Practice · 2022–now · AI Present
Prompt engineering
Craft the magic string until the model behaves. Job title of 2023; table-stakes skill of 2026.
Prompt engineering mutated from a specialty into ordinary product work — versioned prompts, evals, and tool schemas. It failed as a standalone career when models improved and templates commoditized. The durable residue is treating prompts like code with tests.
Patterns
Context
The stack gets a co-pilot
AI pair programming is already changing how code is written. Agent frameworks and vector stores are still sorting winners from demos. The durable layer will look familiar: evals, retrieval quality, product UX, and ownership. Autopilot rewrites without tests are just big-bang migrations with better slides.
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Related
Framework · 2023–now
LLM app frameworks
Chains, agents, and prompt wrappers shipping weekly. The durable pieces will be boring: evals, retrieval, and product UX.
Practice · 2023–now
LLM eval pipelines
Regression tests for nondeterministic models. The unglamorous infrastructure that separates demos from products.
Practice · 2021–now
AI pair programming
Autocomplete that actually understands the file. Changing how code is written faster than how it's reviewed.