01 /Research

Research on product engineering & AI systems.

Original research on full-stack craft, AI systems, automation, and the product decisions behind what I build.

Index · 06 entries

2026 — Present

  1. 01
    NoteToday

    Before you buy an AI receptionist, audit 7 days of missed calls

    Use one week of your own call history to decide whether after-hours or overflow call coverage is worth testing—without relying on generic revenue claims.

    5 min readvoice-ai · hvac · operations
  2. 02
    NoteToday

    Your voice agent understood the call. Did it capture the customer?

    Names, emails, phone numbers, and addresses are easy to hear incorrectly and expensive to save incorrectly. Here is how I would test customer-detail capture before a voice agent takes real calls.

    6 min readvoice-ai · transcription · testing
  3. 03
    NoteToday

    When can an AI receptionist safely say 'you're booked'?

    A calendar timeout can leave a booking in an uncertain state. Here is how I would test confirmations, retries, and dispatch handoffs before an AI receptionist takes real calls.

    4 min readvoice-ai · hvac · testing
  4. 04
    NoteSeptember 6, 2026 (1d ago)

    What to test before an HVAC voice agent takes real calls

    A practical pilot checklist: service-area checks, uncertain scheduling, human handoff, failure handling, and the records dispatch actually needs.

    4 min readvoice-ai · hvac · testing
  5. 05
    ThesisMay 20, 2026 (3mo ago)

    Voice context is a timing problem

    Long voice calls slow down for a familiar reason: too much history, not enough context window. The usual advice is to summarize the old turns. That assumes you have time to run the summary. In voice, you don't. The fix isn't a better summary. It's deciding when the summary runs.

    2 min readvoice-ai · agents · latency
  6. 06
    ThesisApril 20, 2026 (4mo ago)

    The Contact Graph: why agents need a social network, not a database

    Agent memory today is a vector store — text chunks retrieved by keyword similarity. That breaks the moment you need to remember who said what, how reliable they were, or what they still owe you. Here's a different primitive: the contact graph. Memory modeled as a social network, with facts attached to relationships.

    8 min readagents · memory · context-engineering