.
Humanities
Extract scholarly arguments, source citations (primary vs secondary), period and regional context, contested claims, and the user's research questions across history, anthropology, and narratology.
Social Science
Extract empirical findings, methodological choices, dataset limitations, and theoretical frames across psychology and human geography. Capture the user's research design and confidence in claims.
Design
Extract design decisions, brand guidelines, visual systems, UX research findings, accessibility constraints, design critique outcomes, and stakeholder feedback on creative work.
Ux
Extract UX research findings, IA decisions, interaction patterns, usability test outcomes, and UI component standards. Capture stakeholder feedback and accepted vs. rejected proposals.
Visual
Extract brand guidelines, visual systems, image-direction prompts, accessibility/inclusive-visuals constraints, and storytelling decisions. Capture critique outcomes and locked vs. flexible elements.
Engineering
Extract architectural decisions, API contracts, performance numbers, incident root causes, code review patterns, deployment outcomes, and technical trade-offs across backend, frontend, infrastructu…
Ai
Extract AI-engineering decisions: model choices, optimization patterns, voice/email integrations, and remediation outcomes.
Architecture
Extract software-architecture decisions, rapid-prototyping patterns, and senior-developer mentorship outcomes.
Harnesses
Same agent, different runtimes. Pick the one you already use.
Claude Code
Claude Code that learns from every project.
--harness claude-codeHermes
Hermes profiles that learn from every conversation.
--harness hermesClaude Chat & Cowork
Claude.ai agents that learn from every conversation.
--harness claudeOpenClaw
OpenClaw agents that learn from every conversation.
--harness openclawNemoClaw
NVIDIA NeMo Agent sandboxes that learn from every conversation.
--harness nemoclawOr roll your own agent.
An agent is just a directory: drop a bank-template.json next to some markdown files and point the CLI at it. Same self-driving behavior, your domain.
my-agent/
bank-template.json # memory bank + knowledge pages config
playbook.md # any .md/.txt becomes seed knowledge
advanced-tips.mdnpx @vectorize-io/self-driving-agents install ./my-agent --harness claude-code