Share graph · provenance running forward
Ollie Grant
Product engineer · firm
What they dropped, which clusters it landed in, what got elected, and which experiments and findings descended from it. Everyone’s is visible to everyone, symmetrically. Show outcomes, not counts — no totals, no rankings, no rollups.
Dropped
signals with this person attached
Landed in
distinct clusters
Elected
of those, now fields
Descended
experiments and published items
Drops
What descended
Use a structured episodic store with summarised recall, not a raw vector memory
Route through a gateway you control; do not standardise on a vendor's
Prompt caching: use for stable prefixes over 2k tokens; expect 30–45%, not 60%
Every LLM judge ships with a human agreement score or does not ship
Agentic delivery works when the spec is the artifact; do not start with the code
Not yet: realtime voice for AU contact centres above tier-1 triage
Distil to a small model only after the frontier baseline is measured on the same eval
Put backpressure on agent fan-out before you put it on the model
Agents act under delegated, scoped, expiring authority — never a service account
Measure ROI from telemetry and cycle time, not surveys
Give citizen developers a paved road and a retention policy, not a review board
What does inference actually cost right now?
Retrieval or fine-tuning for this?
Which memory layer should a new agent use?
What eval tooling do we use?
When do we need to move to post-quantum crypto?
The direction of agentic development
Learning without weights: where continual learning actually lands
Memory layer bake-off on a 40-session support corpus
Cost-aware routing across three model gardens
Token cost ledger across six client patterns
Judge calibration against human panel
Voice agent latency floor for AU telco
Release canary suite v2
Edge SLM for in-store classification
Agentic QA on a regression-heavy codebase
Spec-first agentic delivery on a live internal repo
Nightingale measurement run: coding-assistant ROI
Delegated-authority broker for agent tool calls
Compiling agent experience into a persistent skill wiki
Backpressure patterns for agent fan-out
Temporal decision memory for a claims agent
Shared-context AI surface for a delivery pod
Non-weight-bound learning via retrieval-updated skills
Follow this person’s finds
Following someone whose drops are consistently good is the internal version of the external voice watchlist, and often a better source than any detector.