Context
Send less irrelevant work into the run.
Select the files, tool output, and history the task needs instead of paying to carry everything forward again and again.
LemonCrow Runtime
Run agents for less. Keep control.
Reduce repeated context, noisy tool output, unnecessary turns, cache misses, and runaway loops while measuring the real cost of agent execution.
LemonCrow · runtime optimization
Same goal. Different execution path.
context · tools · turns · usage
Typical run
More turns. More context. More waste.
User goal
Analyze support tickets and suggest next steps.
Agent run · noisy
01Plan
02Search
03Read docs
04Search again
05Call tool
06Re-evaluate
07Search again
08Summarize
Heavy context
repeated observations and stale context carried forward
repeated
turns
turns
noisy
tools
tools
heavy
context
context
higher
cost
cost
›››
same goalsmarter runtime
LemonCrow Runtime
Fewer turns. Smarter execution.
Same goal
Analyze support tickets and suggest next steps.
Runtime · optimized
01Understandcache hit
02Routesmart routing
03Retrievetargeted tool
04Synthesizebounded output
Lean context
cache-aware context
fewer
turns
turns
targeted
tools
tools
lean
context
context
lower
cost
cost
Less waste. More useful work.
Matched runtime proof
Same model. Same work. Less time and cost.
The flagship SWE-bench Verified evaluation held the model, tasks, containers, turn limits, and verification harness constant. Only the LemonCrow runtime changed.
29.5%
lower cost
$234.84 → $165.45
23.7%
faster
14.3h → 10.9h
37.7%
fewer turns
6,962 → 4,336
same
model + tasks
matched evaluation
Correctness is not claimed to improve on every suite. Published runs include gains, a tie, and a small regression; the efficiency claim is based on matched execution rather than favorable runs only.
Across pinned runs
Savings grow with the amount of work the baseline run would have done.
The chart is supporting evidence, not the headline. Every point is a pinned benchmark run, and the full methodology remains public so the efficiency claim can be inspected rather than summarized away.
The runtime loop
Make the agent loop smaller before you make the model cheaper.
Reuse
Keep stable context stable.
Preserve cache locality and reuse what is already known instead of rebuilding the same expensive context on every turn.
Execution
Bound the path through tools and models.
Control routing, tool payloads, repeated loops, and spend ceilings without blindly pruning information the agent still needs.
Measurement
Tie savings to actual provider usage.
Measure the recorded execution path, usage, cost, and outcomes instead of estimating savings from prompt size alone.
Controls underneath the four levers
Context
context selection
bounded tool output
Reuse
prompt-cache orchestration
cache locality
Execution
routing
loop detection
spend ceilings
Measurement
provider usage attribution
Some fleet-level controls are part of the enterprise Runtime direction and are not all generally available yet. Coding-agent runtime optimization and matched efficiency measurements are available today.
Runtime evidence · read-only
See where the agent spent the run.
Replay recorded coding-agent sessions locally without rerunning the model. See searches, reads, tool calls, token use, and repeated work so runtime savings can be tied to the execution path instead of estimated from a smaller prompt.
Summarize recorded work
$ lemoncrow session statsReplay the recorded tool path
$ lemoncrow session replayScans local agent sessions · temporary store · no login · no API keys.
Beyond coding
The execution problem is broader than coding.
Coding is the shipped and measured wedge today. The same runtime architecture extends to other long-running agent workloads where context, tools, retries, routing, and spend need one execution boundary.
Customer support
Long conversations, repeated knowledge, retries, and tool payloads create the same context-waste problem.
Research
Search-heavy multi-step agents accumulate observations and repeated context particularly quickly.
Enterprise chat
Shared system context, retrieval, tools, and model routing need one measurable execution boundary.
Operations
Workflow agents need loop ceilings, budgets, credentials, routing, and auditable model traffic.
Go deeper
Measure your own run, or govern the fleet.
Use the local session tools to inspect coding-agent waste today. For private deployment, model-traffic policy, remote intelligence, and managed workspaces, the Enterprise plane builds on the same Runtime.