Skip to main content

Work · 5 entries · 3 shipped · 2 in build

The log

Every entry uses the same format: the problem, the constraints, the architecture, three numbers and what broke. Production work is anonymised: no employer names, figures as ranges.

  1. LOG-012025–26

    Migrating a 70K-conversations-a-day voicebot from NLU to hybrid GenAI

    Moving a regulated, high-volume customer-service assistant off intent classification without breaking what customers and the business rely on.

    Shows → End-to-end ownership of a production migration: architecture split, evals, KPI redesign, vendor SLAs, change management.

    In productionTier-1 Italian enterprise · regulated · voice + chat
  2. LOG-022026

    A vendor-neutral business case for AI agents

    An open calculator that ties an AI agent to the P&L: containment ramp, repeat contacts, per-minute vs per-resolution pricing, payback.

    Shows → Translating agent performance into money a CFO will sign off on, and knowing where the numbers lie.

    LivePublic tool · runs in the browser
  3. LOG-032026

    GenAI Evaluation Kit: measuring whether a conversational agent actually works

    The evaluation method from production, packaged: three quality pillars, 18 LLM-as-judge prompts, a golden-dataset template and a scoring dashboard.

    Shows → Eval mindset: golden datasets, judge calibration, quality gates before real traffic.

    ShippedDigital product · sold to teams running GenAI assistants
  4. LOG-042026

    Deployment in a box: a voice agent for a fictional utility, end to end

    A full customer deployment, compressed: discovery, a voice agent with three tools over MCP on simulated APIs, evals, a KPI dashboard and an honest post-mortem.

    Shows → What a deployment strategist does in the first 90 days, in a form you can run.

    In buildOpen-source reference deployment · fictional customer
  5. LOG-052026

    AI-to-AI call lab: what happens when a customer's agent calls your voicebot

    A test bench where a customer-side AI agent calls an enterprise voicebot. Measuring loops, mutual detection, fraud surface and cost.

    Shows → Thinking one step ahead of the customer: the next failure mode of voice deployments.

    In buildResearch prototype · follows up my paper on AI-to-AI calls