You'd never hand a new hire one line and expect great work. No context on the company, the reader, the standards. That's exactly what we do to AI, then call the output generic. It's not undertrained. It's un-onboarded.

#contextengineering #promptengineering

A new arXiv paper proposes structured memory that decouples stored experience from active context for token-efficient continual learning in LLM agents. This could make long-running enterprise or scientific…

#LLMs #ContextEngineering #AIagents #MachineLearning
https://arxiv.org/abs/2610.02687

Without tests, you’re just guessing.

Registries don’t keep your codebase safe. Testing does.

Patrick Debois on testing agent skills, context & error budgets for reliable AI deployments.

🔗 Watch now: buff.ly/kIAuTeo

#InfoQ #AIAgents #SoftwareTesting #ContextEngineering

Context Engineering in Production #20

Don't measure AI coding only by output quality.

Track:

• context size
• prompts/task
• retrieval accuracy
• cost/task
• time/task

If context engineering works, those numbers should move.

#ContextEngineering #AIEngineering #SigMap

Context Engineering in Production #19

"AI hallucinated."

Don't stop there.

Check:

Fake symbol?
Fake file?
Invented API?
Wrong parameter?
Unsupported claim?

Groundedness can be tested against repository evidence.

#ContextEngineering #AIAgents #SigMap

Context Engineering in Production #18

The AI produced an answer.

Now verify it.

Do those files exist?
Are those symbols real?
Are the parameters correct?
Is the answer grounded in retrieved context?

Generate → Verify.

#ContextEngineering #AIAgents #SigMap

Context Engineering in Production #17

Changed 4 files?

Don't rebuild context from 4,000.

Start with the diff.

Then expand outward only when dependencies require it.

Context should grow with evidence, not repository size.

#ContextEngineering #Git #AIAgents #SigMap

Context Engineering in Production #16

Before changing code, ask:

Who depends on this?

Finding the target is only half the job.

Understanding the blast radius tells you what the change could break.

Navigate → Impact → Edit.

#ContextEngineering #BlastRadius #SigMap

Context Engineering in Production #15

Traditional workflow:

Search → open → wrong file → retry.

Better workflow:

Question → rank relevant code → inspect only what matters.

Exploration has a token cost.

Make retrieval earn every file it opens.

#ContextEngineering #AgentNavigation #SigMap

Context Engineering in Production #14

Context compression shouldn't mean:

"Remove useful information."

It should mean:

"Represent useful information with fewer tokens."

Signatures, relationships and ranked context preserve signal while dropping noise

#ContextEngineering #TokenEconomics #SigMap

Context Engineering in Production #13

Don't go:

Repository → AI

Go:

Repository
↓
Module
↓
File
↓
Symbol
↓
Implementation

Each step removes irrelevant context.

By the time AI sees code, most noise should already be gone.

#ContextEngineering #AIAgents #SigMap

Context Engineering in Production #12

Finding "RankingEngine.score()" is step one.

Now ask:

Who calls it?
What does it call?
What depends on it?

Code becomes useful context when you understand its relationships.

#ContextEngineering #CodeRelationships #SigMap

Context Engineering in Production #11

Don't start by loading implementation.

Start with structure:

What exists?
Where?
Who calls it?
What does it call?

Then open implementation only where needed.

Structure first.
Details on demand.

#ContextEngineering #RepoIntelligence #SigMap

An early memory design kept "waiting for a decision" separate from "not enough evidence." Both pause the work, but leave different questions unresolved. A handoff that says only "on hold" loses that distinction. #AI #ContextEngineering

Generic AI output isn't a ceiling, it's a symptom. Give the model your role, your audience, and three lines in your actual voice first. The output changes category - from brochure copy to a real first draft.

#contextengineering #promptengineering

Context Engineering in Production #10

An agent may not need a 2,000-line file.

It may need:

AuthService.login()
→ TokenService.issue()
→ SessionStore.save()

Symbols preserve structure without dragging every implementation detail into context.

#ContextEngineering #AIAgents #SigMap

Context Engineering in Production #9

Search asks:

"Where does "auth" appear?"

Retrieval asks:

"Which code actually implements the auth flow?"

One returns matches.

The other returns context.

That's a huge difference for coding agents.

#ContextEngineering #RepoIntelligence #SigMap

Context Engineering in Production #8

Context starts before your prompt.

Extensions.
MCP servers.
Open repos.
Tool output.

A noisy workspace can make an AI session expensive before question #1.

Reduce the environment before optimizing the prompt.

#ContextEngineering #MCP #SigMap

Context Engineering in Production #7

Caching can make repeated context cheaper.

It doesn't make bad context useful.

30K cached tokens of noise are still 30K tokens of noise.

Cache optimizes reuse.

Context engineering optimizes what deserves reuse.

#ContextEngineering #LLM #SigMap

Context Engineering in Production #6

Keep sessions focused.

Good:
Auth → JWT → Claims → Refresh

Bad:
Auth → Terraform → Search → Databricks

Every topic jump carries old context into a new problem.

Focused sessions preserve signal.

#ContextEngineering #AIAgents #SigMap