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AI · Agents & ChatbotsOne pillar, two modes. Action: agents that read, write and execute inside explicit trust boundaries. Response: chatbots grounded in your institutional memory, answering with governed, cited replies. Evals and guardrails across both.
Action and Response. Action agents pursue goals by reading systems, writing to them and executing multi-step work under permissions defined before they run; Response chatbots answer questions from your governed institutional memory with citations.
Most AI programmes fail by blurring the two: giving conversational tools permission to act, or asking acting tools to improvise answers. We engineer them as distinct disciplines on one substrate: trust boundary architecture specifies per agent what it may read, write and execute and what always escalates to a human; permission-aware retrieval grounds every chatbot answer; and prompt & context engineering, evals and guardrails wrap both.
How agents earn autonomy
Trust boundaries written down: what the agent may read, write and execute.
The institutional memory layer beneath: context for answers and decisions.
Action agents and Response chatbots, engineered with prompt & context engineering.
Evals replay real scenarios and score faithfulness and decision quality.
Autonomy grows only as evidence accumulates. Humans stay at the boundary.
Process automation with explicit boundaries (enforced in the platform, not requested in the prompt), with human sign-off gates where they matter.
Grounded in your institutional memory layer, citation-first, permission-aware, and honest enough to refuse when no source exists.
A living test set of real scenarios scoring faithfulness and decision quality before and after every change, plus runtime input, retrieval and action constraints.
One Forward Deployed Engineer: a senior engineer embedded in your team, accountable for one bounded use case with trust boundaries agreed before the first prompt.
The arc is consistent: pick the use case, write the boundaries down, stand up the memory layer beneath it, ship with evals from day one, and widen autonomy only as evidence accumulates. Built on Anthropic Claude, OpenAI and open frameworks (LangChain, MCP), deployable in cloud, on-premises or fully air-gapped.
No bench. No handoffs. One Forward Deployed Engineer: in your team, on the hook for the outcome.
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