The DeepLearning.AI short course on Spec-Driven Development with Coding Agents introduces a professional paradigm shift in how we build applications using agentic coding assistance. Rather than "vibe coding"—where developers rely on quick, high-level prompts that often lead to technical debt—SDD brings engineering rigour back to the process. Agent is the muscle, but the SPEC is the brain - In this workflow, the human takes on the role of a senior architect, providing the "blueprints" (specifications), while the AI agent acts as the "muscle" to implement those designs. The 1 Hour 20 Minute video course has 15 short lessons - Introduction - 4 mins Why spec−driven development? - 4 mins Workflow overview - 3 mins Set up your environment - 5 mins Setup - 1 min Creating the constitution - 10 mins Feature specification - 3 mins Feature implementation - 1 min Feature validation -...
In response to a question about the feasibility of effective code reviews for large (e.g., 500-line) AI-generated PRs like those from Claude, especially when reviewers lack deep codebase familiarity in new projects or fast-paced environments, Uncle Bob Martin and Grady Booch have contrasting views Uncle Bob Martin advocates metrics-based oversight (test coverage, complexity, dependencies) and higher-level management over line-by-line AI code review, while Grady Booch stresses manual verification for vulnerabilities, dead code, and performance factors. Uncle Bob Martin : " I don’t review code written by agents . I measure things like test coverage, dependency structure, cyclomatic complexity, module sizes, mutation testing, etc. Much can be inferred about the quality of the code from those metrics. The code itself I leave to the AI. Humans are slow at code. To get productivity we humans need to disengage from code and manage from a higher level." Grady Booch : "Unlike B...
This Week I Learned - * From The Batch - - Alignment training teaches LLMs to behave like assistants, but it tethers them to that behavior only loosely. Beyond alignment training, system prompts act as behavioral guardrails, but motivated users can bypass them. - The lengths of tasks completed autonomously by AI agents have doubled roughly every seven months, according to METR, an independent testing organization - LLMs' knowledge is still relatively limited with respect to infrastructure and the complex tradeoffs good engineers must make...finding infrastructure bugs — say, a subtle network misconfiguration — can be incredibly difficult and requires deep engineering expertise. - Research involves thinking through new ideas, formulating hypotheses, running experiments, interpreting them to potentially modify the hypotheses, and iterating until we reach conclusions. Coding agents can speed up the pace at which we can write research code. - Meta has pivoted from its ope...
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