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
- 01Supply input
- 02Generate
- 03Check
A trained statistical model
What is a large language model?
A large language model (LLM) generates sequences of tokens from the input it receives, using patterns learned during training. A model can produce text, code or structured proposals. The application around it supplies context, decides what tools are available and controls real-world actions.
Choosing a model is one decision inside an application design, not the whole design.
CONNECT IT TO WHAT YOU KNOW
Start with something familiar.
Think of a powerful, learned text transformation function with uncertain outputs. Unlike a normal lookup, it can compose an answer that was never stored as a record.
Plausible output is not a verified fact. Training knowledge, information supplied in the current request and live tool observations are different sources.
Words worth knowing
- Inference
- Using a trained model to produce output.
- Training
- Learning model parameters from data.
- Hallucination
- Generated content that appears plausible but is unsupported or incorrect.
ONE EXAMPLE / FICTIONAL CASE
Watch the work take shape.
The model writes a convincing maintenance instruction, but the approved procedure may have changed since the information it learned.
- 01Supply input
- 02Generate
- 03Check
Supply input
Provide the task, relevant approved evidence and output constraints.
A bounded requestFROM RECOGNITION TO REASONING
Separate model knowledge from current evidence.
- 01
Write a fictional procedure dated last week.
- 02
List which parts of a draft must come from that procedure.
- 03
State how the assistant responds if the procedure is unavailable.
A source requirement and an explicit cannot-answer case.
Compare your reasoning when you are ready
A model should not fill a missing current procedure with a confident guess. The application can require a source or route the case to a person.
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.
Plausible output is not a verified fact. Training knowledge, information supplied in the current request and live tool observations are different sources.
Academy lessons use your existing training access. Free guides stay open.
Learn with the original creators
A conceptual introduction published in 2023. Use it for the mental model; use current provider documentation for product setup.