Asana reports a 76x cost reduction (from $36.21 to $0.47 per run) and 5.6x speedup for a browser-agent workflow by stabilizing page history for prompt caching and batch-pruning screenshots, establishing a referenced cost-control pattern for long-running agent workflows.

state: seedheat: mediumuncertainty: mediumconvergesscott: highagent-harnesses inference-economics prompt-cachingAsana

What is this?

Asana published an engineering study reporting a 76× cost reduction (from $36.21 to $0.47 per run) and 5.6× speedup (22.5 min → 4 min) for a browser-agent workflow across 144 runs. The optimization combined stabilizing page history to enable prompt caching with batch-pruning of screenshots. The web search returned no corroborating results, so this grounding rests solely on the case's own description and its two evidence titles.

Why it matters to Scott

Asana's 144-run study is a rigorous, real-world validation of Scott's prefix-caching-economics doctrine ('Keep the prefix stable; append new work; spend cache breaks deliberately where the value is highest') and his long-running-agents framework (stateless workers + stateful external kernel with checkpoint discipline). This is not merely an example of a pattern he believes in — it is a consequential external replication that strengthens the economic argument for context hygiene, prompt-cache stabilization, and screenshot/history management in browser-agent harnesses. Scott can cite this as a dated receipt when arguing that 76× cost reduction is achievable through engineering discipline, not model magic.

ip:concept.prefix-caching-economicsip:framework.long-running-agentsip:framework.context-engineeringip:concept.token-disciplineip:concept.checkpoint-disciplineip:dev:concept.agent-authored-context-compactionip:dev:project.browseruseip:dev:project.scraperadar:concept.prompt-cachingradar:concept.long-running-agentsradar:concept.inference-economicsradar:concept.agent-harnessesradar:cache-hunter-prompt-cache-debuggingradar:browser-agent-token-efficiency-validationradar:tokenops-whole-run-budgetradar:recirculation-running-contextradar:futureos-context-compaction-recall

queries asked of Scott's wikis

prompt-caching strategies for long-running agent loops
inference-economics of browser-use agents
agent-harness patterns for screenshot and history management
cost-control patterns for multi-step tool-using agents
open-weight vs API model economics for agent workloads

Measured heat

now 0 pts/hpeak 0 pts/hcomments 0/hpeers p15momentum: steady2 platformsage 75h

points/hour across evidence · reading as of 2026-10-12 02:59:37.977291+11:00 · deterministic, not a model opinion

How the heat travelled

10-08 13:00	⭐ origin echo-reconstructed	Asana cut browser-agent model cost 76x and runtime from 22.5min to 4min via prompt-cache optimization: stabilizing history for caching and b Asana Engineering on blog (echo) · attributed from reddit.post.1x1v11a	—
10-09 19:46	first on r/artificial · published · +30.8h	Asana says cache changes cut a browser agent's cost 76x Codeblix_Ltd	—
10-09 19:46	amplified on r/artificial 👑	reddit.post.1x1v11a Codeblix_Ltd	peak 1 · 2 comments · 100% of case engagement
10-10 01:31	our radar first saw it · +36.5h	discovery anchor: reddit.post.1x1v11a	—

pace: p34 vs 1243 stories at the 72h mark (now 75h old) — ahead of 3jsbench-llm-3d-generation-benchmark (1.5x), behind acs-local-skill-risk-catalog (0.8x)

Evidence (2) — ⭐ canonical anchor

source	object	author	score	comments
🟠 reddit	Asana says cache changes cut a browser agent's cost 76x artificial	Codeblix_Ltd	1	2
🟧 echo.blog ⭐	Asana cut browser-agent model cost 76x and runtime from 22.5min to 4min via prompt-cache optimization: stabilizing history for caching and b	Asana Engineering	—	—

Interpretation history

2026-10-10T02:01:37Z
grounded: converges/high — Asana's 144-run study is a rigorous, real-world validation of Scott's prefix-caching-economics doctrine ('Keep the prefix stable; append new work; spend cache b
2026-10-10T01:54:44Z
case created — Concrete 144-run engineering study from a real company demonstrating a reproducible prompt-cache optimization pattern that slashes agent inference costs.

Decision trace

10-10 13:52attention_communicatedAsana Engineering's 144-run study across GPT-6.1 Sol and three other frontier models shows stabilizing page history for prompt caching and batch-pruning screenshots reduced per-run cost from $36.
10-10 13:52attention_routeConcrete, reproducible external replication of a load-bearing economic pattern Scott argues for. Dated receipt for 76× cost reduction through engineering discipline, not model magic. Valuable before b
10-10 13:48attention_candidatecreate
10-10 13:01groundAsana's 144-run study is a rigorous, real-world validation of Scott's prefix-caching-economics doctrine ('Keep the prefix stable; append new work; spend cache breaks deliberately where
10-10 12:54createConcrete 144-run engineering study from a real company demonstrating a reproducible prompt-cache optimization pattern that slashes agent inference costs.