Notes from Falconer

Essays, announcements, and research from the team behind Falconer.

Agent Personalization: an agent that knows you

Falconer now tailors every response to who you are. Agent Personalization builds a lightweight, transparent profile of your role, team, and preferences — fully editable, with every attribute traced back to its source.

By Apoorva Shete

Your context is more than training data

Everyone has access to the same frontier models. Your competitive advantage is institutional context — the decisions, tradeoffs, and battle scars inside your four walls. Here's why curating that context is now existential.

By Dave Nunez

Falconer Update: Full self-driving docs

Falconer Update keeps your documentation in sync with your codebase automatically. Toggle it on for any document and choose Review mode for human-in-the-loop edits, or Full Self-Driving mode to let Falconer handle it entirely.

By Matt Zhao

Falconer Generate: from repo to doc set in minutes

Falconer Generate turns a connected GitHub repo into a structured documentation set, helping teams get documentation started faster.

By Lilu Xu

The source of truth for high-speed teams

Our mission is to capture all of your important context, keep it up to date, and make it easy for you to deploy it wherever you want: your teammates, your customers, your coding agents.

By Dave Nunez

Rethinking data ingestion as a DAG

How we reduced data ingestion time from hours to minutes by reimagining our pipeline as a directed acyclic graph. This post covers the architectural shift from async workflows to job queues, the migration strategy we used to preserve behavior, and the observability patterns that helped us identify and isolate bottlenecks at scale.

By Apoorva Shete

LLM-as-a-Courtroom

How we built a multi-agent courtroom simulation to decide when code changes require documentation updates—and why the legal system is humanity's best framework for binary decisions under uncertainty.

By Aryaman Agrawal