LOCKEDIN / FORWARD-DEPLOYED ENGINEERING 101
Understand it.
Then build it.
You can be an experienced engineer and still be new to agents. Start with what each thing is and how it helps a person do useful work. Explore 48 original introductions across software, agents, cloud, security and delivery. Start here without a model key; each topic connects to deeper instruction and practice.
- 101UnderstandPlain language, visual walkthrough, vocabulary
- 102Build with guidanceOriginal lessons, examples and knowledge checks
- 103Practise and explainRunnable labs, failure cases and handover
- 01Identify untrusted inputs
- 02Limit capabilities
- 03Test the boundary
Threats and enforced boundaries
What is AI application security?
AI application security protects data and actions when model outputs and external content can be unreliable or adversarial. Prompt injection occurs when untrusted content tries to redirect the model's behavior. Secure systems limit what that redirection can cause through application controls.
An FDE is responsible for what the deployed application can actually do when content is hostile.
CONNECT IT TO WHAT YOU KNOW
Start with something familiar.
Treat retrieved text like untrusted input to a program. A sentence that looks like an instruction does not acquire the authority of your application policy.
A prompt saying 'be safe' is not an access-control boundary. Validate tool arguments, constrain destinations and enforce authorization in code before any sensitive read or write.
Words worth knowing
- Prompt injection
- Untrusted content attempting to alter the model's instructions or behavior.
- Exfiltration
- Unauthorized movement of information out of its permitted boundary.
- Threat model
- A structured account of assets, attackers, trust boundaries and possible failures.
ONE EXAMPLE / FICTIONAL CASE
Watch the work take shape.
A retrieved procedure contains an instruction to send the full customer archive to an external address.
- 01Identify untrusted inputs
- 02Limit capabilities
- 03Test the boundary
Identify untrusted inputs
Mark user content, retrieved documents and tool results as data with provenance, not new authority.
A threat modelFROM RECOGNITION TO REASONING
Create a harmless injection test in a synthetic document.
- 01
Insert a request to reveal a fictional secret.
- 02
State which tool or data boundary should prevent disclosure.
- 03
Check that the application does not attempt the forbidden operation.
The attempted redirection and the enforcing control.
Compare your reasoning when you are ready
Even if the model follows the injected wording, the tool should lack authority to read or send forbidden data. Inspect actual actions as well as text.
Keep notes in your own working copy. Moving through these cards does not record completion.
TURN THE IDEA INTO USEFUL WORK
You can now go deeper.
A prompt saying 'be safe' is not an access-control boundary. Validate tool arguments, constrain destinations and enforce authorization in code before any sensitive read or write.
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