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Slingshot

Frameworks that actually change how teams build.

Methodologies, case studies, and deep dives into how DevObsessed integrates AI across the software development lifecycle.

01
Methodology

What Is Supervised Slingshot

A 5-week instructor-embedded program that transforms how engineering teams work with AI — combining group workshops, 1:1 coaching, and continuous measurement.

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02
Framework

How AI Is Used in the SDLC

AI integrated across every phase — from requirements gathering through QA — using structured workflows that deliver 20% overall efficiency gains.

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03
Insight

Why AI Adoption Fails in Engineering Teams

Most AI adoption fails because organizations treat it as a tooling rollout, not a behavioral transformation. The real blocker isn't technology — it's human psychology.

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04
Methodology

What Is LLM Kanban

A persistent Kanban-style board that gives LLMs external memory, time tracking, and structured workflows — solving the context window and session persistence problems.

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05
Case Studies

Case Studies

Real-world results from enterprise AI adoption deployments.

Case Study — The Amplifier

A Fortune 500 engineering firm with shallow AI adoption turned one team into the organization's AI leaders — 70% of the org's top AI users came from one team in 5 weeks.

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Case Study — The Multiplier

6 engineers at a global vehicle auction company went from autocomplete to organizational AI adoption in 7 weeks — 50% earned Champion status and tool proficiency jumped from 2.4 to 4.1.

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Case Study — From Access to Output

9 engineers at a global vehicle remarketing platform went from surface-level Copilot usage to shipping production-ready AI workflows in 5 weeks — collaboration improved 46% and 4 of 9 reached Champion status.

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Ready to see what's possible for your team?

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