Forward-Deployed Engineering
Forward-deployed engineering is a model where engineers work directly alongside a client, embedded in their environment, building custom solutions against real problems rather than shipping generic product from a distance. Palantir popularized the term, but the approach is older than the label—it is how defense contractors, management consultancies, and bespoke software shops have always operated when the problem is too specific for off-the-shelf tools. Alephic practices forward-deployed engineering because the gap between what AI can do in a demo and what it needs to do in a specific company's workflow is where most AI projects die. That gap does not close with better documentation or more features in a SaaS dashboard. It closes when an engineer who understands the model also understands the business context, the data, and the humans who will use the system.
Related terms:
System Prompt
A system prompt is an invisible set of instructions given to a language model—defining its persona, constraints, output format, and behavioral rules—and...
Linting
Linting is the automated analysis of code or any structured output to flag errors, enforce style rules, and catch problems before production.
Token
In large language models, a token is the basic unit of text—usually chunks of three to four characters—that the model reads and generates.