SaasRise Research
Here is how the bootcamp works:
By the end of the four days every participant leaves with a working agentic engineering workflow, ready to apply to speeding up their company’s R&D process.
If you already use Claude Code, we’ll surround you with a group applying best practices to use it to its full potential for accelerating R&D velocity with quality. And if you don’t already use Claude Code, we’ll go deep on ensuring that by the end of the week you’ve fully integrated it into your product and engineering processes. We ran this as an 8 week program before. The feedback was incredible. We have now compressed the entire curriculum into 4 days so you get the knowledge and impact much more quickly. Back when I was building iContact to $50M ARR and 300 employees, if we had these tools and this process we would have moved so much faster. That is exactly why we built this. The old model of software development would take 6–12 weeks to get a new feature built. The steps were: Product Requirements Doc → Figma designs → Developer Builds → QA Team → Production. The new model of software development takes 1–3 days to get something meaningful built. The much simpler steps are: Specs → Prompt Claude Code → Automated QA Testing → Production. Our one developer can often knock out 10 user stories per day — an amount of work that used to take a month. Even if your R&D team is already playing around with AI coding tools, this will be an extraordinary group of peers and leaders for them to be within to ensure the very best practices are used for high-quality scalable software development in an AI-native world.
Let’s make sure your company is around and thriving for many years to come! All the best, Ryan Allis CEO & Founder, SaasRise
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We just published a comprehensive report on how engineering is fundamentally changing as AI agents move from experimentation to real production workflows. Here are some of the key findings:
The report covers the full agentic engineering landscape — from adoption data and the AI coding tool market, to how top teams are restructuring around agents and workflows. The bottom line: engineering is becoming a system of humans + agents, and the teams that adapt fastest will dramatically outperform.
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