Wired Geese
How it works
I remain responsible for the product. AI agents participate actively in building it.
This is the working model behind the products I make: human direction, capable agent work, explicit knowledge, and checks before a change is accepted.
Accountability
A person remains answerable for what is built.
Intent
I decide which problem matters and what a useful product outcome means.
Priorities
I choose the next work, trade-offs, and the boundaries worth protecting.
Acceptance
I review important product and engineering decisions before they become an accepted change.
Responsibility
I remain responsible for what is delivered; agents do not own the product or its human consequences.
Agents do real work
Agents are development participants, not a black box.
AI agents can research, analyse, implement, inspect, test, document, maintain, and help with migration work. That creates real execution leverage—not an autonomous company or a replacement for product authority.
Wired Geese reworks the image of hired Wild Geese for digital work: capable AI agents join an authorized job under my direction. Alex Gusev remains the accountable human maker; agents are not employees, owners, or independent commercial actors. F. Lancer, SIA is the legal entity for formal commercial relationships.
Durable context
Important product knowledge is made explicit.
Product meaning should not exist only in my memory, source code, chat history, or an agent’s temporary context window.
I use ADSM—Agent-Driven Software Management—to maintain structured cognitive context: product purpose, architecture, constraints, decisions, environment knowledge, and expectations for verification. It gives people and agents a durable basis for later work, review, and change.
Architecture and verification
Designed for change, checked before acceptance.
Where it fits the product, I use TeqFW as an application platform for modular JavaScript and web software. Its modular structure, inversion of control, and late binding make it practical to replace or extend parts without rebuilding everything.
Agent output is not accepted merely because an agent produced it. The loop is explicit: intent → agent work → inspection, tests, type or static checks, rendered behavior, and context comparison → accepted change. Human review remains part of the loop.
Deployment and access
Hosting and trust boundaries are discussed explicitly.
Where it runs
Depending on the product and agreement, software may run on your infrastructure, a dedicated VPS, another controlled host, or appropriate Alex-managed experimental infrastructure.
Credentials
Before sensitive access is used, we clarify where credentials or session data are stored and what they can reach.
Control
We make the server owner, administrative access, update responsibility, and operational boundary clear.
Revocation
Access can be discussed as an explicit part of setup, including how it can later be removed or revoked.
Working together
Start with a useful outcome and clear limits.
Tell me what service or workflow you want an AI agent to use. We can discuss an MCP integration, paid Telegram early access, or a closely related adaptation, then agree what it may access and what the first result should be.
Inspectable evidence
The model is used across Alex's own software estate.
Repositories show real development across the TeqFW foundation, working software and infrastructure, the multi-component Alarisa system, PDE and Desks, and real sites. They show systematic practice, not a repository-count claim.
TeqFW foundation · TeqCMS · Alarisa · PDE · wiredgeese.com
Repositories alone do not prove demand, quality, adoption, or commercial success. Current Work and the Journal provide the relevant current state and chronology.
Continuity
Future work need not begin by reverse-engineering intent from code alone.
When an agreement covers it, relevant product knowledge can accompany software so Alex and agents, another accountable human and agents, or a customer’s development team can continue the work. Source code, licensing, access, and the precise transfer scope remain separate commercial decisions.
Personal Digital Embassy (PDE) is one independently useful, modular technical system that emerged while exploring Alarisa-related problems. It can support products without becoming a prerequisite for understanding or using them.
Choose a useful next conversation.
See what is available now, inspect Current Work and the Journal, or discuss an MCP or agent-service problem directly.