Top
Best
New

Posted by pchristensen 12 hours ago

The State of Context Engineering(www.dbreunig.com)
158 points | 39 commentspage 2
lhk931122 8 hours ago|
Until a few months ago I did it this way, but OpenAI and Anthropic built their own harnesses, and since those end up conflicting with the harness I built myself, having no setup at all actually ended up performing better. As a result, it doesn't seem necessary to set up rules or memory separately, and if I do, using skills or agents made of only logging and flow (without things like rules or guardrails) seems like the best option going forward.
bertmuir 24 minutes ago|
I think that makes sense for now in individual contributor cases, but the turnkey solutions have gaps when it comes to the most powerful capabilities and I don't see harnesses going away any time soon for that.

E.g. you can't use coworking/projects for shared memory in most domains because this hinges on compacting/refactoring true reusable facts and organisational knowledge (as opposed to code, schemas, technical references). The heuristics to find and decide on candidates for memory in this case are quite specific to the institution you work in. For example, the boundaries of the domain of "sales" versus "marketing" vary lots from place to place, as does the trustworthiness of certain staff, the way they they communicate or make decisions that contain the knowledge you want to store to memory, and so on.

I'm finding harnesses are still vastly better for grabbing this sort of complex institutional knowledge. Also, they're just a bit of a safety net for any frontier labs going bankrupt in the next couple of years, if we need an easy way to port over to open weights.

nottanjune 6 hours ago||
Forgetting is the part I see break first. Old facts in memory don't get deleted, they get contradicted, and the model happily picks whichever one is closer in the prompt. What's worked better for me is having this really cool way of jev compaction, there was a youtube video out there somewhere that spoke about how to get compaction to be super fast, cheap and have it retain the most useful information from the context compaction.
bickfordb 7 hours ago||
I can't tell if this engineering or just autocomplete that is mostly helpful, sometimes.
jdw64 10 hours ago||
>This is the advice I keep giving now. Someone says, “My coding agent’s doing something weird. Claude’s been nerfed.” And I ask, “How big is your context?”

That’s really true, but on the other hand, if there’s too little information, it also ends up working in strange ways. Most AGENT code anti-patterns work well at a medium amount of context, but when there’s too much or too little information, they don’t behave properly.

triyambakam 4 hours ago||
The cardinality of terms feels too high and too much semantic overlap between different terms.

I would like to counter with Theo Browne's "Your Prompts Kinda Suck" [1] I'm not a "fan" of Theo but his perspective here is useful.

[1] https://www.youtube.com/watch?v=m-B3jIMMmUE

viccis 5 hours ago||
Anecdotally I only stuggle with this with Claude Code. Codex has been great at auto managing its context and, when combined with how I handle memory outside of the session, I haven't thought about context window size in ages when using Codex.
vcryan 7 hours ago||
I thought the price reduction was because both companies implemented Deepseek's published research which demonstrate effective approaches to lowering the cost of inference while maintaining quality. Thanks to Deepseek, they did lower their costs and they passed that in to their customers.
jthomas1 7 hours ago||
interesting read, thanks for sharing
lioeters 8 hours ago||
"Engineering"
agentic-affairs 1 hour ago|
[flagged]
More comments...