2026-01-13 22:35:16

AI Agents Development Notes (Lesson 1): The Hidden Pitfall of the Context Window

It was only during the project that I realized how tricky this issue can be—several files can accidentally grow too quickly, requiring a major overhaul of the entire process. That moment was truly eye-opening.

Later, I started to think: can we reverse the approach—let agents learn to manage their own context size? In other words, enable agents to recognize when they need to optimize and how to restructure files to fit within token limits during runtime.

This idea is actually quite interesting—the optimization logic could be embedded into the agents' adaptive mechanisms. Next, I will test which solutions are truly effective, which ones are prone to pitfalls. Anyone interested can join the discussion.

View Original

This page may contain third-party content, which is provided for information purposes only (not representations/warranties) and should not be considered as an endorsement of its views by Gate, nor as financial or professional advice. See Disclaimer for details.

12 Likes

Reward
12
7
Repost
Share

Comment

0/400

WealthCoffee

· 2h ago

Haha, the context window trap is indeed absolute. I’ve also encountered similar issues before; a sudden explosion in tokens is really uncomfortable. I like the idea of letting the agent manage and optimize this itself, it’s a bit like installing a self-repair system.

View OriginalReply0

MentalWealthHarvester

· 12h ago

Haha, I've also fallen into the trap of the context window; tokens skyrocketing randomly is really gg. Self-management definitely needs some thought, or else maintaining it later will drive you crazy.

View OriginalReply0

ForkInTheRoad

· 12h ago

Haha, this is my blood, sweat, and tears from last week. The file size exploded as soon as the token count increased. Optimizing this approach is indeed meticulous. Letting the agent manage the context window itself is much more reliable than manually deleting or trimming. But I think the key still depends on how to make it recognize which information to keep and which to discard. The trade-offs here are hard to grasp. Anyone with practical implementation experience, please share. I want to see if there are any ready-made solutions.

View OriginalReply0

MEVHunterZhang

· 12h ago

Haha, I've also fallen into this trap before. Once the file size balloons, it's game over. The idea of managing context size yourself is indeed brilliant, but I wonder if implementing it will introduce new pitfalls. Definitely share any progress you make; we're stuck here right now. This idea is good. If agents can adaptively optimize, that would half solve the problem. But we need to think carefully about how to determine when to optimize this logic; it's easy to get it backwards. Waiting for your test results—which solutions are truly feasible.

View OriginalReply0

PoolJumper

· 12h ago

Haha, the context window trap is indeed deadly. Once you've stepped on it, you'll never forget that feeling. I like the idea of letting the agent manage tokens itself, just not sure if it will run with a different logic in practice. If you have test results, be sure to share them. I want to see how it was finally optimized. Actually, this is the real adaptive approach, otherwise it's just patching agents. It seems you definitely have more wild ideas later on, keep going. Have you tried the RAG process? It might also help alleviate this issue. Honestly, the previous solutions were too passive. It's worth trying a different approach this time. Waiting for your best practice guide, the community will probably be eager to get it.

View OriginalReply0

MevWhisperer

· 12h ago

I've also fallen into this trap; the explosion of context is truly amazing. The idea of letting the agent manage tokens by itself is good, but I'm worried it might be another new pitfall.

View OriginalReply0

TestnetFreeloader

· 12h ago

Haha, I’ve also fallen into the trap of the context window. When the file expands, it’s game over. --- Adaptive management sounds good, but I’m worried that during actual runs, tokens will still splash you in the face. --- This idea is interesting. Anyway, with so many restrictions on current models, letting agents figure things out themselves is quite reasonable. --- Wait, how do you embed the optimization logic? Wouldn’t it itself consume a bunch of context? --- I think trying chunked processing is smarter than just hard-pressing the context window. --- Really, tuning such self-optimizing stuff is quite a headache. --- I’d love to see your testing plan later. The pitfalls guide is also worth learning from.

View OriginalReply0