A high-discipline execution framework for prompt and agent engineering, aligned with the IMPACT AI Product Management framework. The Impact Prompt + Agent Engineering Framework empowers AI teams to operationalize both prompt workflows and lightweight agent behaviors the way product and ML teams structure intelligent systems — with intent, metrics, and repeatability. Built for LLM-native teams deploying production-grade outputs. This framework is comprised of 8 structured stages that guide you from goal identification to agent-integrated, production-grade engineering. This is the operations layer for LLM-native systems. Build with intention. Optimize with discipline. Ship with clarity.Iterate, fork, or phase-out stale agents/prompts based on lifespan and metric performance
AI product development is breaking the boundaries of traditional software product frameworks. While most AI strategies stall in experimentation or scatter in execution, IMPACT AI PM Framework delivers a structured, repeatable system to drive alignment from model to market. Designed for product managers, AI leads, and cross-functional teams, it turns abstract ML ambition into shipped, measurable outcomes. From intelligent use case discovery to adaptive MLOps, it drives the full cycle from idea to infrastructure. This is the operating system for building AI products that don’t just launch — they lead.
Modern product teams don’t fail from lack of talent — they fail from lack of structure. The IMPACT Tech Product Management Framework is a six-stage execution system purpose-built for software and SaaS environments, turning ambiguity into clarity and features into outcomes. Designed for product managers, GTM leaders, and cross-functional squads, this framework embeds validation, prioritization, and telemetry into every stage. It’s how great teams move fast — without moving blind.
Modern technology projects suffer from familiar failure patterns: missed deadlines, unclear scope, fragmented communication, and stakeholder disappointment. These aren’t issues of incompetence — they stem from misalignment, mis-scoping, and lack of shared truth.
The IMPACT Technical Project Management framework restores clarity, alignment, and trust to how work moves from vision to launch. Built for TPMs, engineers, delivery leads, and stakeholder-heavy teams, it turns complexity into velocity without bureaucracy. This is not a theoretical model. It’s a practical execution architecture forged from real-world scars — and ready for immediate deployment.
Modern AI workflows are breaking the seams of traditional DevOps. While most MLOps frameworks either overfit to academic rigor or collapse under organizational friction, the IMPACT Vertex AI MLOps frameworkis engineered as a pragmatic execution system: scalable, composable, and deeply integrated with Google Cloud’s Vertex AI ecosystem. It exists to answer a clear need: a repeatable, production-ready framework that empowers product managers, data scientists, ML engineers, and platform leads to build intelligent systems on GCP Vertex AI that not only ship — but evolve.