Instant compaction instead of summarization prompts
Tamara's case is about context, not marketing: why compaction in 2026 is still a summarization prompt, when JEV can do it instantly by scoring every tool call and dropping what is irrelevant.
Original post "found the perfect use case for @typesafeai Jev: instant compaction. in 2026, why is compaction still a summarization prompt? Jev can make it instant by scoring every tool call and dropping what's irrelevant" Read the original post on X
The numbers
Reported reach is the striking part: 3,657,994 impressions, 10,667 likes, 8,155 bookmarks, 316 quotes. It is the most-shared JEV case in this set.
The problem it names
Compaction today means asking a language model to summarize the conversation so far. That is generation work doing a keeping-or-dropping job, which is slow, expensive, and lossy in ways nobody controls.
Reframed as a decision: for each tool call in the context, keep it or drop it. That is a per-item judgment against a standard, which is exactly the shape a decision model handles in parallel.
Why this matters beyond agents
The same pattern applies anywhere context grows: transcripts, research notes, support threads, call summaries. The question is never "write me a shorter version," it is "which of these items still matter."
How to copy it
- List what accumulates in your context and what makes each item worth keeping.
- Define keep or drop as the fixed decision, with a reason field.
- Score the existing context, drop the fails, and stop paying a writer to do a judge's job.
Related
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