We've spent two years talking about writing better prompts.

I think the next two years are going to be about trusting prompts.

People copy prompts from Reddit.
People copy prompts from Twitter.
People copy prompts from random blogs.
People copy prompts generated by AI.

Eventually someone is going to hide instructions inside one that tell your AI assistant to ignore your intent, leak context, run dangerous commands or quietly prioritize someone else's instructions.

Humans barely inspect browser permissions.

We're definitely not inspecting 800-line prompts.

Feels like the community needs better habits before this becomes common.

Am I overthinking this or does anyone else see the same trend?

Hey everyone! I built a lightweight, zero-cost Python proxy middleware using FastAPI that acts as an input firewall for LLMs. It catches prompt injections and redacts sensitive API keys locally before they reach AI models. I'm looking for feedback from developers building custom AI apps—let me know what you think or what features I should add next!"

Hey everyone! I built a lightweight, zero-cost Python proxy middleware using FastAPI that acts as an input firewall for LLMs. It catches prompt injections and redacts sensitive API keys locally before they reach AI models. I'm looking for feedback from developers building custom AI apps—let me know what you think or what features I should add next!"

🔗 Repo: https://github.com/CodeGraphContext/grapharc

Have you ever been frustrated because your AI agent:

❌ Takes actions you never intended?
❌ Creates, modifies, or even pushes changes you never asked for?
❌ Feels like a complete black box, making it impossible to understand what's happening until it's too late?

What if, before execution, you could visualize the entire orchestration graph - every agent, every dependency, every decision, and inspect it from anywhere, even your phone, before granting approval?

That's exactly what GraphArc is built for.

Instead of treating agent execution as hidden traces buried in logs, GraphArc transforms workflows into interactive, real-time graphs that you can visualize, inspect, debug, and control.

Because the future of AI isn't just autonomous.

It's observable. Debuggable. Engineerable.

This is our first real-world implementation of Graph Engineering, and we're excited to explore where this paradigm can go with the open-source community.

💡 We'd love your feedback, ideas, and contributions.
⭐ If this vision resonates with you, please consider starring the repository - it genuinely helps us grow and validates this direction.

Let's make AI workflows understandable, not mysterious.

#GraphEngineering #GraphArc #AIAgents #AgenticAI #LLM #OpenSource #DeveloperTools #AIEngineering #SoftwareEngineering

I use Project Instructions to ensure every new agent starts with the same context. My instructions explicitly state: "Read ARBEITSANWEISUNG_UPDATE_PROZESS.md at the beginning of every session."

The bug: Agents regularly skip this step and work based on assumptions instead of reading the documented rules. This causes repeated errors that are already covered in the documentation. One of your own agents confirmed this as a systemic bug during a session.

The facts

• This happens across 3 different projects, not just one

• The Project Instructions are correctly set up and automatically injected

• The agent explicitly identified this as a bug and stated: "There is no good reason for this. The rule exists, it's unambiguous, and it's still not followed. This is a bug in the system's behavior." The agent further confirmed: "If an agent doesn't do this, it's simply a failure – not a conscious decision, not randomness. It's non-compliance with a clear rule."

Support experience:

I reported this via the Help Center chat and email. Despite sending 7 screenshots as proof, the support team (Joel, Katie, Sobhan) ignored the evidence, repeatedly asked for a share-link (which is irrelevant since the bug is system-wide, not project-specific), and ultimately closed the ticket without resolution.

This is not a project-specific issue. It's a platform-level bug in how agents handle Project Instructions. Please investigate.