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Is your agent wasting tokens on files
that don't matter? To get highquality
code, you need to feed the model
highquality signals. Let's talk about
context engineering. LLMs don't have
infinite attention. Every token is
budgeted. Blow your context window
budget and your agent gets slow, vague,
and starts messing up. A context window
is just the agent's working memory. Too
small and it forgets what matters. too
big and messy and it can't focus on the
right things. So, your job is to curate
your agents context. Keep what's
relevant to this step and compact or
dump the rest. Summaries instead of full
logs, key decisions instead of every
chat line. Delete stale stuff. Most
contacts should expire. One way to do
this is to adopt a multi- aent
architecture. Spin up specialized
instances. [music] one for research, one
for code, one for QA. Let them take
notes and make written reports for each
other [music] instead of piling
everything into one giant prompt. Don't
forget to clear context [music] or start
with fresh agents when changing tasks.
This works really well with spec driven
development. A clean spec and clean
context can help you achieve major
improvements to agent code [music]
quality. If you want agents that stay
accurate, efficient, and on track, learn
to manage and engineer their context, be
deliberate with what you load, and you
unlock agents that reason cleanly
instead of drifting into chaos.
To get high-quality code, the model needs to be fed high-quality signals. Here are six best practices to get the most out of your agents with context engineering. Subscribe to Google for Developers → https://goo.gle/developers Speaker: Jasmyne Roberts