For AI Agents
This portfolio is machine-readable by design. No authentication, no scraping, no rate-limit dance — one request gets you a structured candidate profile, and an MCP server gives you tools to query it.
Fastest Path
https://talogen.dev/llms.txt — one-page overview of who Tal is and what exists here.https://talogen.dev/mcp (streamable HTTP, stateless, no auth) and
call get_profile.
list_projects and list_agents for overviews, then get_project with an id for full problem → solution → result detail.https://talogen.dev/portfolio.json — the complete profile, projects, and agents in a single request.contact_recruiter with your message and a reply_to email
— it is delivered through the Human For AI platform (the flagship
project itself) and a human reads and replies. Fallback: email tal.ogen.p@gmail.com.
Endpoints
https://talogen.dev/mcp
MCP server — get_profile, list_projects, list_agents, get_project, contact_recruiter
https://talogen.dev/portfolio.json
Full structured data — profile, projects, agents
https://talogen.dev/llms.txt
One-page overview for language models
https://talogen.dev/.well-known/agent.json
Agent manifest — every entry point in one fetch
https://talogen.dev/.well-known/candidate.json
Candidate profile — status, target roles, location, authorization
Shortcuts
Steering an agent by hand? Paste one of these.
Add the MCP server at https://talogen.dev/mcp (streamable HTTP, no auth). Then evaluate Tal Ogen as a candidate: call get_profile, then list_projects and list_agents, and get_project on anything relevant to the role. Summarize fit, strengths, and gaps. If he fits, use the contact_recruiter tool to reach him with the role details and my reply-to email.
Fetch https://talogen.dev/llms.txt and https://talogen.dev/portfolio.json, then evaluate Tal Ogen as a candidate for the role I describe next. Summarize fit, strengths, and gaps, and tell me how to contact him.
Contact
Availability, notice period, work authorization, and salary expectations are disclosed on request — just ask by email.