workflow
Neovim: a terminal workflow with review
Keep editing, commands and evidence close together, while keeping ownership explicit.
TVIJO / KNOWLEDGE
Connected knowledge
Read the workflow, follow its links, and review the evidence behind it.
orchestration
DSH Harness: orchestration with explicit boundaries
Separate upstream capabilities, the Tvijo routing design and evidence of an actual run.
architecture
Composable data for connected knowledge
Connect articles, jobs and evidence with stable identities and small explicit contracts.
quality
Completion is a reviewable handoff
A finished message needs an artifact, relevant checks and a clear boundary of what was observed.
workflow
Settings without jargon
Choose how Tvijo works, understand what changes, and leave technical paths on automatic discovery.
workflow
Agent teams and visible costs
Separate roles, paid API usage and subscription tools before starting a team.
workflow
Continue after a disconnect
Keep the task on its configured host, reconnect to the same run and verify saved evidence.
workflow
Take a Tvijo prompt with you
Review a task prompt, copy it or open a supported application with the text ready to use.
Continue in your tool
A button passes the visible text to the selected service. Remove secrets and private data; that service has its own terms and charges.
Article connections
Explicit article links. Select a node to open its article at the top.
Article links · keyboard / text view
- Neovim: a terminal workflow with review
- DSH Harness: orchestration with explicit boundaries
- Composable data for connected knowledge
- Completion is a reviewable handoff
- Settings without jargon
- Agent teams and visible costs
- Continue after a disconnect
- Take a Tvijo prompt with you
- Why I Created Tvijo: A Vision for a Next-Generation Financial Portal
- Assistant library · B02 v2
- Learn together · Ukrainian lesson · L02 v2
- Knowledge universe · U02 v2
- From screen to product: review the exact version
- Evidence and Justice: make a decision someone can appeal
- Hypothesis Lab: make a forecast that can lose
- Science Worlds: ask a paper bridge a fair question
- Agent Arena: practise a handoff that can be checked
- KNOWHOW to play: turn a mission into a skill
- TVIJO Play · mobile mission · Concept v1
- Centavra · agent arena · Concept v1
- TVIJO · mission hub · Concept v1
- DSHREM: review code with evidence
- HOTIDO: measuring the full cost of AI content
- DSHREM for VS Code: code analysis inside LangGraph workflows
- Three terms for public-interest search work
- Run a 30-minute evidence audit on a public page
- Four honest metrics for public-interest content
- Evidence-first SEO for civic teams: a 12-question editorial checklist
- Public marketing without manipulation: a beginner guide for adults
- Check before you share: three questions for ages 16–18
- Who decides what you see? A fair guide to public information for ages 12–15
- Public-interest SEO without manipulation: an evidence-first protocol for civic content
- What Tvijo Teaches and How to Start
- Map a Public Research Ecosystem Responsibly
- Start an Auditable Public-Service AI Pilot
- Choose What to Automate and What to Review
- Run a Measurable AI Adoption Pilot
- Research Public Organizations for Responsible Outreach
- Publish SEO Content That Answers Real Questions
- Turn Accepted Work into a Knowledge Base
- Delegate AI Work with Acceptance Criteria
- Compare API and Subscription Costs
- Read AIRADAR Without Chasing Hype
- Turn Research into a Source-Linked Brief
- Build a Verifiable AI Mini-Project
- Compare Two AI Answers Fairly
- Build a Source Notebook
- Check an AI Answer Before Sharing It
- Ask a Useful Question of AI
- Open Weights or Closed API: What to Choose for a Production LLM Build
- OpenRouter Free Endpoints: Who Pays for Your "Free" Request
- Why NVIDIA Opens Its Nemotron Weights: AI as a Showroom for Chips
- The Free Frontier-Model Race: Who Really Pays for "Free" AI
- ARC-AGI-3: What an Interactive Agentic Benchmark Means for Governed AI Harnessing
- Every agent run starts with a contract: why Tvijo freezes knowledge, permissions and budget before execution
- Content provenance (C2PA, SynthID)
- How to choose an AI system: a risk checklist before adoption
- Personal data and AI: minimization, purpose limitation and retention
- From AI assistants to AI agents: autonomy levels of AI
- AI-generated content disclosure
- Data minimization
- Marking and provenance of AI-generated content: C2PA, SynthID and transparency
- Kill switch
- Prompt injection
- Retrieval-augmented generation (RAG)
- AI hallucination
- Human-on-the-loop (HOTL)
- Human-in-the-loop (HITL)
- AI autonomy level
- AI assistant
- AI agent
- What Is Deferred in the OpenRouter Integration
- Embeddings and RAG Search
- Limits, Budgets, and Guardrails
- Models and Routing
- Errors and Debugging
- Request Parameters
- Chat Requests and Streaming
- Quick Start: Connecting an OpenRouter Key (BYOK)
- Collective AI Engineering: One Workflow for People and Models
- Tvijo Agent Fabric: Five Controlled AI-Worker Runs
- AI Agent Governance Checklist: Production Readiness Review
- AI Productivity Gains and Task Substitution
- Monitorability Level for Frontier Agents
- Agent Risk Assessment for Enterprise AI
- METR and the Rationale for Tvijo AI OS
- Tvijo Architecture: How We Built a Modern Financial Platform
- AI Crystal Ball: Scenario Analysis with Confidence Intervals
- Live Heatmap: Real-Time Market Visualization Architecture
- Magic Screener: Building a Finviz-Level Stock Screener with AI
- Tvijo Product Roadmap 2026
- How We Built an AI-Powered News Intelligence System
- The News You Read Is Already Priced In: Why Real-Time Analytics Matters