AI agents that behave like good employees.
I build production AI chatbots end-to-end. Design, prompts, code, deploy. Two live agents for CoverTurn shown here. A chatbot that captures leads after hours, on Claude Haiku and Cloudflare Workers. An autonomous outbound voice agent on Retell. Both designed against WCAG 2.2 AA, Nielsen's heuristics, and the Cooperative Principle.
Captures leads while the owner is asleep.
Runs sales calls end-to-end.
Two agents. Both customer-facing. Both have to feel honest.
One inbound chatbot to capture leads from the website at any hour. One outbound voice agent to run calls and book demos without me on the line. Both customer-facing, both representing the brand.
The constraint that shaped both was trust. They cannot oversell, cannot lie about what they are, cannot loop, cannot embarrass. Designed against the same standards as a human employee, and built so the underlying model can be swapped without rewriting the conversation.
Treat each agent like a junior employee.
Grounded in the conversation design canon (Hall, Pearl, Grice), accessibility for non-visual interfaces (WCAG 2.2 AA, ARIA live regions, focus management), and Gong's analysis of more than three hundred million cold calls. Cross-checked against transcripts from my own early test runs.
Working theory: give every agent a script, a voice, and a clear set of rules about when to escape. The rest is craft.
Designed for after hours, scoped against Nielsen.
A small orange widget in the bottom-right of every CoverTurn site, running on Claude Haiku. One job: capture a lead, qualify lightly, hand off by email. Built against Nielsen H1, H5, H6, H7, H10 and WCAG 2.2 AA.
Persona rules. Forward-looking framing only. One or two sentences per turn. Repair on off-script input. Honest disclosure on any "are you a bot" question. Nothing about the agent is allowed to deceive a user about what it is.
The configuration that ships
Hosted on Cloudflare on the same domain as the site to keep latency low. Every conversation is summarised into a short email to the owner. From the owner's perspective: wake up, find "a lead came in at 11pm, here's what they wanted, here's their number".
An outbound caller that talks like a person.
Calls real prospects, books demos onto Cal.com. No UI, no buttons. If the first three seconds sound like a script, the prospect hangs up. Voice UX is mostly latency, prosody, and turn-taking, and little else.
First script was an information-delivery pitch. It went nowhere. Real calls don't work like pitches; they work like conversations.
The 4-yes Socratic flow
The version in production (v19) is built on a four-yes structure: Cialdini commitment, SPIN situation and problem questions, Sandler pain funnel compressed for cold-call attention spans.
Permission-based opener, two discovery questions each followed by a mirror-back yes, then a qualifying yes, then the demo offer. Four yeses before the ask.
Settings shipped. Latency: 500–750ms end-to-end, inside the human-pacing band. Interruption sensitivity at maximum, so the agent waits rather than talks over real prospects. A separate inbound agent handles callbacks with a context-aware greeting.
Six steps. Disciplined, not improvised.
Read the canon and the user data
Conversation design research for the agent, real transcripts and chat logs for the user. Both, every time.
Spec before prompt
Persona, voice, openings, escape hatches, failure modes, a11y floor, latency budget. Written as a brief.
Pair with Claude in Cursor
Spec in, working code out. The designer's job becomes editing for taste, a11y, and brand voice.
Test live
Five live calls or twenty real chats teach more than fifty internal tests. Read every conversation end-to-end.
Version like code
Nineteen voice agent versions in two weeks. One named change, one hypothesis per version.
Audit every release
Forward-looking framing, locale, a11y floor. Copy audit before every deploy. Regressions treated like bugs.
Two agents in production. Real conversations, real data.
Conversation design is product design without the UI.
Same heuristics, same accessibility floor, same craft. Every turn the agent takes is a layout decision in time instead of in space. AI-native design isn't faster design at the same level of taste; it's the same speed of design at a higher level, because the time saved on boilerplate gets reinvested in research, conversation review, and audits.