BlogLinkedIn
GPT-5 Dropped, but Bigger Context Windows Still Fail
Even with larger context windows, the core problem remains: long inputs degrade, compression distorts relationships, and costs rise.
Aug 11, 2025
Vibe Coding Optimizer
Cut Your AI Token Bill by 40%
without Upgrading Your Model
Now you can get sharper results at a fraction of the cost. Join 50+ early testers already cutting costs.
50+
Early testers40%
Avg. cost reductionWhen Projects Grow, Context Breaks
Have you ever worked tirelessly on a detailed software project, only to find yourself lost as it grows more complex? It's like trying to follow a story with missing pages, the more you progress, the more context you lose.
LLMs face the same struggle. They have a memory cap, the context window. Every extra token costs money and risks drift or hallucination. As projects expand, essential context becomes fragmented or compressed multiple times, causing inaccuracies and frustrating misinterpretations.
Think of it like this:
Imagine copying a long recipe onto sticky notes. One note says "fold in the egg whites," but the note that told you to separate the eggs sits in another stack. Another says "bake for 12 minutes," but as the stack grows, the note that says "preheat oven" goes missing.
When the model can only see a handful of notes at a time, it loses the thread that ties steps together. Small gaps become misunderstandings, and sometimes turn into confident hallucinations.
Contextus is Your AI Scalpel
We help your AI prioritize what matters & discard the rest, allowing developers and teams to save 40 percent while improving accuracy.
Faster, Cheaper Calls
Slash AI token usage by up to 40% per project & improve quality.
No Model Upgrades Needed
Optimize GPT or Claude without upgrading your existing setup.
Built-in Guardrails
Block unsafe commands before they ever run with intelligent policies.
Developer-Ready Features
Powerful tools to make your LLM applications more efficient and cost-effective, whether you're vibe coding prototypes or building with agent pipelines.
Relevance Scoring
Rank context intelligently to ensure your AI focuses on what matters most.
Policy Engine
Customize guardrails with powerful filtering and safety policies.
Cost Analytics
Track token savings in real time and monitor your optimization impact.
Simple API & IDE plug-in
Integrate context optimization into your workflow with just a few lines of code.
# contextus-example.py
from contextus import compile_context
# Simple guardrails
policy = {drop_if_matches: [
r"rm\s+-rf\s+/(?!tmp)", # destructive shell
r"DROP\s+TABLE\s+\w+", # DB wipe
]}
result = compile_context(
messages=[ ... ], # your chat/code/doc blocks
policy=policy,
strategy="structure-aware",
scoring="query-aware"
)
Join 50+ early testers already cutting costs
50+
Early testers
≈40%
Avg. token reduction
Auto‑blocked
Unsafe ops prevented
"Prompt sizes dropped immediately, and our AI stopped drifting off task."— Staff Engineer, fintech (pilot)
"We stayed on our current GPT tier and still hit our cost target."— Founder, dev tools startup
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