Dev-Lens

Problem: Developers spend hours translating codebase realities for non-technical stakeholders. When product managers ask "How hard is this feature?" or clients ask "Why is this refactor necessary?", developers must pause their core work, inspect multiple repositories, evaluate architectural impact, and translate complex technical nuances into language suited for specific audiences (PMs, clients, managers, or support). Existing AI coding tools either write code or produce generic summaries prone to hallucinations that lack grounded architectural validation. Solution: I built DevLens, a developer-first codebase intelligence tool that bridges the gap between a developer’s mental model and stakeholder questions. By combining multi-repository indexing, a personalized "Developer Lens", and dual-engine AI validation powered by IBM Granite, DevLens delivers structured, 7-section technical impact analyses (Current System, What Would Change, Affected Areas, Effort, Risks, Unknowns, and Internal Developer Reasoning) tailored to any selected audience. Target Users: Software engineers, tech leads, engineering managers, and technical product managers working with single repositories or multi-service microservices. How Users Interact With It: 1. Context & Component Indexing: Users connect GitHub repositories or multi-service projects, allowing DevLens to index file trees, dependencies, and architectural components. 2. Define the Developer Lens: Engineers configure their investigation methodology (e.g., test-driven, data-flow first) and communication preferences (bullet points, trade-off focus), creating a reusable mental model that can be published as a public share link. 3. Audience-Aware Analysis: Users ask any engineering question and select their audience (Developer, PM, Manager, Client, or Support). DevLens generates a structured, role-adapted breakdown. 4. Granite Evidence Validation: IBM Granite automatically audits the analysis against indexed codebase evidence, categorizing claims (SUPPORTED, WEAKLY_SUPPORTED, CONTRADICTED) and surfacing architectural anomalies. 5. Report Bot: Users curate multiple saved analyses into a paginated, print-ready PDF engineering report via Paprize. What Makes It Creative & Unique: - Dual-Engine Trust: Unlike single-prompt LLM wrappers, DevLens separates generation from verification. IBM Granite acts as an objective validator to ensure claims reflect actual code. - Developer Lens Personalization: DevLens explains systems the way you think, preserving individual engineering insights across team handoffs. - Multi-Audience Pitching: The exact same architectural change is automatically translated into executive summaries for management, sprint impact for PMs, or line-level reasoning for developers. Effectiveness & Efficiency: DevLens eliminates hours of manual drafting, cross-team misunderstandings, and unverified architectural assumptions. Running on a lightweight Cloudflare Worker with D1 SQLite persistence and non-blocking IBM Granite inference, DevLens provides instant, verified engineering intelligence with zero infrastructure overhead.