Results for “context engineering”

…of safety testing to focus on what the system can do. The first engineering boundary is where the model belongs in execution. A participant relays a secondhand account of a Scale AI hackathon winner that used GPT as a backend: the simple…

…for granted. Further improvement would depend more on difficult engineering across chips and systems, increasing the value and potential pricing power of companies capable of doing it. Nvidia’s advantage is framed as system-wide expertise…

…it with consequential work. The team translated software engineering practices into observable behaviors that evaluators could grade: - Communicate progress: keep the developer informed while work is underway. - Plan when appropriate:…

…development through stronger reasoning, better understanding of engineering nuances, and longer context. GPT-4-level agents’ limits remained uncertain. The forecast was that future models could handle almost any reasonably well-scoped…

…Those models remain one component of a larger pipeline, making context utilization a practical concern: can a new model actually use the information supplied to it? Context utilization means successfully using information inside a prompt,…

…in five or ten minutes; if not, do not assume the agent can. Context engineering here means selecting useful information from a large enterprise corpus for the model to work with. Putting every potentially relevant file into the prompt is…

…back into focus, at a potentially much larger scale. AI engineering is presented as an emerging specialization, analogous to frontend, DevOps, and data engineering. The economic argument is that scarce research talent and GPUs concentrate…

…periods, without specifying a model, provider, or workload. The engineering task is to make the application responsive and reliable despite unpredictable timing, formats, and meaning. Elicit applies language models to scientific work and…

…the podcast’s growth as a rough proxy for the expanding AI engineering community. He recalls hundreds of people queuing for an applied AI talk at AWS re:Invent. swyx points to Gartner and GitHub adopting the term as signs that the category …

…data, training, fine-tuning, and continually curating local context to feed into models. The closing engineering advice connects the whole discussion: building useful AI applications requires models, system optimization, and data curation…

…search index. Beyang initially knew Steve Yegge through his engineering writing; a later talk connected Steve with the code-intelligence system he had used. Steve’s tooling interests reached back to a video game he began around 1995, which …

…large language model (LLM) applications combines sound software engineering with experimental machine-learning practice. Evaluations start by defining success: specify the objective, decide how to measure it, and connect that measure to the…